Patent Publication Number: US-11657456-B2

Title: Systems and methods for allocating resources using information technology infrastructure

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application claims the benefit of priority under 35 U.S.C. § 120 as a continuation of U.S. patent application Ser. No. 15/237,354, filed Aug. 15, 2016, which claims the benefit of priority under 35 U.S.C. § 119 to U.S. Prov. Pat. App. No. 62/268,235, filed Dec. 16, 2015, each of which is incorporated herein by reference in its entirety. 
    
    
     FIELD OF THE DISCLOSURE 
     The present solution is generally directed to allocating resources using an information technology infrastructure. In particular, the present solution can determine allocation of resources among electronic accounts based on predicted resource consumption over a time interval. 
     BACKGROUND OF THE DISCLOSURE 
     Entities can provide various types of electronic tax benefit accounts configured with parameters and rules. As the types of electronic tax benefit accounts configured with various parameters and rules increase, it may be challenging for customers of the accounts to efficiently allocate resources among the various types electronic accounts. 
     BRIEF SUMMARY OF THE DISCLOSURE 
     The systems and methods of the present solution are directed to the technical problems and challenges of implementing the functionality of resource allocation on an electronic transaction based technology and platform. Existing electronic transaction based technologies and platforms do not effectively and efficiently make use of the computing and network resources deployed for electronic transaction based technologies and platforms to include such functionality. Without implementing such functionality, existing electronic transaction based technologies and platforms have the problems of excessive server-client requests and responses, processing delays, increase bandwidth usage, or erroneous or inefficient resource allocation. 
     The systems and methods of the present solution are directed to the improvement of the performance and operation of the electronic transaction based technology and platform and computing and networking resource used by such electronic transaction based technology and platform. In some aspects, the present solution improves and enhances the implemented functionality of the electronic transaction based technology and platform implemented on, integrated with and inherently tied to the processor, memory, network and computing resources of one or more computing devices. In some aspects, the present solution more effectively performs the functionality of the electronic transaction based technology and platform thereby making and causing more effective use of the computing and networking resources to achieve the improved functionality of the present solution. The same computing and network resources used by such electronic transaction based technology and platform will provide increased and improved functionality with implementation of the present solution. 
     In some aspects, the present solution more efficiently uses the computing and networking resources to implement the improved functionality of the electronic transaction based technology and platform. For example, systems and methods of the present solution are directed to allocating resources using an information technology infrastructure. Systems and methods of the present solution can determine amounts of funds a participant should allocate to a healthcare tax benefit account to cover predicted lifetime healthcare expenses. 
     Administrators, such as companies or health insurance providers, can establish electronic benefits accounts such as flexible spending accounts or healthcare tax benefit accounts (e.g., health savings accounts) for participants such as employees, subscribers, or customers. These electronic benefits accounts can provide a tax advantage for the participants. As healthcare tax benefit accounts become increasingly popular, it may be challenging for participants of the accounts to determine how much and at what rate they should be allocating funds into the accounts for optimally taking advantage of the tax benefits to cover future known and unknown healthcare expenses. For example, a 401k retirement account may be configured with different parameters and rules as compared to a health savings accounts. Systems and methods of the present disclosure can determine a resource allocation among the 401k account and the health savings account to optimize a performance metric or reach a predicted lifetime healthcare expense. 
     Administrators that establish or provide electronic tax benefits accounts for various participants of those accounts can utilize backend information technology infrastructure to process, analyze, monitor or manage the electronic tax benefits accounts. An entity managing the backend information technology may have access to data regarding electronics tax benefit accounts across multiple administrators. This data may include financial and health information of the various participants across the various administrators, which the entity managing the backend information technology may advantageously utilize to provide unique services. 
     The present disclosure provides systems and methods of allocating resources using an information technology infrastructure. The interactive interface can include a report based on analyzing the financial and health data of the various participants across multiple administrators. For example, the system can use the data on participants in the system to build various profiles and saving or spending trends for those participants. The system enables existing or new participants to enter information about themselves, into an interactive interface, about their healthcare and retirement savings, income, or spending, and compare that to lifestyle profiles or expense prediction models to forecast the necessary retirement funds needed to fund not only their lifestyle, but their healthcare needs. Additionally the system can profile the economic advantage (e.g., tax advantage) of various retirement vehicles to determine the most beneficial savings approach for the participant (e.g., health savings accounts triple tax benefit vs. 401k vs. Roth IRA vs. other healthcare spending accounts like health retirement accounts and flexible spending accounts). 
     The system can be configured with a machine learning technique to constantly update and refine expense prediction models. The machine learning technique can be based on new financial and health data of the participants that is continuously received by the system. The system can parse the new information and determine how the data reinforces a predictive model or changes a predictive model. Upon receiving personal financial and health data from a participant seeking to identify how to optimally allocate funds to their electronic benefits accounts, the system can identify a predictive model based on the received information that is most similar to the seeking participant&#39;s information, and can then identify future healthcare and non-healthcare costs of the participant based on the identified predictive model. Based on the predicted expenses of the participant, the system can determine the economically optimal (e.g., most tax-advantaged) contribution scheme for the participant to invest in one or more healthcare benefits accounts and one or more non-healthcare benefits accounts (e.g., how much and into which accounts the participant should deposit funds). 
     Upon determining the optimal contribution plan, the system can generate an interactive interface for displaying the results of the system&#39;s calculations to the participant seeking the information. The interactive interface can include or be configured on a dashboard. In some cases, the interface can be provided or streamed over a data network. The interface can be configured to receive data manipulation indications via an input device, and the system can update the calculated results and display the results via the interface in real-time. For example, the interface can receive indications to manipulate the data corresponding to the amount of annual contribution to one or more of the electronic benefits account, the amount already saved in the accounts, health indicators (e.g., a promise to increase exercise activities), financial indicators (e.g., an imminent income raise), or the like. 
     In an illustrative embodiment, the system can provide payment processing infrastructure and technology to a plurality of administrators such as multiple insurance companies. The insurance companies can provide various types of insurance (e.g., health, dental, vision, car, property, legal, construction, etc.) to its customers. A customer of the insurance company can include an employer that has employees. The system can enable the employees that participate in the insurance company plans to initiate and receive a report indicating predicted expenses and a suggested contribution scheme to healthcare and non-healthcare benefits accounts for the employee. The suggestions presented to the employee are based on the health and financial data personal to the employee, and on the vast financial and health data of the various employees that are provided with the electronic benefits accounts from the multiple insurance companies. 
     At least one aspect of the present solution is directed to a system to allocate resources using an information technology infrastructure. The system can include a communication interface executed by one or more processors of a server and configured to receive financial data indicating a financial snapshot of a participant of a client device and health data of the participant to predict lifetime healthcare expenses of the participant. The system can include a forecast engine executed by the server. The forecast engine is executed to generate a multi-dimensional feature vector of the participant based on the received financial data and the health data of the participant. The forecast engine is executed to identify a healthcare expense prediction model to predict the future healthcare expenses of the participant, the healthcare expense prediction model generated by the server using financial data and health data of a plurality of participants. The forecast engine is executed to determine from the identified healthcare expense prediction model using the multi-dimensional feature vector of the participant, the predicted lifetime healthcare expenses of the participant. The forecast engine is executed to identify lifetime non-healthcare expenses of the participant. The forecast engine is executed to perform a lookup in a database to identify a healthcare tax benefit account of the participant to provide funds towards the predicted lifetime healthcare expenses of the participant and a non-healthcare tax benefit account of the participant to provide funds towards lifetime non-healthcare expenses of the participant. The forecast engine is executed to determine, based on the predicted lifetime healthcare expenses of the participant, a first amount of funds to allocate per time period to the healthcare tax benefit account. The forecast engine is executed to determine, based on the lifetime non-healthcare expenses of the participant, a second amount of funds to allocate per time period to the non-healthcare tax benefit account. The communication interface is executed to provide, for presentation via an interactive user interface, the first amount of funds to allocate to the healthcare tax benefit account and the second amount of funds to allocate to the non-healthcare tax benefit account, the interactive user interface including a control object configured to i) receive an input to adjust the first amount, and ii) responsive to receiving the input to adjust the first amount, updating a total amount of funds projected to be allocated to the healthcare tax benefit account. 
     In some embodiments, the server generates the interactive user interface with an electronic survey comprising one or more input elements, the interactive user interface configured to receive the financial data and the health data. 
     In some embodiments, the server generates the interactive user interface with a countdown timer set to a predetermined time interval, initiates the countdown timer responsive to enabling the interactive user interface to receive the financial data and the health data, and disables input via the interactive user interface responsive to expiration of the countdown timer. 
     In some embodiments, the server generates the multi-dimensional feature vector comprising a first feature indicating demographic information, a second feature indicating a healthcare spend amount, a third feature indicating a health savings account contribution amount, and a fourth feature indicating a health preference. 
     In some embodiments, the server can include a machine learning engine, and the machine learning engine is executed to train the healthcare expense prediction model with the financial data and the health data of the plurality of participants. 
     In some embodiments, the server inputs the multi-dimensional feature vector into the healthcare expense prediction model to output the predicted lifetime healthcare expenses of the participant, the predicted lifetime healthcare expenses of the participant based on data associated with similar participants used to generate the healthcare expense prediction model. 
     In some embodiments, the server determines the first amount of funds to allocate per time period to the healthcare tax benefit account using a first feature indicating demographic information, a second feature indicating a healthcare spend amount, a third feature indicating a health savings account contribution amount, and a fourth feature indicating a health preference 
     In some embodiments, the server determines the second amount of funds to allocate per time period to the non-healthcare tax benefit account using a first feature indicating demographic information, a second feature indicating a non-healthcare spend amount, and a third feature indicating a non-health retirement account contribution amount. 
     In some embodiments, the server determines a first allocation priority associated with the healthcare tax benefit account, and determines a second allocation priority associated with the non-healthcare tax benefit account, the second allocation priority less than the first allocation priority. 
     In some embodiments, the server determines the first amount of funds to allocate to the healthcare tax benefit account based on the first allocation priority, the second allocation priority, and the healthcare expense prediction model. 
     Another aspect of the present solution is directed to a method of allocating resources using an information technology infrastructure. A server including one or more processors receives financial data indicating a financial snapshot of a participant of a client device and health data of the participant to predict lifetime healthcare expenses of the participant. The server generates a multi-dimensional feature vector of the participant based on the received financial data and the health data of the participant. The server identifies a healthcare expense prediction model to predict the future healthcare expenses of the participant, the healthcare expense prediction model generated by the server using financial data and health data of a plurality of participants. The server determines from the identified healthcare expense prediction model using the multi-dimensional feature vector of the participant, the predicted lifetime healthcare expenses of the participant. The server identifies lifetime non-healthcare expenses of the participant. The server performs a lookup in a database to identify a healthcare tax benefit account of the participant to provide funds towards the predicted lifetime healthcare expenses of the participant and a non-healthcare tax benefit account of the participant to provide funds towards lifetime non-healthcare expenses of the participant. The server determines, based on the predicted lifetime healthcare expenses of the participant, a first amount of funds to allocate per time period to the healthcare tax benefit account. The server determines, based on the lifetime non-healthcare expenses of the participant, a second amount of funds to allocate per time period to the non-healthcare tax benefit account. The server provides, for presentation via an interactive user interface, the first amount of funds to allocate to the healthcare tax benefit account and the second amount of funds to allocate to the non-healthcare tax benefit account, the interactive user interface including a control object configured to i) receive an input to adjust the first amount, and ii) responsive to receiving the input to adjust the first amount, updating a total amount of funds projected to be allocated to the healthcare tax benefit account. 
     In some embodiments, the server generates the interactive user interface with an electronic survey comprising one or more input elements, the interactive user interface configured to receive the financial data and the health data. 
     In some embodiments, the server generates the interactive user interface with a countdown timer set to a predetermined time interval, initiates the countdown timer responsive to enabling the interactive user interface to receive the financial data and the health data, and disables input via the interactive user interface responsive to expiration of the countdown timer. 
     In some embodiments, the server generates the multi-dimensional feature vector comprising a first feature indicating demographic information, a second feature indicating a healthcare spend amount, a third feature indicating a health savings account contribution amount, and a fourth feature indicating a health preference. 
     In some embodiments, the server can include a machine learning engine, and the machine learning engine is executed to train the healthcare expense prediction model with the financial data and the health data of the plurality of participants. 
     In some embodiments, the server inputs the multi-dimensional feature vector into the healthcare expense prediction model to output the predicted lifetime healthcare expenses of the participant, the predicted lifetime healthcare expenses of the participant based on data associated with similar participants used to generate the healthcare expense prediction model. 
     In some embodiments, the server determines the first amount of funds to allocate per time period to the healthcare tax benefit account using a first feature indicating demographic information, a second feature indicating a healthcare spend amount, a third feature indicating a health savings account contribution amount, and a fourth feature indicating a health preference 
     In some embodiments, the server determines the second amount of funds to allocate per time period to the non-healthcare tax benefit account using a first feature indicating demographic information, a second feature indicating a non-healthcare spend amount, and a third feature indicating a non-health retirement account contribution amount. 
     In some embodiments, the server determines a first allocation priority associated with the healthcare tax benefit account, and determines a second allocation priority associated with the non-healthcare tax benefit account, the second allocation priority less than the first allocation priority. 
     In some embodiments, the server determines the first amount of funds to allocate to the healthcare tax benefit account based on the first allocation priority, the second allocation priority, and the healthcare expense prediction model. 
     At least one aspect of the present solution is directed to a system to manage information technology infrastructure. The system can include a device including one or more processors, the device configured with a tool that interfaces with a plurality of administrator devices remote from the device, the plurality of administrator devices each configured to administer one or more tax benefit accounts corresponding to one or more participants. The tool is executed to receive, via a network, an identifier of an administrator of an administrator device of the plurality of administrator devices. The tool is executed to retrieve, from an administrator profile data structure stored in memory, an administrator profile corresponding to the identifier. An administrator matching engine of the tool is executed to identify one or more administrator profiles stored in the administrator profile data structure of one or more different administrators. The administrator matching engine is executed to determine, based on a parameter matching technique, from the one or more identified administrator profiles, a similarity metric between the administrator profile and each of the identified one or more administrator profiles. The administrator matching engine is executed to identify the one or more administrator profiles having the similarity metric satisfying a predetermined threshold. A report generator of the tool is executed to instantiate a dynamic report interface to render for display via the administrator device, an electronic report indicating a first value of a first performance metric of the administrator based on the administrator profile and a second value of the first performance metric based on the identified one or more administrator profiles. The tool is executed to provide, via the dynamic report interface, the electronic report for display via the administrator device. 
     In some embodiments, the tool is further configured to receive, via the network from the administrator device, a parameter of the administrator profile, the parameter including at least one of an account opening fee, a minimum operating balance, a monthly fee, an annual fee, an electronic fund access type, or an interest rate. 
     In some embodiments, the tool is further configured to generate the administrator profile with parameters received from the administrator device, the administrator device configured to receive data from a plurality of participant devices corresponding to the one or more tax benefit accounts configured using the administrator profile. 
     In some embodiments, the tool is further configured to train, via a machine learning technique, an administrator profile model using a plurality of administrator profiles, and input a parameter of the administrator profile into the administrator profile model to determine the first value of the first performance metric. 
     In some embodiments, the tool is further configured to aggregate a plurality of administrator profiles corresponding to the plurality of administrator devices, and store the plurality of administrator profiles in the administrator profile data structure in memory. 
     In some embodiments, the tool is further configured to render the electronic report indicating the first value of the first performance metric based on a number of participants of the administrator during a time interval, and the second value of the first performance metric based on the number of customers of the identified one or more administrators. 
     In some embodiments, the tool is further configured to receive, via the instance of the dynamic report interface, an indication from the administrator device to adjust the time interval, and manipulate the first value of the first performance metric and the second value of the first performance metric indicated in the rendered electronic report responsive to the indication to adjust the time interval. 
     In some embodiments, the tool is further configured to receive, via the instance of the dynamic report interface, a filter criterion, use the filter criterion to identify a subset of the one or more administrator profiles stored in the administrator profile data structure, generate a third value of the first performance metric based on the subset of the one or more administrator profiles, render, via the dynamic report interface, the electronic report to indicate the first value of the first performance metric and the third value of the first performance metric, and remove the second value of the first performance metric from the rendered electronic report, the second value of the first performance metric being different from the third value of the first performance metric. 
     In some embodiments, the tool is further configured to receive an update to the administrator profile after the electronic report is rendered, generate a third value of the first performance metric based on the update to the administrator profile, and render, via the dynamic report interface, the electronic report to include the third value of the first performance metric and remove the first value of the first performance metric. 
     In some embodiments, the tool is further configured to render the electronic report for display on the administrator device via the dynamic report interface, and receive, from the administrator device via the dynamic report interface, an indication to manipulate the electronic report. 
     At least one aspect of the present solution is directed to a system for conducting electronic transactions via a computer network. The system can include a communication interface of a server having one or more processors to receive a request to adjudicate a single claim against an electronic benefits account. The system can include a policy engine executed by the one or more processors of the server to determine, responsive to the communication interface receiving the request to adjudicate the single claim, that the single claim against the electronic benefits account is approved for an amount of expenditures qualifying under the electronic benefits account. The policy engine is executed to identify, via a configuration of the electronic benefits account maintained by the server, a reimbursement policy of the electronic benefits account specifying an ordered list of account destinations for benefits account reimbursements. The electronic reimbursement account is configured to allow transactions for non-qualifying benefits account expenditures. The policy engine executed to update the electronic reimbursement account maintained by the server with a value corresponding to a credit for the approved amount for the single claim. The system can include a notification engine executed by the server to generate, responsive to the request adjudicated by the server and the update by the policy engine of the electronic reimbursement account with the value corresponding to the credit for the approved amount for the single claim, a notification identifying the update to the electronic reimbursement account corresponding to the credit. The notification engine is executed to transmit, via the computer network to a device of the electronic benefits account, a first one or more packets carrying data indicating the notification of the credit. 
     In some embodiments, the server is further configured to determine a balance of the electronic reimbursement account, the balance including the value used to update the electronic reimbursement account prior to transmission of the first one or more packets carrying data indicating the notification of the credit. The server can be further configured to transmit the first one or more packets responsive to determining the balance includes the value. 
     In some embodiments, the server is further configured to receive a second one or more packets carrying the request to adjudicate the single claim against the electronic benefits account, the request comprising a request data structure having a first field indicating a merchant ID, a second field indicating a total amount of expenditures, and a third field indicating the electronic benefits account. The server can be further configured to parse the second one or more packets to identify the electronic benefits account indicated via the third field. The server can be further configured to perform, with the identification of the electronic benefits account, a lookup in a benefits account policy database maintained in memory by the server. The server can be further configured to retrieve, responsive to the lookup, an electronic benefits account policy corresponding to the single claim against the electronic benefits account. The server can be further configured to generate, responsive to application of the electronic benefits account policy using the merchant ID and the total amount of expenditures, the indication that the single claim against the electronic benefits account is approved for the amount of expenditures qualifying under the electronic benefits account. 
     In some embodiments, the server is further configured to determine the amount of expenditures qualifying under the electronic benefits account is different from the total amount of expenditures. 
     In some embodiments, the server is further configured to receive, via the computer network, a second one or more packets carrying a request to adjudicate the single claim against the electronic benefits account, the request comprising a request data structure having a first field indicating a merchant ID, a second field indicating a total amount of expenditures, and a third field indicating the electronic benefits account. The server can be further configured to transmit the first one or more packets carrying data indicating the notification of the transferred credit within a predetermined time interval of receiving the second one or more packets. 
     In some embodiments, the server is further configured to receive a second one or more packets generated by a merchant device to conduct an electronic transaction at a merchant, the second one or more packets carrying data identifying a merchant category of the merchant, the electronic benefits account maintained and configured on the server, and a total monetary amount of the electronic transaction. The server can be further configured to transmit the first one or more packets carrying data indicating the notification of the transferred credit within a predetermined time interval of receiving the second one or more packets. 
     In some embodiments, the server is further configured to receive a second one or more packets generated by a merchant device to conduct an electronic transaction at a merchant, the second one or more packets carrying data identifying a merchant category of the merchant, the electronic benefits account maintained and configured on the server, and a total monetary amount of the electronic transaction. The server can be further configured to initiate a claim adjudication process responsive to receiving the second one or more packets. The server can be further configured to generate, responsive to initiating the single claim adjudication process, a second notification of the initiation. The server can be further configured to transmit, prior to transmission of the first one or more packets, a third one or more packets carrying data indicating the second notification of the initiation. 
     In some embodiments, the server is further configured to transmit the first one or more packets carrying data indicating the notification and the third one or more packets carrying data indicating the second notification with a predetermined time interval. 
     In some embodiments, the server is further configured to retrieve, responsive to transmission of the instructions including the value to update the electronic reimbursement account, an electronic report template configured for the electronic benefits account. The server can be further configured to generate the notification using the electronic report template to include a balance of the electronic reimbursement account subsequent to updating the electronic reimbursement account with the credit. The server can be further configured to transmit, to the device, the first one or more packets carrying data indicating the notification via at least one of a Short Message Service protocol or an electronic mail protocol. 
     In some embodiments, the server is further configured to perform a lookup in a profile database of the electronic benefits account to identify the device configured to receive notifications for the electronic benefits account. The server can be further configured to retrieve, from the profile database, a unique identifier for the device and a notification mode, the notification mode including at least one of a Short Message Service protocol or an electronic mail protocol. The server can be further configured to configure the first one or more packets carrying data indicating the notification based on the notification mode. 
     Another aspect of the present solution is directed to a method of managing electronic transactions via a computer network. A communication interface of a server receives a request to adjudicate a single claim against an electronic benefits account. The server can include one or more processors. A policy engine executed by the server determines, responsive to the communication interface receiving the request to adjudicate the single claim, that the single claim against the electronic benefits account is approved for an amount of expenditures qualifying under the electronic benefits account. The policy engine identifies, via a configuration of the electronic benefits account maintained by the server, a reimbursement policy of the electronic benefits account specifying an ordered list of account destinations for benefits account reimbursements. The policy engine determines, via application of the reimbursement policy to the single claim, an electronic reimbursement account as a destination for a benefits account reimbursement, the electronic reimbursement account configured to allow transactions for non-qualifying benefits account expenditures. The server transmits instructions to update the electronic reimbursement account maintained by the server with a value corresponding to a credit for the approved amount for the single claim. The server generates, responsive to the request adjudicated by the server and transmitting the instructions to update the electronic reimbursement account with the credit of the single claim, a notification identifying the update to the electronic reimbursement account corresponding to the credit of the single claim. The server transmits, via the computer network to a device of the electronic benefits account, a first one or more packets carrying data indicating the notification of the credit. 
     In some embodiments, the server determines a balance of the electronic reimbursement account. The balance can include the value used to update the electronic reimbursement account. The server can determine the balance prior to transmitting the first one or more packets carrying data indicating the notification of the credit. In some embodiments, the server transmits the first one or more packets responsive to determining the balance includes the value. 
     In some embodiments, the policy engine receives, via the computer network, a second one or more packets carrying the request to adjudicate the single claim against the electronic benefits account, the request comprising a request data structure having a first field indicating a merchant ID, a second field indicating a total amount of expenditures, and a third field indicating the electronic benefits account. The policy engine can the second one or more packets to identify the electronic benefits account indicated via the third field. The policy engine can perform a lookup in a benefits account policy database maintained in memory by the server using the identification of the electronic benefits account. The policy engine can retrieve, responsive to the lookup, a benefits account policy corresponding to the single claim against the electronic benefits account. The server can generate, responsive to application of the electronic benefits account policy using the merchant ID and the total amount of expenditures, the indication that the single claim against the electronic benefits account is approved for the amount of expenditures qualifying under the electronic benefits account. 
     In some embodiments, the server determines the amount of expenditures qualifying under the electronic benefits account is different from the total amount of expenditures. 
     In some embodiments, the server receives, via the computer network, a second one or more packets carrying a request to adjudicate the single claim against the electronic benefits account, the request comprising a request data structure having a first field indicating a merchant ID, a second field indicating a total amount of expenditures, and a third field indicating the electronic benefits account. The server can transmit the first one or more packets carrying data indicating the notification of the transferred credit within a predetermined time interval of receiving the second one or more packets. 
     In some embodiments, the server receives a second one or more packets generated by a merchant device to conduct an electronic transaction at a merchant, the second one or more packets carrying data identifying a merchant category of the merchant, the electronic benefits account maintained and configured on the server, and a total monetary amount of the electronic transaction. The server can transmit the first one or more packets carrying data indicating the notification of the transferred credit within a predetermined time interval of receiving the second one or more packets. 
     In some embodiments, the server can receive a second one or more packets generated by a merchant device to conduct an electronic transaction at a merchant, the second one or more packets carrying data identifying a merchant category of the merchant, the electronic benefits account maintained and configured on the server, and a total monetary amount of the electronic transaction. The server can initiate a claim adjudication process responsive to receiving the second one or more packets. The server can generate, responsive to initiating the single claim adjudication process, a second notification of the initiation. The server can transmit, prior to transmission of the first one or more packets, a third one or more packets carrying data indicating the second notification of the initiation. 
     In some embodiments, the server can transmit the first one or more packets carrying data indicating the notification and the third one or more packets carrying data indicating the second notification with a predetermined time interval. 
     In some embodiments, the server can retrieve, responsive to transmitting the instructions including the value to update the electronic reimbursement account, an electronic report template configured for the electronic benefits account. The server can generate the notification using the electronic report template to include a balance of the electronic reimbursement account subsequent to updating the electronic reimbursement account with the credit. The server can transmit, to the device, the first one or more packets carrying data indicating the notification via at least one of a Short Message Service protocol or an electronic mail protocol. 
     In some embodiments, the server can perform a lookup in a profile database of the electronic benefits account to identify the device configured to receive notifications for the electronic benefits account. The server can retrieve, from the profile database, a unique identifier for the device and a notification mode, the notification mode including at least one of a Short Message Service protocol or an electronic mail protocol. The server can configure the first one or more packets carrying data indicating the notification based on the notification mode. 
     At least one aspect of the present solution is directed to a method of managing electronic transactions via a computer network. A communications interface of a server receives a first one or more data packets via a network protocol. The server can include one or more processors. The first one or more data packets can be generated by a first device at a first merchant to conduct a first electronic transaction at the first merchant. The first one or more data packets can include first header information and first payload information carrying data. The first one or more data packets can carry data identifying a first merchant category of the first merchant, an electronic account maintained and configured on the server, and a first monetary amount of the first electronic transaction. A policy engine executing on the one or more processors of the server selects a first purse of a plurality of purses allocated to the electronic account maintained by the server based on a first policy applied to the data. The first purse can be configured as a purse with funds exempt from payroll tax deductions to be used to conduct approved transactions. The server obtains the first monetary amount of the first electronic transaction from the first purse of the electronic account. The policy engine applies a second policy to the data to determine a reimbursement amount based on the first monetary amount of the transaction. The server electronically provides, via the computer network, the reimbursement amount to a second purse of the electronic account. The second purse can be different from the first purse. 
     In some embodiments, the server selects the first purse based on the first policy applied to the first merchant category. In some embodiments, the server provides a real-time notification of the reimbursement amount responsive to transferring the reimbursement amount to the second purse of the electronic account. In some embodiments, the policy engine determines that the first purse of the electronic purse is configured for prescription purchases. The server can select the first purse responsive to determining that the first merchant is a prescription provider based on the first merchant category. 
     In some embodiments, the server receives a second one or more data packets generated by a second device at a second merchant to conduct a second electronic transaction at the second merchant. The second one or more data packets can carry second data indicating a second merchant category of the second merchant, the electronic account, and a second monetary amount of the second electronic transaction. The policy engine can use the first policy to select the second purse of the electronic account based on the second merchant category. The server can provide an indication to use the second account for at least a portion of the secondary monetary amount. In some embodiments, the server can select the first account for a first portion of the second monetary amount based on the second merchant category matching the first account. The server can select the second account for a second portion of the second monetary amount based on an available balance in the first account being less than the second monetary amount of the second transaction. 
     In some embodiments, the server can select the second purse responsive to determining that the first purse is not configured for the second merchant category of the second merchant. In some embodiments, the server can map, using the first policy, the first merchant to the first purse based on the first merchant category and a first configuration of the first purse. The server can use the first policy to map the second merchant to the second purse based on the second merchant category and a second configuration of the second purse. 
     In some embodiments, the server can retrieve, from a policy repository stored in memory, the second policy using an identifier of the electronic account. In some embodiments, the server can access a data record in memory for the electronic account. The data record can include a first available amount and a first configuration for the first purse, and a second available amount and a second configuration for the second purse. The server can determine, based on the first available amount and the first configuration, to use the first purse for the first electronic transaction. The server can determine, based on the first available amount and the first configuration, not to use the second purse for the first electronic transaction. The server can determine, based on the first configuration, not to use the first purse for a second electronic transaction. The server can determine, based on the second available amount and the second configuration, to use the second purse for the second electronic transaction. 
     In some embodiments, the server can receive a request from a client device for information about the electronic account. The server can authenticate the request from the client device using credentials associated with the request. The server can access a data record in memory for the electronic account. The data record can include a first available amount for the first purse, and a second available amount for the second purse. The server can provide for display on the client device a report indicating the first available amount and the second available amount. 
     In some embodiments, the server can receive the request via a Short Message Service protocol from the client device. The client device can be a mobile telecommunications device. The server can provide the report via at least one of the Short Message Service protocol or an electronic mail protocol. 
     Another aspect of the present solution is directed to a system to conduct electronic transactions via a computer network. The system can include a server having one or more processors and a communication interface. The system can include a policy engine and a transaction engine. The communications interface receives, via a network protocol, a first one or more data packets generated by a first device at a first merchant to conduct a first electronic transaction at the first merchant. The first one or more data packets carry data identifying a first merchant category of the first merchant, an electronic account, and a first monetary amount of the first electronic transaction. The policy engine selects a first purse of a plurality of purses allocated to the electronic account maintained by the server based on a first policy applied to the data. The first purse can be configured as a purse with funds exempt from payroll tax deductions to be used to conduct approved transactions. The transaction engine obtains the first monetary amount of the first electronic transaction from the first purse of the electronic account. The policy engine applies a second policy to the data to determine a reimbursement amount based on the first monetary amount of the transaction. The transaction engine provides, via a network, the reimbursement amount to a second purse of the electronic account, the second purse different from the first purse. 
     In some embodiments, the server provides a real-time notification of the reimbursement amount responsive to transferring the reimbursement amount to the second purse of the electronic account. In some embodiments, the server determines that the first purse of the electronic purse is configured for prescription purchases. The server can select the first purse responsive to determining that the first merchant is a prescription provider based on the first merchant category. 
     In some embodiments, the server receives a second one or more data packets generated by a second device at a second merchant to conduct a second electronic transaction at the second merchant. The second one or more data packets carry second data indicating a second merchant category of the second merchant, the electronic account, and a second monetary amount of the second electronic transaction. The server can use the first policy to select the second purse of the electronic account based on the second merchant category. The server can provide an indication to use the second account for at least a portion of the secondary monetary amount. 
     In some embodiments, the server can select the second purse responsive to determining that the first purse is not configured for the second merchant category of the second merchant. In some embodiments, the server can use the first policy to map the first merchant to the first purse based on the first merchant category and a first configuration of the first purse. The server can use the first policy to map the second merchant to the second purse based on the second merchant category and a second configuration of the second purse. 
     In some embodiments, the server can access a data record in memory for the electronic account. The data record can include a first available amount and a first configuration for the first purse, and a second available amount and a second configuration for the second purse. The server can determine, based on the first available amount and the first configuration, to use the first purse for the first electronic transaction. The server can determine, based on the first available amount and the first configuration, not to use the second purse for the first electronic transaction. The server can determine, based on the first configuration, not to use the first purse for a second electronic transaction. The server can determine, based on the second available amount and the second configuration, to use the second purse for the second electronic transaction. 
     In some embodiments, the server can receive a request from a client device for information about the electronic account. The server can authenticate the request from the client device using credentials associated with the request. The server can access a data record in memory for the electronic account. The data record can include a first available amount for the first purse, and a second available amount for the second purse. The server can provide, for display on the client device, a report indicating the first available amount and the second available amount. 
     At least one aspect of the present solution is directed to a system to manage resource allocation via an information technology infrastructure. The system can include a server including one or more processors configured to provide to a plurality of devices corresponding to a plurality of heterogeneous electronic funding sources, an electronic benefits account transaction application programming interface (“API”) configured to receive transaction requests from the plurality of heterogeneous electronic funding sources, and configured to receive, via the electronic benefits account transaction API, from a first device of the plurality of devices corresponding to a first electronic funding source of the plurality of heterogeneous electronic transaction sources, a first one or more packets comprising a request to initiate a single electronic benefits account transaction to fund an electronic benefits account. The request can identify a transaction destination, a transaction code, a transaction amount and an identifier identifying the first electronic funding source. The server can include an enforcement engine configured on an executed by the server. The enforcement engine is executed to determine the transaction code maps to one of a current year or a previous year. The enforcement engine is executed to perform a lookup in an electronic transaction queue of the electronic benefits account maintained in memory by the server to identify an in-process transaction amount and a reportable contribution amount. The enforcement engine is executed to generate a value by combining the transaction amount, the in-process transaction amount and the reportable contribution amount identified from the electronic transaction queue of the electronic benefits account maintained in memory by the server. The value can indicate a virtual transaction balance. The enforcement engine is executed to compare the value with a threshold limit for the one of the current year or the previous year mapped to the transaction code to determine that the value exceeds the threshold limit. The enforcement engine is executed to select an alert format configured for an interface corresponding to the first electronic funding source. The enforcement engine is executed to transmit, via a network to the first device, one or more packets carrying data in the alert format indicating a denial of the single electronic benefits account transaction request responsive to the comparison and the transaction code mapping to the one of the current year or the previous year. The one or more packets can be configured to indicate to the first device termination of the single electronic benefits account transaction initiated by the request to prevent exceeding the threshold limit established for the electronic benefits account. 
     In some embodiments, the enforcement engine is further configured to identify using a profile database stored in memory, that the first electronic funding source enforces electronic benefits account limits, and determine, responsive to identifying that the first electronic funding source enforces electronic benefits account limits, the transaction code maps to one of the current year or the previous year. 
     In some embodiments, the enforcement engine is further configured to determine an enforcement rule based on the single electronic benefits account transaction request, and identify the threshold limit based on the enforcement rule. 
     In some embodiments, the enforcement engine is further configured to generate the value by summing the transaction amount, the in-process transaction amount and the reportable contribution amount identified. 
     In some embodiments, the enforcement engine is further configured to select the threshold limit based on a predetermined threshold limit configured for the electronic funding source. 
     In some embodiments, the enforcement engine is further configured to receive the request to initiate a single electronic benefits account transaction, the request initiated by a remote device that is remote to the first device and configured with authentication credentials to access the first device. 
     In some embodiments, the enforcement engine is further configured to generate an alert in the alert format that includes instructions to terminate the single electronic benefits account transaction initiated by the request to prevent exceeding the threshold limit established for the electronic benefits account. 
     In some embodiments, the enforcement engine is further configured to establish a bidirectional communication channel with the first device, the bidirectional communication channel configured to transfer requests and instructions to terminate transactions. 
     In some embodiments, the enforcement engine is further configured to transmit, via the network to the first device, the response packets indicating the denial of the single electronic benefits account transaction request within a predetermined time interval from receiving the single electronic benefits account request. 
     In some embodiments, the enforcement engine is further configured to determine that the electronic funding source corresponds to a funded payroll deposit, select the alert format corresponding to the funded payroll deposit, the alert format comprising a first field for the instructions to deny the single electronic benefits account transaction and a second field for a reason code, generate an alert in the alert format that includes instructions to terminate the single electronic benefits account transaction and a reason code, and transmit the one or more response packets carrying the alert. 
     In some embodiments, the enforcement engine is further configured to access a profile database to determine that the electronic funding source corresponds to a non-payroll deposit, select the alert format for the instructions to terminate the single electronic benefits account transaction corresponding to the non-payroll deposit, the alert format including a first field for a reason code, and a second field for instructions to exclude the transaction from the in-process transaction amount, generate an alert in the alert format that includes instructions to terminate the single electronic benefits account transaction, the reason code, the instructions to exclude the transaction from the in-process transaction amount, and transmit the one or more response packets carrying the alert. 
     In some embodiments, the enforcement engine is further configured to receive a second one or more packets comprising a second request to initiate a second single electronic benefits account transaction to fund the electronic benefits account, the second request including a second data structure identifying the transaction destination, the transaction code, a second transaction amount and the first electronic funding source, generate a second value by combining the second transaction amount, the in-process transaction amount and the reportable contribution amount identified from the electronic transaction queue of the electronic benefits account maintained in memory by the server, the second value different from the value, determine the second value is less than the threshold limit based on a comparison of the second value with the threshold limit, and generate, responsive to the second value being less than the threshold limit, second response packets to authorize the second single electronic benefits account transaction. 
     Another aspect of the present solution is directed to a method of managing resources via information technology infrastructure. A server including one or more processor provides, to a plurality of devices corresponding to a plurality of heterogeneous electronic funding sources, an electronic benefits account transaction application programming interface (“API”) configured to receive transaction requests from the plurality of heterogeneous electronic funding sources. The server receives via the electronic benefits account transaction API, from a first device of the plurality of devices corresponding to a first electronic funding source of the plurality of heterogeneous electronic transaction sources, a first one or more packets comprising a request to initiate a single electronic benefits account transaction to fund an electronic benefits account, the request identifying a transaction destination, a transaction code, a transaction amount and an identifier identifying the first electronic funding source. The server executes an enforcement engine to determine that the transaction code maps to one of a current year or a previous year. The executes the enforcement engine to perform a lookup in an electronic transaction queue of the electronic benefits account maintained in memory by the server to identify an in-process transaction amount and a reportable contribution amount. The server executes the enforcement engine to generate a value by combining the transaction amount, the in-process transaction amount and the reportable contribution amount identified from the electronic transaction queue of the electronic benefits account maintained in memory by the server, setting generated value to indicate a virtual transaction balance. The server executes the enforcement engine to compare the value with a threshold limit for the one of the current year or the previous year mapped to the transaction code to determine that the value exceeds the threshold limit based on the comparison. The server executes the enforcement engine to select an alert format configured for an interface corresponding to the first electronic funding source. The server executes the enforcement engine to transmit, via a network to the first device, one or more response packets carrying data in the alert format indicating a denial of the single electronic benefits account transaction request responsive to the comparison and the transaction code mapping to the one of the current year or the previous year, the one or more packets configured to indicate to the first device termination of the single electronic benefits account transaction initiated by the request to prevent exceeding the threshold limit established for the electronic benefits account. 
     In some embodiments, the server executes the enforcement engine to identify, using a profile database stored in memory, that the first electronic funding source enforces electronic benefits account limits, and determine responsive to identifying that the first electronic funding source enforces electronic benefits account limits, the transaction code maps to one of the current year or the previous year. 
     In some embodiments, the server executes the enforcement engine to determine an enforcement rule based on the single electronic benefits account transaction request, and identify the threshold limit based on the enforcement rule. 
     In some embodiments, the server executes the enforcement engine to generate the value by summing the transaction amount, the in-process transaction amount and the reportable contribution amount identified. 
     In some embodiments, the server executes the enforcement engine to select the threshold limit based on a predetermined threshold limit configured for the electronic funding source. 
     In some embodiments, the server executes the enforcement engine to receive the request to initiate a single electronic benefits account transaction, the request initiated by a remote device that is remote to the first device and configured with authentication credentials to access the first device. 
     In some embodiments, the server executes the enforcement engine to generate an alert in the alert format that includes instructions to terminate the single electronic benefits account transaction initiated by the request to prevent exceeding the threshold limit established for the electronic benefits account, and transmit the alert to the first device to cause the first device to terminate the transaction, the transaction initiated by a remote device remote to the first device. 
     In some embodiments, the server executes the enforcement engine to transmit, via the network to the first device, the response packets indicating the denial of the single electronic benefits account transaction request within a predetermined time interval from receiving the single electronic benefits account request. 
     At least one aspect of the present solution is directed to a system to manage information technology infrastructure. The system can include a device including one or more processors, the device configured with a tool that interfaces with a plurality of administrator devices remote from the device, the plurality of administrator devices each configured to administer one or more tax benefit accounts corresponding to one or more participants. The tool is executed to receive, via a network, an identifier of an administrator of an administrator device of the plurality of administrator devices. The tool is executed to retrieve, from an administrator profile data structure stored in memory, an administrator profile corresponding to the identifier. An administrator matching engine of the tool is executed to identify one or more administrator profiles stored in the administrator profile data structure of one or more different administrators. The administrator matching engine is executed to determine, based on a parameter matching technique, from the one or more identified administrator profiles, a similarity metric between the administrator profile and each of the identified one or more administrator profiles. The administrator matching engine is executed to identify the one or more administrator profiles having the similarity metric satisfying a predetermined threshold. A report generator of the tool is executed to instantiate a dynamic report interface to render for display via the administrator device, an electronic report indicating a first value of a first performance metric of the administrator based on the administrator profile and a second value of the first performance metric based on the identified one or more administrator profiles. The tool is executed to provide, via the dynamic report interface, the electronic report for display via the administrator device. 
     In some embodiments, the tool is further configured to receive, via the network from the administrator device, a parameter of the administrator profile, the parameter including at least one of an account opening fee, a minimum operating balance, a monthly fee, an annual fee, an electronic fund access type, or an interest rate. 
     In some embodiments, the tool is further configured to generate the administrator profile with parameters received from the administrator device, the administrator device configured to receive data from a plurality of participant devices corresponding to the one or more tax benefit accounts configured using the administrator profile. 
     In some embodiments, the tool is further configured to train, via a machine learning technique, an administrator profile model using a plurality of administrator profiles, and input a parameter of the administrator profile into the administrator profile model to determine the first value of the first performance metric. 
     In some embodiments, the tool is further configured to aggregate a plurality of administrator profiles corresponding to the plurality of administrator devices, and store the plurality of administrator profiles in the administrator profile data structure in memory. 
     In some embodiments, the tool is further configured to render the electronic report indicating the first value of the first performance metric based on a number of participants of the administrator during a time interval, and the second value of the first performance metric based on the number of customers of the identified one or more administrators. 
     In some embodiments, the tool is further configured to receive, via the instance of the dynamic report interface, an indication from the administrator device to adjust the time interval, and manipulate the first value of the first performance metric and the second value of the first performance metric indicated in the rendered electronic report responsive to the indication to adjust the time interval. 
     In some embodiments, the tool is further configured to receive, via the instance of the dynamic report interface, a filter criterion, use the filter criterion to identify a subset of the one or more administrator profiles stored in the administrator profile data structure, generate a third value of the first performance metric based on the subset of the one or more administrator profiles, render, via the dynamic report interface, the electronic report to indicate the first value of the first performance metric and the third value of the first performance metric, and remove the second value of the first performance metric from the rendered electronic report, the second value of the first performance metric being different from the third value of the first performance metric. 
     In some embodiments, the tool is further configured to receive an update to the administrator profile after the electronic report is rendered, generate a third value of the first performance metric based on the update to the administrator profile, and render, via the dynamic report interface, the electronic report to include the third value of the first performance metric and remove the first value of the first performance metric. 
     In some embodiments, the tool is further configured to render the electronic report for display on the administrator device via the dynamic report interface, and receive, from the administrator device via the dynamic report interface, an indication to manipulate the electronic report. 
     Another aspect of the present solution is directed to a method of managing information technology infrastructure. A tool executed by one or more processors of a device that interfaces with a plurality of administrator devices remote from the device receives, via a network, an identifier of an administrator of an administrator device of a plurality of administrator devices, the plurality of administrator devices each configured to administer one or more tax benefit accounts corresponding to one or more participants. The tool retrieves from an administrator profile data structure stored in memory, an administrator profile corresponding to the identifier. The tool executes an administrator matching engine to identify, based on a parameter matching technique, one or more administrator profiles of one or more different administrators stored in the administrator profile data structure. The tool determines, based on the parameter matching technique from the one or more identified administrator profiles, a similarity metric between the administrator profile and each of the one or more administrator profiles. The tool identifies the one or more administrator profiles having the similarity metric satisfying a similarity threshold. The tool executes a report generator to generate an instance of a dynamic report interface to render for display via the administrator device, an electronic report indicating a first value of a first performance metric of the administrator based on the administrator profile and a second value of a first performance metric based on the identified one or more administrator profiles. The tool provides, via the dynamic report interface, the electronic report for display via the administrator device. 
     In some embodiments, the tool receives, via the network from the administrator device, a parameter of the administrator profile, the parameter including at least one of an account opening fee, a minimum operating balance, a monthly fee, an annual fee, an electronic fund access type, or an interest rate. 
     In some embodiments, the tool generates the administrator profile with parameters received from the administrator device, the administrator device configured to receive data from a plurality of participant devices corresponding to the one or more tax benefit accounts configured using the administrator profile. 
     In some embodiments, the tool trains, via a machine learning technique, an administrator profile model using a plurality of administrator profiles, and determines the first value of a first performance metric based on an output from the administrator profile model responsive to a parameter of the administrator profile input into the administrator profile model. 
     In some embodiments, the tool aggregates a plurality of administrator profiles corresponding to the plurality of administrator devices, and stores the plurality of administrator profiles in the administrator profile data structure in memory. 
     In some embodiments, the tool renders the electronic report indicating the first value of a first performance metric based on a number of participants of the administrator during a time interval, and the second value of a first performance metric based on the number of customers of the identified one or more administrators. 
     In some embodiments, the tool receives, via the instance of the dynamic report interface, an indication from the administrator device to adjust the time interval, and manipulates the first value of a first performance metric and the second value of a first performance metric indicated in the rendered electronic report responsive to the indication to adjust the time interval. 
     In some embodiments, the tool receives, via the instance of the dynamic report interface, a filter criterion, uses the filter criterion to identify a subset of the one or more administrator profiles stored in the administrator profile data structure, generates a third value of a first performance metric based on the subset of the one or more administrator profiles, renders via the dynamic report interface, the electronic report to indicate the first value of a first performance metric and the third value of a first performance metric, and removes the second value of a first performance metric from the rendered electronic report, the second value of a first performance metric different from the third value of a first performance metric. 
     In some embodiments, the tool receives an update to the administrator profile after the electronic report is rendered, generates a third value of the first performance metric based on the update to the administrator profile, and renders via the dynamic report interface, the electronic report to include the third value of the first performance metric and remove the first value of the first performance metric. 
     In some embodiments, the tool renders the electronic report for display on the administrator device via the dynamic report interface, and receives from the administrator device via the dynamic report interface, an indication to manipulate the electronic report. 
     At least one aspect of the present disclosure is directed to a system to reduce resource consumption via information technology infrastructure. The system can include one or more servers with one or more processors and memory. The system can include a communications interface, a forecast engine, and a notification engine executed by one or more servers. In some embodiments, the communications interface can receive one or more data packets including data indicating a healthcare transaction event corresponding to a participant of a plurality of participants of a healthcare management platform. The forecast engine can select a healthcare trend model to provide healthcare related recommendations to the plurality of participants of the healthcare management platform maintained by the server. The healthcare trend model can be trained by the server using previously received data packets including data indicating healthcare transaction events corresponding to the plurality of participants of the healthcare management platform. The notification engine can perform a lookup in a recommendation data structure using an identifier of the selected healthcare trend model to identify a plurality of healthcare related recommendations linked with the selected healthcare trend model. The notification engine can determine a correlation coefficient between each of the plurality of healthcare related recommendations and the selected healthcare trend model. The notification engine can select, based on a rank of each correlation coefficient, a highest ranking healthcare related recommendation of the plurality of healthcare related recommendations. The notification engine can retrieve, responsive to the selection of the highest ranking healthcare related recommendation, a notification template from a notification data structure that maps to the highest ranking healthcare related recommendation. The notification engine can generate, using the notification template, a notification corresponding to the highest ranking healthcare related recommendation. The notification engine can generate a request to deliver the notification corresponding to the highest ranking healthcare related recommendation at a destination address of a computing device of the participant. The notification engine can transmit the notification to the computing device of the participant responsive to the request. The notification engine can transmit the notification to the computing device via a communication channel established between the server and the computing device. 
     The healthcare transaction events can include one or more of a claim payment, a card denial, a password change, or a received deposit. In some embodiments, the healthcare transaction event can include a denial. The server can be further configured to retrieve a denial healthcare trend model responsive to the healthcare transaction event including the denial. The server can be further configured to select, based on the denial healthcare trend model, a denial recommendation that includes a recommended processing configuration. The server can select the denial recommendation responsive to a processing configuration that resulted in the denial healthcare transaction event. In some cases, the server can select a denial recommendation that includes a recommended resource allocation responsive to determining that an insufficient amount of resources resulted in the denial healthcare transaction event. In some cases, the server can select a denial recommendation that includes an ordered list including at least one qualifying item and at least one non-qualifying item responsive to determining that the denial healthcare transaction event resulted from a transaction including one or more qualifying items and one or more non-qualifying items. 
     In some embodiments, the server can categorize the healthcare transaction event into a first category selected from a plurality of categories. The server can determine, from the healthcare trend model, that a metric of the first category meets or exceeds a threshold for the first category. The server can select, responsive to the determination of the metric meeting or exceeding the threshold, the highest ranking healthcare related recommendation. 
     In some embodiments, the server can generate a first vector based on the healthcare transaction event and one or more healthcare transaction events of the participants. The server can identify a second vector for each of a plurality of healthcare transaction events. The server can determine for each of the plurality of healthcare transaction events, a distance between the first vector and the second vector. The server can identify a minimum distance from the determined distance for each of the plurality of healthcare transaction events. The server can select the healthcare trend model corresponding to the minimum distance. 
     In some embodiments, the server can categorize the healthcare transaction event into a first category selected from a plurality of categories. The server can determine, from the healthcare trend model, that a metric of the first category is below a threshold. The server can select, responsive to the determination of the metric below the threshold, the highest ranking healthcare related recommendation. 
     In some embodiments, the system can include the healthcare management platform. The healthcare management platform can receive electronic healthcare transactions. The healthcare management platform can process the electronic healthcare transaction to cause healthcare transaction events. The healthcare management platform can store the healthcare transaction events in a database. 
     In some embodiments, the server can receive the previously received data packets from a device of an administrator remote from the server via an administrator interface rendered by the server on the device of the administrator. 
     Another aspect of the present disclosure is directed to a method of reducing resource consumption via information technology infrastructure. In some embodiments, the method can include the server receiving, via a communications interface, one or more data packets including data indicating a healthcare transaction event corresponding to a participant of a plurality of participants of a healthcare management platform. The method can include the server identifying a healthcare trend model to provide healthcare related recommendations to the plurality of participants of the healthcare management platform maintained by the server. The healthcare trend model can be trained by the server using previously received data packets including data indicating healthcare transaction events corresponding to the plurality of participants of the healthcare management platform. The method can include the server performing a lookup in a recommendation data structure using an identifier of the selected healthcare trend model to identify a plurality of healthcare related recommendations linked with the selected healthcare trend model. The method can include the server determining a correlation coefficient between each of the plurality of healthcare related recommendations and the selected healthcare trend model. The method can include the server selecting, based on a rank of each correlation coefficient, a highest ranking healthcare related recommendation of the plurality of healthcare related recommendations. The method can include the server retrieving a notification template from a notification data structure that maps to the highest ranking healthcare related recommendation. The server can retrieve the notification template responsive to selecting the highest ranking healthcare related recommendation. The method can include the server configuring a notification engine with the notification template to generate a notification corresponding to the highest ranking healthcare related recommendation. The method can include the notification engine of the server generating a request to deliver the notification corresponding to the highest ranking healthcare related recommendation at a destination address of a computing device of the participant. The method can include the server transmitting the notification to the computing device of the participant. The server can transmit the notification responsive to the request and via a communication channel established between the server and the computing device. 
     In some embodiments, the method can include the server retrieving a denial healthcare trend model responsive to the healthcare transaction event including a denial. The method can include the server selecting, based on the denial healthcare trend model, a denial recommendation that includes a recommended processing configuration. The server can select the denial healthcare trend model responsive to a processing configuration that resulted in the denial healthcare transaction event. In some embodiments, the method can include the the server selecting, based on the denial healthcare trend model, a denial recommendation comprising a recommended resource allocation responsive to determining that an insufficient amount of resources resulted in the denial healthcare transaction event. In some embodiments, the method can include the server selecting, based on the denial healthcare trend model, a denial recommendation that includes an ordered list. The ordered list can include at least one qualifying item and at least one non-qualifying item. The server can select the denial recommendation with the ordered list responsive to determining that the denial healthcare transaction event resulted from a transaction including one or more qualifying items and one or more non-qualifying items. 
     In some embodiments, the method includes the server categorizing the healthcare transaction event into a first category selected from a plurality of categories. The method can include the server determining, from the healthcare trend model, that a metric of the first category meets or exceeds a threshold for the first category. The method can include the server selecting, responsive to determining the metric meeting or exceeding the threshold, the highest ranking healthcare related recommendation. 
     In some embodiments, the method includes the server generating a first vector based on the healthcare transaction event and one or more healthcare transaction events of the participants. The method can include the server identifying a second vector for each of a plurality of healthcare transaction events. The method can include the server determining, for each of the plurality of healthcare transaction events, a distance vector between the first vector and the second vector. The method can include the server identifying a minimum distance vector from the determined distance vector for each of the plurality of healthcare transaction events. The method can include the server selecting the healthcare trend model corresponding to the minimum distance vector. 
     In some embodiments, the method can include the server categorizing the healthcare transaction event into a first category selected from a plurality of categories. The method can include the server determining, from the healthcare trend model, that a metric of the first category falls below a threshold. The method can include the server selecting, responsive to determining that the metric falls below the threshold, the highest ranking healthcare related recommendation. 
     In some embodiments, the method can include the healthcare management platform receiving electronic healthcare transactions. The method can include the healthcare management platform processing the electronic healthcare transaction to cause healthcare transaction events. The method can include the healthcare management platform storing, in a database, the healthcare transaction events. In some embodiments, the healthcare transaction events can include one or more of a claim payment, a card denial, a password change, or a received deposit. In some embodiments, the method includes the server receiving the previously received data packets from a device of an administrator remote from the server via an administrator interface rendered by the server on the device of the administrator. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The foregoing and other objects, aspects, features, and advantages of the disclosure will become more apparent and better understood by referring to the following description taken in conjunction with the accompanying drawings, in which: 
         FIG.  1 A  is a block diagram depicting an embodiment of a network environment comprising client device in communication with server device; 
         FIG.  1 B  is a block diagram depicting a cloud computing environment comprising a client device in communication with cloud service providers; 
         FIGS.  1 C and  1 D  are block diagrams depicting embodiments of computing devices useful in connection with the methods and systems described herein; 
         FIG.  2    is a block diagram depicting an embodiment of a system for conducting electronic transactions via a computer network; 
         FIG.  3    is a flow diagram depicting an embodiment of a method of conducting electronic transactions; 
         FIG.  4    is a block diagram depicting an embodiment of a system for conducting electronic transactions via a computer network; 
         FIG.  5    is a block diagram depicting an embodiment of a system for organizing and communicating data transmissions for conducting electronic transactions via a computer network; 
         FIG.  6    is a flow diagram depicting an embodiment of a method of conducting electronic transactions; 
         FIG.  7    is a block diagram depicting an embodiment of an electronic transactional portal system for funding electronic benefits accounts; 
         FIG.  8    is a flow diagram depicting an embodiment of a method of operating an electronic transactional portal for funding electronic benefits accounts; 
         FIGS.  9 A- 9 D  are process flow diagrams depicting embodiments of operating an electronic transaction portal for funding electronic benefits accounts; 
         FIGS.  10 A- 10 D  are block diagrams depicting embodiments of electronic transaction portal system interfaces for funding electronic benefits accounts; 
         FIG.  11    is a block diagram depicting an embodiment of a system for managing information technology infrastructure; 
         FIGS.  12 A and  12 B  are diagrams depicting a dynamic report interface associated with an administrator matching and report generating system; 
         FIG.  13    is a flow diagram depicting an embodiment of a method of managing information technology infrastructure; 
         FIG.  14    is a block diagram depicting an embodiment of a system for allocating resources using an information technology infrastructure; 
         FIG.  15 A- 15 D  are diagrams depicting an interactive user interface associated with a predictive resource allocating system; 
         FIG.  16    is a flow diagram depicting an embodiment of a method of allocating resources using an information technology infrastructure; 
         FIG.  17    is a block diagram depicting an embodiment of a system to reduce resource consumption via information technology infrastructure; and 
         FIG.  18    is a block diagram depicting an embodiment of a method for reducing resource consumption via information technology infrastructure. 
     
    
    
     The features and advantages of the present invention will become more apparent from the detailed description set forth below when taken in conjunction with the drawings, in which like reference characters identify corresponding elements throughout. In the drawings, like reference numbers generally indicate identical, functionally similar, or structurally similar elements. 
     DETAILED DESCRIPTION 
     For purposes of reading the description of the various embodiments below, the following descriptions of the sections of the specification and their respective contents can be helpful: 
     Section A describes a network environment and computing environment which can be useful for practicing embodiments described herein. 
     Section B describes embodiments of systems and methods for conducting electronic transactions. 
     Section C describes embodiments of systems and methods for using a multi-purse card and providing notifications relating to the electronic transactions. 
     Section D describes embodiments of systems and methods for managing electronic transactions using a transaction portal. 
     Section E describes embodiments of systems and methods for managing information technology infrastructure using an administrator matching and report generating system. 
     Section F describes embodiments of systems and methods for allocating resources using a predictive resource allocating system. 
     Section G describes embodiments of systems and methods for reducing resource consumption via information technology infrastructure. 
     A. Computing and Network Environment 
     Prior to discussing specific embodiments of the present solution, it can be helpful to describe aspects of the operating environment as well as associated system components (e.g., hardware elements) in connection with the methods and systems described herein. Referring to  FIG.  1 A , an embodiment of a network environment is depicted. In brief overview, the network environment includes one or more clients  102   a - 102   n  (also generally referred to as local machine(s)  102 , client(s)  102 , client node(s)  102 , client machine(s)  102 , client computer(s)  102 , client device(s)  102 , endpoint(s)  102 , or endpoint node(s)  102 ) in communication with one or more servers  106   a - 106   n  (also generally referred to as server(s)  106 , node  106 , or remote machine(s)  106 ) via one or more networks  104 . In some embodiments, a client  102  has the capacity to function as both a client node seeking access to resources provided by a server and as a server providing access to hosted resources for other clients  102   a - 102   n.    
     Although  FIG.  1 A  shows a network  104  between the clients  102  and the servers  106 , the clients  102  and the servers  106  can be on the same network  104 . In some embodiments, there are multiple networks  104  between the clients  102  and the servers  106 . In one of these embodiments, a network  104 ′ (not shown) can be a private network and a network  104  can be a public network. In another of these embodiments, a network  104  can be a private network and a network  104 ′ a public network. In still another of these embodiments, networks  104  and  104 ′ can both be private networks. 
     The network  104  can be connected via wired or wireless links. Wired links can include Digital Subscriber Line (DSL), coaxial cable lines, or optical fiber lines. The wireless links can include BLUETOOTH, Wi-Fi, Worldwide Interoperability for Microwave Access (WiMAX), an infrared channel or satellite band. The wireless links can also include any cellular network standards used to communicate among mobile devices, including standards that qualify as 1G, 2G, 3G, or 4G. The network standards can qualify as one or more generation of mobile telecommunication standards by fulfilling a specification or standards such as the specifications maintained by International Telecommunication Union. The 3G standards, for example, can correspond to the International Mobile Telecommunications-2000 (IMT-2000) specification, and the 4G standards can correspond to the International Mobile Telecommunications Advanced (IMT-Advanced) specification. Examples of cellular network standards include AMPS, GSM, GPRS, UMTS, LTE, LTE Advanced, Mobile WiMAX, and WiMAX-Advanced. Cellular network standards can use various channel access methods e.g. FDMA, TDMA, CDMA, or SDMA. In some embodiments, different types of data can be transmitted via different links and standards. In other embodiments, the same types of data can be transmitted via different links and standards. 
     The network  104  can be any type and/or form of network. The geographical scope of the network  104  can vary widely and the network  104  can be a body area network (BAN), a personal area network (PAN), a local-area network (LAN), e.g. Intranet, a metropolitan area network (MAN), a wide area network (WAN), or the Internet. The topology of the network  104  can be of any form and can include, e.g., any of the following: point-to-point, bus, star, ring, mesh, or tree. The network  104  can be an overlay network which is virtual and sits on top of one or more layers of other networks  104 ′. The network  104  can be of any such network topology as known to those ordinarily skilled in the art capable of supporting the operations described herein. The network  104  can utilize different techniques and layers or stacks of protocols, including, e.g., the Ethernet protocol, the internet protocol suite (TCP/IP), the ATM (Asynchronous Transfer Mode) technique, the SONET (Synchronous Optical Networking) protocol, or the SDH (Synchronous Digital Hierarchy) protocol. The TCP/IP internet protocol suite can include application layer, transport layer, internet layer (including, e.g., IPv6), or the link layer. The network  104  can be a type of a broadcast network, a telecommunications network, a data communication network, or a computer network. 
     In some embodiments, the system can include multiple, logically-grouped servers  106 . In one of these embodiments, the logical group of servers can be referred to as a server farm  38  or a machine farm  38 . In another of these embodiments, the servers  106  can be geographically dispersed. In other embodiments, a machine farm  38  can be administered as a single entity. In still other embodiments, the machine farm  38  includes a plurality of machine farms  38 . The servers  106  within each machine farm  38  can be heterogeneous—one or more of the servers  106  or machines  106  can operate according to one type of operating system platform (e.g., WINDOWS NT, manufactured by Microsoft Corp. of Redmond, Wash.), while one or more of the other servers  106  can operate on according to another type of operating system platform (e.g., Unix, Linux, or Mac OS X). 
     In one embodiment, servers  106  in the machine farm  38  can be stored in high-density rack systems, along with associated storage systems, and located in an enterprise data center. In this embodiment, consolidating the servers  106  in this way can improve system manageability, data security, the physical security of the system, and system performance by locating servers  106  and high performance storage systems on localized high performance networks. Centralizing the servers  106  and storage systems and coupling them with advanced system management tools allows more efficient use of server resources. 
     The servers  106  of each machine farm  38  do not need to be physically proximate to another server  106  in the same machine farm  38 . Thus, the group of servers  106  logically grouped as a machine farm  38  can be interconnected using a wide-area network (WAN) connection or a metropolitan-area network (MAN) connection. For example, a machine farm  38  can include servers  106  physically located in different continents or different regions of a continent, country, state, city, campus, or room. Data transmission speeds between servers  106  in the machine farm  38  can be increased if the servers  106  are connected using a local-area network (LAN) connection or some form of direct connection. Additionally, a heterogeneous machine farm  38  can include one or more servers  106  operating according to a type of operating system, while one or more other servers  106  execute one or more types of hypervisors rather than operating systems. In these embodiments, hypervisors can be used to emulate virtual hardware, partition physical hardware, virtualize physical hardware, and execute virtual machines that provide access to computing environments, allowing multiple operating systems to run concurrently on a host computer. Native hypervisors can run directly on the host computer. Hypervisors can include VMware ESX/ESXi, manufactured by VMWare, Inc., of Palo Alto, Calif.; the Xen hypervisor, an open source product whose development is overseen by Citrix Systems, Inc.; the HYPER-V hypervisors provided by Microsoft or others. Hosted hypervisors can run within an operating system on a second software level. Examples of hosted hypervisors can include VMware Workstation and VIRTUALBOX. 
     Management of the machine farm  38  can be de-centralized. For example, one or more servers  106  can comprise components, subsystems and modules to support one or more management services for the machine farm  38 . In one of these embodiments, one or more servers  106  provide functionality for management of dynamic data, including techniques for handling failover, data replication, and increasing the robustness of the machine farm  38 . Each server  106  can communicate with a persistent store and, in some embodiments, with a dynamic store. 
     Server  106  can be a file server, application server, web server, proxy server, appliance, network appliance, gateway, gateway server, virtualization server, deployment server, SSL VPN server, or firewall. In one embodiment, the server  106  can be referred to as a remote machine or a node. In another embodiment, a plurality of nodes  290  can be in the path between any two communicating servers. 
     Referring to  FIG.  1 B , a cloud computing environment is depicted. A cloud computing environment can provide client  102  with one or more resources provided by a network environment. The cloud computing environment can include one or more clients  102   a - 102   n , in communication with the cloud  108  over one or more networks  104 . Clients  102  can include, e.g., thick clients, thin clients, and zero clients. A thick client can provide at least some functionality even when disconnected from the cloud  108  or servers  106 . A thin client or a zero client can depend on the connection to the cloud  108  or server  106  to provide functionality. A zero client can depend on the cloud  108  or other networks  104  or servers  106  to retrieve operating system data for the client device. The cloud  108  can include back end platforms, e.g., servers  106 , storage, server farms or data centers. 
     The cloud  108  can be public, private, or hybrid. Public clouds can include public servers  106  that are maintained by third parties to the clients  102  or the owners of the clients. The servers  106  can be located off-site in remote geographical locations as disclosed above or otherwise. Public clouds can be connected to the servers  106  over a public network. Private clouds can include private servers  106  that are physically maintained by clients  102  or owners of clients. Private clouds can be connected to the servers  106  over a private network  104 . Hybrid clouds  108  can include both the private and public networks  104  and servers  106 . 
     The cloud  108  can also include a cloud based delivery, e.g. Software as a Service (SaaS)  110 , Platform as a Service (PaaS)  112 , and Infrastructure as a Service (IaaS)  114 . IaaS can refer to a user renting the use of infrastructure resources that are needed during a specified time period. IaaS providers can offer storage, networking, servers or virtualization resources from large pools, allowing the users to quickly scale up by accessing more resources as needed. Examples of IaaS can include infrastructure and services (e.g., EG-32) provided by OVH HOSTING of Montreal, Quebec, Canada, AMAZON WEB SERVICES provided by Amazon.com, Inc., of Seattle, Wash., RACKSPACE CLOUD provided by Rackspace US, Inc., of San Antonio, Tex., Google Compute Engine provided by Google Inc. of Mountain View, Calif., or RIGHTSCALE provided by RightScale, Inc., of Santa Barbara, Calif. PaaS providers can offer functionality provided by IaaS, including, e.g., storage, networking, servers or virtualization, as well as additional resources such as, e.g., the operating system, middleware, or runtime resources. Examples of PaaS include WINDOWS AZURE provided by Microsoft Corporation of Redmond, Wash., Google App Engine provided by Google Inc., and HEROKU provided by Heroku, Inc. of San Francisco, Calif. SaaS providers can offer the resources that PaaS provides, including storage, networking, servers, virtualization, operating system, middleware, or runtime resources. In some embodiments, SaaS providers can offer additional resources including, e.g., data and application resources. Examples of SaaS include GOOGLE APPS provided by Google Inc., SALESFORCE provided by Salesforce.com Inc. of San Francisco, Calif., or OFFICE 365 provided by Microsoft Corporation. Examples of SaaS can also include data storage providers, e.g. DROPBOX provided by Dropbox, Inc. of San Francisco, Calif., Microsoft SKYDRIVE provided by Microsoft Corporation, Google Drive provided by Google Inc., or Apple ICLOUD provided by Apple Inc. of Cupertino, Calif. 
     Clients  102  can access IaaS resources with one or more IaaS standards, including, e.g., Amazon Elastic Compute Cloud (EC2), Open Cloud Computing Interface (OCCI), Cloud Infrastructure Management Interface (CIMI), or OpenStack standards. Some IaaS standards can allow clients access to resources over HTTP, and can use Representational State Transfer (REST) protocol or Simple Object Access Protocol (SOAP). Clients  102  can access PaaS resources with different PaaS interfaces. Some PaaS interfaces use HTTP packages, standard Java APIs, JavaMail API, Java Data Objects (JDO), Java Persistence API (JPA), Python APIs, web integration APIs for different programming languages including, e.g., Rack for Ruby, WSGI for Python, or PSGI for Perl, or other APIs that can be built on REST, HTTP, XML, or other protocols. Clients  102  can access SaaS resources through the use of web-based user interfaces, provided by a web browser (e.g. GOOGLE CHROME, Microsoft INTERNET EXPLORER, or Mozilla Firefox provided by Mozilla Foundation of Mountain View, Calif.). Clients  102  can also access SaaS resources through smartphone or tablet applications, including, e.g., Salesforce Sales Cloud, or Google Drive app. Clients  102  can also access SaaS resources through the client operating system, including, e.g., Windows file system for DROPBOX. 
     In some embodiments, access to IaaS, PaaS, or SaaS resources can be authenticated. For example, a server or authentication server can authenticate a user via security certificates, HTTPS, or API keys. API keys can include various encryption standards such as, e.g., Advanced Encryption Standard (AES). Data resources can be sent over Transport Layer Security (TLS) or Secure Sockets Layer (SSL). 
     The client  102  and server  106  can be deployed as and/or executed on any type and form of computing device, e.g. a computer, network device or appliance capable of communicating on any type and form of network and performing the operations described herein.  FIGS.  1 C and  1 D  depict block diagrams of a computing device  100  useful for practicing an embodiment of the client  102  or a server  106 . As shown in  FIGS.  1 C and  1 D , each computing device  100  includes a central processing unit  121 , and a main memory unit  122 . As shown in  FIG.  1 C , a computing device  100  can include a storage device  128 , an installation device  116 , a network interface  118 , an I/O controller  123 , display devices  124   a - 124   n , a keyboard  126  and a pointing device  127 , e.g. a mouse. The storage device  128  can include, without limitation, an operating system, software, and a software of a multi-purse transaction system (MPTS)  120 . As shown in  FIG.  1 D , each computing device  100  can also include additional optional elements, e.g. a memory port  103 , a bridge  170 , one or more input/output devices  130   a - 130   n  (generally referred to using reference numeral  130 ), and a cache memory  140  in communication with the central processing unit  121 . 
     The central processing unit  121  is any logic circuitry that responds to and processes instructions fetched from the main memory unit  122 . In many embodiments, the central processing unit  121  is provided by a microprocessor unit, e.g.: those manufactured by Intel Corporation of Mountain View, Calif.; those manufactured by Motorola Corporation of Schaumburg, Ill.; the ARM processor and TEGRA system on a chip (SoC) manufactured by Nvidia of Santa Clara, Calif.; the POWER7 processor, those manufactured by International Business Machines of White Plains, N.Y.; or those manufactured by Advanced Micro Devices of Sunnyvale, Calif. The computing device  100  can be based on any of these processors, or any other processor capable of operating as described herein. The central processing unit  121  can utilize instruction level parallelism, thread level parallelism, different levels of cache, and multi-core processors. A multi-core processor can include two or more processing units on a single computing component. Examples of multi-core processors include the AMD PHENOM IIX2, INTEL CORE i5 and INTEL CORE i7. 
     Main memory unit  122  can include one or more memory chips capable of storing data and allowing any storage location to be directly accessed by the microprocessor  121 . Main memory unit  122  can be volatile and faster than storage  128  memory. Main memory units  122  can be Dynamic random access memory (DRAM) or any variants, including static random access memory (SRAM), Burst SRAM or SynchBurst SRAM (BSRAM), Fast Page Mode DRAM (FPM DRAM), Enhanced DRAM (EDRAM), Extended Data Output RAM (EDO RAM), Extended Data Output DRAM (EDO DRAM), Burst Extended Data Output DRAM (BEDO DRAM), Single Data Rate Synchronous DRAM (SDR SDRAM), Double Data Rate SDRAM (DDR SDRAM), Direct Rambus DRAM (DRDRAM), or Extreme Data Rate DRAM (XDR DRAM). In some embodiments, the main memory  122  or the storage  128  can be non-volatile; e.g., non-volatile read access memory (NVRAM), flash memory non-volatile static RAM (nvSRAM), Ferroelectric RAM (FeRAM), Magnetoresistive RAM (MRAM), Phase-change memory (PRAM), conductive-bridging RAM (CBRAM), Silicon-Oxide-Nitride-Oxide-Silicon (SONOS), Resistive RAM (RRAM), Racetrack, Nano-RAM (NRAM), or Millipede memory. The main memory  122  can be based on any of the above described memory chips, or any other available memory chips capable of operating as described herein. In the embodiment shown in  FIG.  1 C , the processor  121  communicates with main memory  122  via a system bus  150  (described in more detail below).  FIG.  1 D  depicts an embodiment of a computing device  100  in which the processor communicates directly with main memory  122  via a memory port  103 . For example, in  FIG.  1 D  the main memory  122  can be DRDRAM. 
       FIG.  1 D  depicts an embodiment in which the main processor  121  communicates directly with cache memory  140  via a secondary bus, sometimes referred to as a backside bus. In other embodiments, the main processor  121  communicates with cache memory  140  using the system bus  150 . Cache memory  140  typically has a faster response time than main memory  122  and is typically provided by SRAM, BSRAM, or EDRAM. In the embodiment shown in  FIG.  1 D , the processor  121  communicates with various I/O devices  130  via a local system bus  150 . Various buses can be used to connect the central processing unit  121  to any of the I/O devices  130 , including a PCI bus, a PCI-X bus, or a PCI-Express bus, or a NuBus. For embodiments in which the I/O device is a video display  124 , the processor  121  can use an Advanced Graphics Port (AGP) to communicate with the display  124  or the I/O controller  123  for the display  124 .  FIG.  1 D  depicts an embodiment of a computer  100  in which the main processor  121  communicates directly with I/O device  130   b  or other processors  121 ′ via HYPERTRANSPORT, RAPIDIO, or INFINIBAND communications technology.  FIG.  1 D  also depicts an embodiment in which local busses and direct communication are mixed: the processor  121  communicates with I/O device  130   a  using a local interconnect bus while communicating with I/O device  130   b  directly. 
     A wide variety of I/O devices  130   a - 130   n  can be present in the computing device  100 . Input devices can include keyboards, mice, trackpads, trackballs, touchpads, touch mice, multi-touch touchpads and touch mice, microphones, multi-array microphones, drawing tablets, cameras, single-lens reflex camera (SLR), digital SLR (DSLR), CMOS sensors, accelerometers, infrared optical sensors, pressure sensors, magnetometer sensors, angular rate sensors, depth sensors, proximity sensors, ambient light sensors, gyroscopic sensors, or other sensors. Output devices can include video displays, graphical displays, speakers, headphones, inkjet printers, laser printers, and 3D printers. 
     Devices  130   a - 130   n  can include a combination of multiple input or output devices, including, e.g., Microsoft KINECT, Nintendo Wiimote for the WII, Nintendo WII U GAMEPAD, or Apple IPHONE. Some devices  130   a - 130   n  allow gesture recognition inputs through combining some of the inputs and outputs. Some devices  130   a - 130   n  provides for facial recognition which can be utilized as an input for different purposes including authentication and other commands. Some devices  130   a - 130   n  provides for voice recognition and inputs, including, e.g., Microsoft KINECT, SIRI for IPHONE by Apple, Google Now or Google Voice Search. 
     Additional devices  130   a - 130   n  have both input and output capabilities, including, e.g., haptic feedback devices, touchscreen displays, or multi-touch displays. Touchscreen, multi-touch displays, touchpads, touch mice, or other touch sensing devices can use different technologies to sense touch, including, e.g., capacitive, surface capacitive, projected capacitive touch (PCT), in-cell capacitive, resistive, infrared, waveguide, dispersive signal touch (DST), in-cell optical, surface acoustic wave (SAW), bending wave touch (BWT), or force-based sensing technologies. Some multi-touch devices can allow two or more contact points with the surface, allowing advanced functionality including, e.g., pinch, spread, rotate, scroll, or other gestures. Some touchscreen devices, including, e.g., Microsoft PIXELSENSE or Multi-Touch Collaboration Wall, can have larger surfaces, such as on a table-top or on a wall, and can also interact with other electronic devices. Some I/O devices  130   a - 130   n , display devices  124   a - 124   n  or group of devices can be augment reality devices. The I/O devices can be controlled by an I/O controller  123  as shown in  FIG.  1 C . The I/O controller can control one or more I/O devices, such as, e.g., a keyboard  126  and a pointing device  127 , e.g., a mouse or optical pen. Furthermore, an I/O device can also provide storage and/or an installation medium  116  for the computing device  100 . In still other embodiments, the computing device  100  can provide USB connections (not shown) to receive handheld USB storage devices. In further embodiments, an I/O device  130  can be a bridge between the system bus  150  and an external communication bus, e.g. a USB bus, a SCSI bus, a FireWire bus, an Ethernet bus, a Gigabit Ethernet bus, a Fibre Channel bus, or a Thunderbolt bus. 
     In some embodiments, display devices  124   a - 124   n  can be connected to I/O controller  123 . Display devices can include, e.g., liquid crystal displays (LCD), thin film transistor LCD (TFT-LCD), blue phase LCD, electronic papers (e-ink) displays, flexile displays, light emitting diode displays (LED), digital light processing (DLP) displays, liquid crystal on silicon (LCOS) displays, organic light-emitting diode (OLED) displays, active-matrix organic light-emitting diode (AMOLED) displays, liquid crystal laser displays, time-multiplexed optical shutter (TMOS) displays, or 3D displays. Examples of 3D displays can use, e.g. stereoscopy, polarization filters, active shutters, or autostereoscopy. Display devices  124   a - 124   n  can also be a head-mounted display (HMD). In some embodiments, display devices  124   a - 124   n  or the corresponding I/O controllers  123  can be controlled through or have hardware support for OPENGL or DIRECTX API or other graphics libraries. 
     In some embodiments, the computing device  100  can include or connect to multiple display devices  124   a - 124   n , which each can be of the same or different type and/or form. As such, any of the I/O devices  130   a - 130   n  and/or the I/O controller  123  can include any type and/or form of suitable hardware, software, or combination of hardware and software to support, enable or provide for the connection and use of multiple display devices  124   a - 124   n  by the computing device  100 . For example, the computing device  100  can include any type and/or form of video adapter, video card, driver, and/or library to interface, communicate, connect or otherwise use the display devices  124   a - 124   n . In one embodiment, a video adapter can include multiple connectors to interface to multiple display devices  124   a - 124   n . In other embodiments, the computing device  100  can include multiple video adapters, with each video adapter connected to one or more of the display devices  124   a - 124   n . In some embodiments, any portion of the operating system of the computing device  100  can be configured for using multiple displays  124   a - 124   n . In other embodiments, one or more of the display devices  124   a - 124   n  can be provided by one or more other computing devices  100   a  or  100   b  connected to the computing device  100 , via the network  104 . In some embodiments software can be designed and constructed to use another computer&#39;s display device as a second display device  124   a  for the computing device  100 . For example, in one embodiment, an Apple iPad can connect to a computing device  100  and use the display of the device  100  as an additional display screen that can be used as an extended desktop. One ordinarily skilled in the art will recognize and appreciate the various ways and embodiments that a computing device  100  can be configured to have multiple display devices  124   a - 124   n.    
     Referring again to  FIG.  1 C , the computing device  100  can comprise a storage device  128  (e.g. one or more hard disk drives or redundant arrays of independent disks) for storing an operating system or other related software, and for storing application software programs such as any program related to the software  120  for the multi-purse transaction system. Examples of storage device  128  include, e.g., hard disk drive (HDD); optical drive including CD drive, DVD drive, or BLU-RAY drive; solid-state drive (SSD); USB flash drive; or any other device suitable for storing data. Some storage devices can include multiple volatile and non-volatile memories, including, e.g., solid state hybrid drives that combine hard disks with solid state cache. Some storage device  128  can be non-volatile, mutable, or read-only. Some storage device  128  can be internal and connect to the computing device  100  via a bus  150 . Some storage device  128  can be external and connect to the computing device  100  via a I/O device  130  that provides an external bus. Some storage device  128  can connect to the computing device  100  via the network interface  118  over a network  104 , including, e.g., the Remote Disk for MACBOOK AIR by Apple. Some client devices  100  may not require a non-volatile storage device  128  and can be thin clients or zero clients  102 . Some storage device  128  can also be used as an installation device  116 , and can be suitable for installing software and programs. Additionally, the operating system and the software can be run from a bootable medium, for example, a bootable CD, e.g. KNOPPIX, a bootable CD for GNU/Linux that is available as a GNU/Linux distribution from knoppix.net. 
     Client device  100  can also install software or application from an application distribution platform. Examples of application distribution platforms include the App Store for iOS provided by Apple, Inc., the Mac App Store provided by Apple, Inc., GOOGLE PLAY for Android OS provided by Google Inc., Chrome Webstore for CHROME OS provided by Google Inc., and Amazon Appstore for Android OS and KINDLE FIRE provided by Amazon.com, Inc. An application distribution platform can facilitate installation of software on a client device  102 . An application distribution platform can include a repository of applications on a server  106  or a cloud  108 , which the clients  102   a - 102   n  can access over a network  104 . An application distribution platform can include application developed and provided by various developers. A user of a client device  102  can select, purchase and/or download an application via the application distribution platform. 
     Furthermore, the computing device  100  can include a network interface  118  to interface to the network  104  through a variety of connections including, but not limited to, standard telephone lines LAN or WAN links (e.g., 802.11, T1, T3, Gigabit Ethernet, Infiniband), broadband connections (e.g., ISDN, Frame Relay, ATM, Gigabit Ethernet, Ethernet-over-SONET, ADSL, VDSL, BPON, GPON, fiber optical including FiOS), wireless connections, or some combination of any or all of the above. Connections can be established using a variety of communication protocols (e.g., TCP/IP, Ethernet, ARCNET, SONET, SDH, Fiber Distributed Data Interface (FDDI), IEEE 802.11a/b/g/n/ac CDMA, GSM, WiMax and direct asynchronous connections). In one embodiment, the computing device  100  communicates with other computing devices  100 ′ via any type and/or form of gateway or tunneling protocol e.g. Secure Socket Layer (SSL) or Transport Layer Security (TLS), or the Citrix Gateway Protocol manufactured by Citrix Systems, Inc. of Ft. Lauderdale, Fla. The network interface  118  can comprise a built-in network adapter, network interface card, PCMCIA network card, EXPRESSCARD network card, card bus network adapter, wireless network adapter, USB network adapter, modem or any other device suitable for interfacing the computing device  100  to any type of network capable of communication and performing the operations described herein. 
     A computing device  100  of the sort depicted in  FIGS.  1 B and  1 C  can operate under the control of an operating system, which controls scheduling of tasks and access to system resources. The computing device  100  can be running any operating system such as any of the versions of the MICROSOFT WINDOWS operating systems, the different releases of the Unix and Linux operating systems, any version of the MAC OS for Macintosh computers, any embedded operating system, any real-time operating system, any open source operating system, any proprietary operating system, any operating systems for mobile computing devices, or any other operating system capable of running on the computing device and performing the operations described herein. Typical operating systems include, but are not limited to: WINDOWS 2000, WINDOWS Server 2012, WINDOWS CE, WINDOWS Phone, WINDOWS XP, WINDOWS VISTA, and WINDOWS 7, WINDOWS RT, and WINDOWS 8 all of which are manufactured by Microsoft Corporation of Redmond, Wash.; MAC OS and iOS, manufactured by Apple, Inc. of Cupertino, Calif.; and Linux, a freely-available operating system, e.g. Linux Mint distribution (“distro”) or Ubuntu, distributed by Canonical Ltd. of London, United Kingdom; or Unix or other Unix-like derivative operating systems; and Android, designed by Google, of Mountain View, Calif., among others. Some operating systems, including, e.g., the CHROME OS by Google, can be used on zero clients or thin clients, including, e.g., CHROMEBOOKS. 
     The computer system  100  can be any workstation, telephone, desktop computer, laptop or notebook computer, netbook, ULTRABOOK, tablet, server, handheld computer, mobile telephone, smartphone or other portable telecommunications device, media playing device, a gaming system, mobile computing device, or any other type and/or form of computing, telecommunications or media device that is capable of communication. The computer system  100  has sufficient processor power and memory capacity to perform the operations described herein. In some embodiments, the computing device  100  can have different processors, operating systems, and input devices consistent with the device. The Samsung GALAXY smartphones, e.g., operate under the control of Android operating system developed by Google, Inc. GALAXY smartphones receive input via a touch interface. 
     In some embodiments, the computing device  100  is a gaming system. For example, the computer system  100  can comprise a PLAYSTATION 3, or PERSONAL PLAYSTATION PORTABLE (PSP), or a PLAYSTATION VITA device manufactured by the Sony Corporation of Tokyo, Japan, a NINTENDO DS, NINTENDO 3DS, NINTENDO WII, or a NINTENDO WII U device manufactured by Nintendo Co., Ltd., of Kyoto, Japan, an XBOX 360 device manufactured by the Microsoft Corporation of Redmond, Wash. 
     In some embodiments, the computing device  100  is a digital audio player such as the Apple IPOD, IPOD Touch, and IPOD NANO lines of devices, manufactured by Apple Computer of Cupertino, Calif. Some digital audio players can have other functionality, including, e.g., a gaming system or any functionality made available by an application from a digital application distribution platform. For example, the IPOD Touch can access the Apple App Store. In some embodiments, the computing device  100  is a portable media player or digital audio player supporting file formats including, but not limited to, MP3, WAV, M4A/AAC, WMA Protected AAC, AIFF, Audible audiobook, Apple Lossless audio file formats and .mov, .m4v, and .mp4 MPEG-4 (H.264/MPEG-4 AVC) video file formats. 
     In some embodiments, the computing device  100  is a tablet e.g. the IPAD line of devices by Apple; GALAXY TAB family of devices by Samsung; or KINDLE FIRE, by Amazon.com, Inc. of Seattle, Wash. In other embodiments, the computing device  100  is an eBook reader, e.g. the KINDLE family of devices by Amazon.com, or NOOK family of devices by Barnes &amp; Noble, Inc. of New York City, N.Y. 
     In some embodiments, the communications device  102  includes a combination of devices, e.g. a smartphone combined with a digital audio player or portable media player. For example, one of these embodiments is a smartphone, e.g. the IPHONE family of smartphones manufactured by Apple, Inc.; a Samsung GALAXY family of smartphones manufactured by Samsung, Inc.; or a Motorola DROID family of smartphones. In yet another embodiment, the communications device  102  is a laptop or desktop computer equipped with a web browser and a microphone and speaker system, e.g. a telephony headset. In these embodiments, the communications devices  102  are web-enabled and can receive and initiate phone calls. In some embodiments, a laptop or desktop computer is also equipped with a webcam or other video capture device that enables video chat and video call. 
     In some embodiments, the status of one or more machines  102 ,  106  in the network  104  are monitored, generally as part of network management. In one of these embodiments, the status of a machine can include an identification of load information (e.g., the number of processes on the machine, CPU and memory utilization), of port information (e.g., the number of available communication ports and the port addresses), or of session status (e.g., the duration and type of processes, and whether a process is active or idle). In another of these embodiments, this information can be identified by a plurality of metrics, and the plurality of metrics can be applied at least in part towards decisions in load distribution, network traffic management, and network failure recovery as well as any aspects of operations of the present solution described herein. Aspects of the operating environments and components described above will become apparent in the context of the systems and methods disclosed herein. 
     B. Multi-Purse Transaction System 
     Systems and methods of the present solution are directed to conducting electronic transactions via a computer network. Systems and methods of the present solution can use a multi-purse transaction system that maintains an electronic account having multiple purses. An electronic account can be maintained by a server and be included in a database in memory or a storage device. The electronic account can include sub structures or fields. The electronic account can include multiple purses that are configured with one or more rules, parameters, restrictions, or policies. For example, the electronic account can include a first purse that is configured as a benefits purse. A purse configured for benefits can refer to a purse that is configured for transactions made using a tax benefit account such as a flexible spending account (“FSA”), Dependent Care Account (“DCA”), Transport Account (e.g., for parking or monthly passes). In some embodiments, the FSA, DCA, and Transport Account can be further separated into sub-purses within the benefits purse of the electronic account. A flexible spending account, or flexible spending arrangement, can refer to a tax-advantaged financial account that can be set up through a cafeteria plan of an employer and used to set aside a portion of earnings to pay for qualified expenses as established in the cafeteria plan. Types of FSA can include medical expense FSA, health FSA, health savings account (HSA), health reimbursement account (HRA), health reimbursement plan (HRP), etc. Qualified expenses can include, for example, medical expenses, dependent care, dental expenses, vision expenses, parking, monthly passes, etc. An FSA can be tax-advantaged because funds deducted from an employee&#39;s account and transferred to the FSA is not subject to payroll taxes, resulting in payroll tax savings. 
     A user can make the transaction at an entity such as a merchant, pharmacy, retail store, medical supply store, or other entity that provides goods or services that are deemed to be qualified expenses in accordance with the tax benefit account or FSA. The transaction can occur via a point-of-sale terminal or device (e.g., checkout device, electronic point of sale device or other device that includes hardware and software to facilitate a transaction) configured to receive financial transaction information from the user (e.g., via a debit card, pin number, mobile payment device, near field communication-enabled device, mobile telecommunications device) and communicate with one or more servers or databases to authenticate the financial transaction information, identify a corresponding FSA of the user, and initiate or facilitate the transfer of funds from the FSA to the entity. The transaction can include or be associated with information such as an FSA account identifier, time stamp, entity identifier, and transaction amount. This information can be provided in real-time to a transaction repository. 
     When participants submit claims for reimbursement from their FSA, HRA or other benefit account, the present solution provides a real time credit to their multi-purse debit card when the claim is approved for reimbursement. The present solution provides a notification via electronic mail or electronic messaging explaining that the reimbursed amount is now available for unrestricted spending at any merchant. The present solution uses one or more policy or logic engines to authorize transactions based on a merchant category code (“MCC”) to determine from which of the accounts on the electronic multi-purse card, commonly called purses, are eligible to pay for the transaction. 
     For example, if the participant has $100 in their FSA which is setup for Medical, Rx, Vision and Dental purchases, and the participant swipes their card at a vision provider for $75, the system makes a determination based on a policy to select an FSA from which to detect funds. If the card is swiped at a restaurant and the participant has a Reimbursement Purse on the card, the system can deduct funds from a reimbursement purse. If the participant has a transaction that exceeds the FSA for a qualified expense, the system can use the FSA funds plus an amount from the reimbursement purse. Participants can text a code such as “BAL” to the present solution to receive a current balance in one or more accounts/purses, including the reimbursement purse, or call to obtain balances for all accounts through an interactive voice response, as well as view the balance through a mobile application or online portal. 
     Referring now to  FIG.  2   , a block diagram depicting an embodiment of a system  200  comprising a multi-purse transaction system (MPTS) is shown. In brief overview, the system  200  includes a multi-purse transaction system  120  (“MPTS”) that can receive and/or transmit data via a network  104  with clients  102   a - n  and POS terminals  202   a - n . The system  200  can include or interact with one or more clients  102   a - n  (or client device  102 ), and one or more point-of-sale (POS) terminals  202   a - n  (or POS terminal  202 ). The MPTS  120  can include a communications interface  210  that is configured with one or more communications ports, application programming interfaces, network protocols (e.g., TCP/IP), authentication protocols, or security protocols (e.g., SSL). The MPTS  120  can include a policy engine  212  that selects a purse of an electronic account including multiple purses to use to conduct a transaction. The MPTS  120  can include a transaction engine  214  that obtains funds from one or more accounts or purses and transfers the funds to one or more accounts or purses or merchants. The MPTS  120  can include one or more databases or data structure that store information to facilitate the systems and methods of the present solution, such as database  216  and database  218 . The database  216  (or electronic account) can include an electronic account maintained or configured on the MPTS  120  that includes one or more purses, such as a benefits purse and a cash purse. The database  218  can include one or more policies in a policy repository, user profiles, or merchant information. 
     The system  120 , communications interface  210 , policy engine  212 , and transaction engine  214  can each include one or more processing units or other logic devices such as programmable logic array engines, modules, or circuitry designed and constructed to facilitate managing security on a network infrastructure. The MPTS  120  can include the components  100  shown in  FIG.  1 C  or  FIG.  1 D , or be configured to operate as a service in cloud  108 . The MPTS can include or interact with one or more servers  106   a - n  and clients  102   a - n.    
     In some embodiments, the MPTS  120  can employ a multitier architecture such as a client-server architecture in which presentation, application processing, and data management functions are logically or physically separated. The presentation tier, or front-end, can include the communications interface  210  that serves static content or dynamic content to be rendered by the client  102  (e.g., by a web browser executing on client  102 ). The presentation tier or web server  210  can interact or communicate with the application tier to obtain data to provide to the client  102  or POS terminals  202   a - n . The application tier can include the policy engine  212  and transaction engine  214  that controls the system&#39;s functionality and performs additional processing or analysis on data. The application tier can interact with the data tier to obtain the transaction data. The data tier can include data persistence mechanisms (database servers, file shares, etc.) and the data access layer that encapsulates the persistence mechanisms and exposes the data. The data tier can include databases  216  and  218 . The data tier can include an application programming interface (API) to the application tier. The databases  216  or  218  can include stored procedures (e.g., SQL statements) that perform tasks with respect the stored data. 
     In further detail, and in some embodiments, the MPTS  120  includes a communications interface  210 . The communications interface  210  can execute on one or more processors of a server. The communications interface  210  can include one or more communications ports and be configured with one or more network protocols. Communications ports can include, e.g., network ports, Ethernet ports, WAN ports, I/O ports, or software ports. The communication port can be configured with a network protocol such as Transport Layer Protocols such as TCP/IP or UDP that are configured to receive and process data packets received via a computer network. The port can include or be associated with an IP address of a host and a protocol type of the communication. 
     In some embodiments, the communications interface  210  can receive data packets. The data packets can be generated by a first device at a first merchant to conduct a first electronic transaction at the first merchant. The first device can refer to a POS terminal such as POS terminal  202   a . A point of sale terminal  202  (“POS”) is the place where a retail transaction is completed. The POS terminal  202  is the point at which a customer of the entity or merchant makes a payment to the merchant in exchange for goods or services. At the point of sale the merchant can calculate the amount owed by the customer and provide options for the customer to make payment. The merchant can also issue a receipt for the transaction. 
     The POS terminal  202  can include hardware and software. Merchants can utilize weighing scales, scanners, electronic and manual cash registers, EFTPOS terminals, touch screens and any other wide variety of hardware and software available for use with POS terminal  202 . For example, a pharmacy can use software to customize the item or service sold when a customer has a special medication request. 
     The POS terminal  202  can include advanced features to cater to different functionality, such as inventory management, CRM, financials, warehousing, flexible spending account transactions, etc., all built into the POS software. The point of sale terminal  202  can be configured to conduct a transactions using a debit card, multipurse card, Bluetooth, near field communications, smartphone, smartwatch, mobile telecommunications computing device, wearable communications, RFID, etc. 
     The communications interface  210  can receive data packets generated by the POS Terminal  202   a  responsive to conducting an electronic transaction. The data packets can include header information and payload information. Multiple data packets can be strung together in a sequence. The header information can refer to TCP/IP headers that include fields such as source port, destination port, sequence number, acknowledgment number, window size, etc. The payload information of the data packet can include information related to the transaction, merchant, or customer. The system  120  can receive the data packet with header information and payload information and process the packets to obtain information for further processing. The payload can include data identifying a first merchant category of the first merchant, an electronic account, and a monetary amount of the electronic transaction. 
     The data packets can carry data identifying a merchant or merchant category of the merchant. In some embodiments, the data carried by the data packets include a merchant category code or identifier (e.g., dental, medical, etc.). In some embodiments, the data identified a merchant, and the system  120  determined a merchant category based on the identification of the merchant by, for example, using a merchant to merchant category mapping or lookup table stored in database  218 . 
     The data packets (e.g., payload of the data packets) can further identify an electronic account maintained and configured on the server. The electronic account can be maintained and configured in a database  216 . The electronic account can correspond to a user and have a unique identifier. The unique identifier can include numbers, letters, characters, symbols, etc. The electronic account can be associated with the customer making the transaction at the merchant. The POS terminal  202   a  can receive or determine the electronic account identifier via a card swipe or other communication technique employed at the POS terminal  202   a , which the POS  202   a  can then convey to the system  120 . 
     The communications interface  210  can further receive data packets (e.g., payload information) identifying a first monetary amount of the first electronic transaction. The monetary amount can be for the purchase of goods or services made at the merchant. The monetary amount of the transaction can refer to the amount of funds in consideration for goods or services obtained from the entity or merchant. The merchant or entity can refer to the entity at which a point-of-sale terminal or device used to make the transaction is located or with which the terminal is associated. The monetary amount can be in any currency (e.g., United States dollars) or units. The monetary amount can be further tied to a category, such as medical services. 
     In some embodiments, the POS terminal  202  can generate multiple data packets for a single transaction. The multiple data packets can each include a header and a payload. The header can indicate that the multiple data packets are to be grouped together for routing, transmission or processing purposes. 
     In some embodiments, the system  120  includes a policy engine  212 . The policy engine  212  can execute on one or more processors of a server. The policy engine  212  can receive, retrieve, or otherwise obtain or access some or all of the data carried by the data packets. The policy engine  212  can receive, retrieve, or otherwise obtain or access policies, such as policies stored in database  218 . The policy engine  212  can apply the policy to the data to select a purse of the electronic account. 
     The policy engine  212  can use or apply a policy that includes one or more techniques, algorithms, heuristics, or procedures. The policy can include decision points and utilize parameters or criteria. The policy can be based on criteria or rules that are established by an administrator of the MPTS  120  or another entity. The policy can facilitate determining which purse of the multipurse electronic account to use to transfer funds. 
     In some embodiments, the policy can be based on a merchant category. The policy can be based on a merchant category code (“MCC”). The MCC can refer to a code (e.g., a four-digit number) that can be assigned to a business by an entity, such as a credit card company or the MPTS. This code can be used to classify the merchant by a business type, or type of goods or services provided. 
     For example, the policy can be: if merchant category corresponds to (or equals or maps to or is) medical, then use benefits purse. In another example, the policy can be: if merchant category corresponds to dental, then use benefits purse. In another example, the policy can be: if merchant category maps to qualified benefits category, then use benefits purse. In some embodiments, the electronic account can include a benefits purse that is preconfigured with merchant categories that map to qualified or approved categories, such as categories for funds exempt from payroll tax can be used to conduct a transaction. 
     In some embodiments, the policy can include multiple criteria. For example, the policy can include: if merchant category corresponds to (or equals or maps to or is) medical or dental or vision or parking, then use benefits purse. In some embodiments, the policy can be a negative policy. For example, the policy can include: if merchant category does not equal medical or dental or vision, then use cash purse. In some embodiments, the policy can include an action to take when the policy is not satisfied. For example, if merchant category corresponds to medical or dental or vision or parking, then use benefits purse; otherwise, use cash purse. In some embodiments, a single policy can include multiple policies. In some embodiments, the system  120  can use process multiple policies before identifying a policy that is satisfied. 
     In some embodiments, the policy engine  212  can select a sub-purse using the policy. The sub-purse can refer to a purse within a benefits purse. For example, the benefits purse can include multiple purses, such as an FSA purse, HRA purse, HAS purse, DCA purse, or Transport Purse. Thus, the policy engine  212  can use a policy that can select the benefits purse and a benefits sub-purse based on a merchant identifier or merchant category. For example, the policy can be: if merchant category corresponds to parking, then select Purse{Benefits].SubPurse{Transport}. 
     In some embodiments, the policy engine  212  can use a policy that includes monetary amount thresholds. For example, a merchant category can correspond to an approved benefits purse. However, the approved benefits purse can include a threshold that limits a monetary amount of a transaction. For example, the benefits purse can be configured with a parking sub-purse with a monetary amount threshold. The monetary amount threshold can be for a time period, such as a month, quarter, year, week, or other time interval. For example, the transport or parking sub-purse can be approved for $200 per month for transactions made at merchants that correspond to merchant category transport or parking. Thus, the policy can include criteria such as merchant category, transaction amount, and time interval. For example: if merchant category corresponds to transport and if transaction amount less than or equal to approved transaction amount for time interval, then use transport sub-purse. 
     In some embodiments, the policy engine  212  can obtain funds for a single transaction at a merchant from multiple purses of the electronic account. For example, a benefits purse can be configured with a monetary amount limit or threshold for a merchant category. The policy engine can then determine, using the policy, to select the cash purse for the remaining monetary amount. For example, for a transaction of a first transaction amount made at a medical provider, the policy can include: if merchant category corresponds to medical, then select benefits purse for funds up to medical amount threshold; if transaction amount is greater than medical amount threshold, then select cash purse for remaining amount, where remaining amount is transaction amount minus medical amount threshold. 
     In some cases, where the amount thresholds are based on a time interval, the system  120  can determine the amount using historical transaction information stored in a database  216  or  218 . For example, the electronic account  216  can include transaction information with time stamps for one or more purses. Similarly, profiles stored in database  218  can include a user&#39;s profile which can include transaction information. 
     Thus, and in some embodiments, the first policy can refer to one or more policies that are used to determine or select one or more purses from which funds are to be obtained or withdrawn to complete a transaction conducted at a merchant. 
     In some embodiments, the policy engine  212  can apply a second policy directed to additional factors after using a first policy. The policy engine  212  can select the second policy responsive to or based on the first policy. The second policy can be associated with a monetary amount, transaction amount, or reimbursement amount. The policy engine  212  can use the second policy to determine a reimbursement amount. The policy engine  212  can use a reimbursement policy. The reimbursement policy can be applied to the data that identifies the transaction amount, merchant category, and electronic account. The reimbursement policy can be selected based on an insurance policy tied to or associated with the electronic account. The electronic account can include a unique identifier that maps to or corresponds to a type of insurance policy or reimbursement policy. The reimbursement or insurance policy (e.g., second policy) can be established by an administrator of the system  120 , an employer of the user/customer conducting the transaction, or another entity. Using this reimbursement policy, the policy engine  212  can determine a reimbursement amount. For example, if the transaction amount for the medical service was $100, the policy engine  212  can determine that 80% of the transaction is covered by insurance. The system  120  can initially deduct $100 from the benefits purse of the electronic account in accordance with the first policy. Thereafter, applying the second policy, the system  120  can determine to credit or reimburse the electronic account $80. 
     Responsive to determining the reimbursement amount, the policy engine  212  can further select a second purse of the electronic account for the reimbursement. The second purse can be different from the first purse. For example, the second purse can be a cash purse without the same restrictions as the benefits purse. The cash purse or reimbursement purse can be configured for use for any type of transaction, including, e.g., food or entertainment. 
     In some embodiments, the second policy refers to a policy the policy engine  212  can use to select a purse for the reimbursement amount that is different from the first purse selected using the first policy. For example, the first purse selected using the first policy can be a benefits purse that can have restrictions. The restrictions on the benefits purse can refer to restrictions on what types of goods or services funds in the benefits can be used. However, the electronic account can include an additional purse that may not be configured with such restrictions. The additional purse can be referred to as a reimbursement purse or cash purse. The cash purse can be stored on the electronic account in database  216 . 
     The second policy used by the policy engine  212  and obtained from database  218  to determine a reimbursement amount can include rules, parameters, criteria or thresholds. For example, the reimbursement policy can include: if merchant category corresponds to medical, then reimburse 80% of transaction amount. In another example, the policy can include: if merchant category corresponds to medical, then reimburse 80% of transaction amount, but do not reimburse more than reimbursement limit. The reimbursement limit can be on a per transaction basis, or a time interval basis. For example, the reimbursement limit can refer to the maximum reimbursement amount for a time interval, such as a month, quarter, year or other time interval. The reimbursement limit can be a global limit across all benefits purses, or can be specific for each benefits subpurse (e.g., a first limit for HRA, a second limit for DCA, a third limit for FSA, etc.). 
     In some embodiments, the policy engine  212  can receive an indication from a claims processor  220  external to the system  120  via network  104 . In some embodiments, the system  120  or policy engine  212  is configured with the claims processor  220  or configured to interface with the claims processor  220  via communications interface  210 . The claims processor  220  can process an insurance claim to determine a reimbursement amount. The claims processor  220  can be configured to use one or more policies or rules to process the insurance claim and determine a reimbursement amount. The policies can be based on a type of insurance coverage associated with a user of the electronic account. The claims processor  220  can automatically receive the insurance claim responsive to a user conducting a transaction using the multipurse card connected with the electronic account. The claims processor  220  can obtain, via database  216  or  218 , policies, profiles and merchant information to adjudicate the claim. The claims processor  220  can adjudicate the claim, determine a reimbursement amount, and provide an indication to the system  120  regarding the reimbursement amount. The indication can identify the electronic account, user identifier, time, original transaction amount, reimbursement policy, or reimbursement amount. 
     The system  120 , upon receiving the indication of the reimbursement amount from the claims processor  220 , can select a second policy to determine to which purse of the multipurse electronic account to transfer the reimbursement amount. The policy engine  212  can retrieve the second policy from the database  218 . The second policy include, for example, the following: if transaction corresponds to reimbursement, then select cash purse of the electronic account. The cash purse may not have the same restrictions as the benefits purse. 
     The system  120  can include a transaction engine  214 . The transaction engine  214  can receive information or instructions from the policy engine  212  regarding a transaction, and conduct the transaction. The transaction engine  214  can obtain merchant information from database  218  and electronic account information from  216  to perform the transaction. The transaction can include electronically transferring funds from a first account to a second account. The first account can be an electronic account, and the second account can be an account of a merchant (such as a financial account). In some cases, the transaction engine  214  can facilitate a transfer of funds between an electronic account of a claims processor  220  and the electronic account  216 . The transaction engine  214  can receive account identifiers, transaction amounts, credentials, authentication information, etc. The transaction engine  214  can conduct the transaction via communications interface  210 , thereby using the network protocols, security protocols and other components or interfaces provided by the communications interface  210 . 
     In some embodiments, upon completing the transaction via the transaction engine  214 , the system  120  can provide, via the communications interface  210 , a real-time notification of the reimbursement amount to account holder of the electronic account including the cash purse that received the reimbursement amount. The communications interface  210  can be configured to provide the notification via an electronic mail protocol, Simple Messaging Service protocol, notification or prompt on a mobile telecommunications devices (e.g., a smartphone, tablet, smartwatch, wearable telecommunications device, laptop computer, desktop computer, etc.). The notification can be in real-time, which can refer to providing the notification soon after completion of the transaction (e.g., within 1 minute, within 5 minutes, within 30 seconds). In some embodiments, the notifications can include status information regarding the reimbursement transaction (e.g., processing reimbursement, reimbursement approved, reimbursement denied, reimbursement submitted for transfer, transferring reimbursement, or reimbursement complete). 
     In some embodiments, the system  120  (e.g., via communication interface  210 ), receives a request for account information from a client device  102  associated with an electronic account maintained or configured on the system  120 . The request for information can include information about a balance of the electronic account, available purses, balance of an individual purse, status of a reimbursement, policies associated with purses, or transaction history. The request can further include authentication information or credentials associated with the request. The authentication information can include network security credentials, such as security certificates or tokens. The authentication information can further include a username, password, two-tier authentication information (e.g., date of birth, cell phone number, verification code sent via text message to cell phone number in profile associated with electronic account). The request can be from a client device such as a smartphone. The request can be sent using a text messaging protocol such as SMS. The system  120  can authenticate a request sent via SMS based on the cell phone number of the device sending the SMS request, and matching the cell phone number with corresponding number stored in profile in database  218  for the electronic account. 
     Responsive to authenticating or otherwise approving the request, the system  120  can access a data record in database  216  for the electronic account to generate a report with the requested information, or generate a standard report, or generate another preconfigured report. The report can identify the account holder information, available purses, benefits purses, reimbursement purse, subpurses, and available amounts for each purse. The report can further identify a transaction history for the electronic account or each subpurse thereof. The report can further identify or indicate if one or more purses have reached a maximum limit. The report can further include a forecast based on current/previous transaction history that indicates whether the user can likely deplete available resources or exceed maximum limits based on current spending for a time interval. 
     Referring now to  FIG.  3   , a flow diagram depicting an embodiment of a method of conducting an electronic transaction is shown. The method can be performed by system  200 , MPTS  120 , or one or more component thereof. In brief overview, at step  305 , a server of a multipurse transaction system receives data packets to conduct a first electronic transaction. At step  310 , the server selects a first purse allocated to an electronic account maintained by the server. At step  315 , the server obtains a first monetary amount of the first electronic transaction from the first purse. At step  320 , the server applies a second policy to the data to determine a reimbursement amount. At step  325 , the server electronically provides the reimbursement amount to a second purse of the electronic account. 
     Still referring to  FIG.  3   , and in further detail, a server of a multipurse transaction system receives data packets to conduct a first electronic transaction at step  305 . The data packets can be received via a computer network using a networking protocol. The data packets can be generated by a device at a merchant, such as a Point-of-Sale Terminal. The data packets can include header information and payload information. The header information can include, e.g., TCP header information that can facilitate the routing and transmission of the data packet. The payload information can include data related to, describing, defining, associated with or otherwise about the transaction occurring between the POS terminal, merchant, or customer. 
     The server can parse, process, or otherwise identify, from the header information or payload information from the one or more data packets, information about the transaction. The system can identify the first merchant (e.g., a name of a merchant, location of the merchant, unique identifier of the first merchant) or merchant category of the first merchant. In the event the data packets do not include a merchant category, the server can determine a merchant category based on a merchant identifier. In some embodiments, where the server fails to determine a merchant category, the server can default to using a cash purse that is approved for any time of transaction (e.g., where the merchant category in the data packets does not correspond to a policy in the policy repository). The data packets can also carry data (e.g., via payload information) identifying an electronic account maintained and configured on the server, and a monetary amount of the electronic transaction. The server can receive data packets for multiple transactions, where each transaction is associated with a merchant or merchant category and transaction amount. The data packets can further include (e.g., within the payload information) an electronic account associated with a multipurse card swiped at a POS of a merchant conducting the transaction. The multipurse card can be a plastic card (e.g., debit card or debit card with a magnetic strip or RFID), or be an electronic card stored on a telecommunications device which transmits an electronic account identifier corresponding to the electronic card via a wireless technology (e.g., Bluetooth, or NFC). The POS can generate or obtain information that allows the MPTS to conduct the transaction, encapsulate or process the information using a protocol to generate data packets, and transmit the data packets in a secure manner over a network to the MPTS for further processing. 
     At step  310 , the server selects a first purse allocated to an electronic account maintained by the server. The electronic account can include several purses that are of different types or configured for different types of transactions, and the server can select the first purse using a policy. The server can retrieve the policy from a policy repository. The policy can include one or more rules, policies, parameters, criteria, comparisons, or thresholds. This first policy can refer to a policy used to select a purse for withdrawing funds to facilitate completing a transaction conducted a merchant. The policy can be used to select a purse having funds that can be allocated towards a purchase made at the merchant. 
     In some embodiments, the first policy can take into consideration factors such as merchant category and transaction amount. The first policy can select a purse based on the merchant category. The selected purse can be preconfigured or approved for purchases made at a merchant corresponding to a merchant category (e.g., prescription purchase made at a pharmacy can be approved to use funds from a benefits purse, such as a prescription purse). This purse can be configured as a purse with funds exempt from payroll tax deductions to be used to conduct approved transactions. For example, the server can determine that the first purse of the electronic purse is configured for prescription purchases, and select the first purse responsive to determining that the merchant is a prescription provider based on the first merchant category. 
     At step  315 , the server obtains a first monetary amount of the first electronic transaction from the first purse of the electronic account. In some embodiments, the server can interface with a financial institution to conduct the transfer of funds. For example, the server can include an interface configured for conducting financial transactions over a network. 
     In some embodiments, the server can use the policy to determine the amount to obtain. For example, the amount to obtain from the first can be different from the transaction amount. The amount to obtain from the first can be less than the transaction amount. The amount to obtain from the first purse can be based on the policy. The policy can indicate that only a certain amount of the total transaction amount is approved to be deducted from the first purse. For example, the policy for a benefits purse such as a transport purse can limit the amount of funds that can be deducted during a time interval (e.g., $200 per month). Accordingly, the server can determine, by applying the first policy, to deduct a portion of the transaction amount from the first purse, and deduct a remaining portion from a different purse of the electronic account, such as a cash purse that may not include the same restriction. In some embodiments, the server can determine that there are not sufficient available funds in the first purse to complete the transaction (e.g., the transaction amount is greater than the available funds in the first purse that is configured as the benefits purse or an approved subpurse thereof). The server can then determine to deduct a remaining amount or the entire transaction amount from a cash purse or be configured with a credit card purse that can allow for a credit card transaction. 
     At step  320 , the server applies a second policy to the data to determine a reimbursement amount. The second policy can refer to a policy that determines an amount of the transaction amount that is to be reimbursed to the electronic account. This second policy can be based on an insurance policy, claim policy, plan information, or benefits information. This second policy can include adjudication an insurance claim. In some embodiments, the MPTS can perform one or more component of the adjudication process or otherwise facilitate the adjudication process. In some embodiments, this claim processing can be done by the MPTS. In some embodiments, the claims processing can be performed in real-time (e.g., within 1 minute, 30 seconds, 5 minutes, 30 minutes of the claim being submitted). In some embodiments, the claims processing can be done by a third-party entity external to the MPTS. In some embodiments, the MPTS can receive an indication of the reimbursement amount, an account identifier with for the source of the funds to be reimbursement (e.g., a financial account of an insurance provider), and an account identifier or electronic account identifier or other user identifier corresponding to a destination for the funds to be reimbursed. 
     The second policy can include one or more policies that facilitate determining a reimbursement amount or a purse to which the reimbursement amount to be allocated. For example, the reimbursement policy can include: if prescription purchase at qualified merchant category, then reimbursement amount is 70% of the prescription amount. In some embodiments, the reimbursement amount can be an absolute value (e.g., $10, $50). In some embodiments, the reimbursement amount can include a function or formulate that takes into account the type of prescription or merchant category, a reimbursement rate, a type of insurance coverage, a geographic location, a cost of living factor, etc. 
     In some embodiments, the second policy can include a policy or factor that determines to which account to reimburse the funds. The second policy can select an account with fewer restrictions as compared to a benefits account. The second account can be configured with, in, on, or be part of the electronic account that includes a plurality of accounts maintained or configured on the server. The second account can be a cash purse or reimbursement purse of the electronic account. The second account can have no restrictions on where, when or for what the funds available in the second account can be used. In some embodiments, funds from the second account can be withdrawn as cash. In some embodiments, funds from the second account may not be withdrawn as cash, but can be used at any merchant that can conduct a transaction with the second account. 
     At step  325 , the server electronically provides the reimbursement amount to a second purse of the electronic account. This second purse (or reimbursement purse or cash purse or restriction-free purse) can be different from the first purse, but maintained on or correspond to the same electronic account having the first purse or benefits purse. In some embodiments, the server provides a real-time notification of the reimbursement amount responsive to transferring the reimbursement amount to the first purse of the electronic account. The real-time notification can refer to providing the notification within a time interval of transferring the reimbursement amount to the second purse, or when the reimbursement amount is available for use or withdrawal via the second account. The time interval can refer to as soon as possible, 15 seconds, 30 seconds, 5 minutes, or some other time interval that notifies a user of available funds resulting from a reimbursement made to a purse of the electronic account soon after the funds are available. 
     In some embodiments, the server can receive one more data packets generated by a second device at a second merchant to conduct a second electronic transaction at the second merchant. The second device can refer to a different point of sale terminal, and the second merchant can be a merchant with a merchant category that does not correspond to a merchant category that is approved to receive funds for purchases from a benefits account. The second one or more data packets can include second header information and second payload information. The second payload information can include data associated with, defining, about or identifying aspects of the second transaction. The server can process the second one or more data packets to identify data from the payload information indicative of the second transaction. This payload information can include information such as a merchant identifier, merchant code, transaction amount, location, or electronic account information. In some embodiments, merchant category corresponds to an item being purchased in the transaction (e.g., soda purchased at a pharmacy). Thus, the merchant category of the transaction may not be approved to receive funds from a benefits account, although the merchant can provide other items that can be approved by the benefits account policy (e.g., prescription medications at a pharmacy vs. cigarettes sold at a pharmacy). 
     Along with these second data packets, the server can receive an identification of the electronic account, and a monetary amount of the second electronic transaction. The server can retrieve a second policy from a policy repository stored in memory using an identifier of the electronic account. The server can use the policy engine to apply the first policy to determine which purse of the electronic account to select for withdrawing funds to pay for the transaction. In some embodiments, the server determines, using a mapping of merchant category to purse configuration or purse policy, that the merchant category is not approved to receive funds from a benefits purse (e.g., the category may not correspond to any of the benefits subpurses, including medical, vision, dental, transport), and, instead, selects the cash purse for the transaction. The server can then instruct a transaction engine to obtain funds for this transaction from a cash purse that may not have restrictions based on merchant category or can be otherwise approved for providing funds for the transaction with the second merchant. For example, the server can select the second purse responsive to determining that the first purse is not configured for the second merchant category of the second merchant. 
     In some embodiments, merchant category can refer to a merchant category code (“MCC”). Table 1 is an example mapping of merchant categories to purses in accordance with an embodiment: 
     
       
         
           
               
             
               
                 TABLE 1 
               
             
            
               
                   
               
               
                 Example mapping of merchant categories to  
               
               
                 purses in accordance with an embodiment. 
               
            
           
           
               
               
               
               
            
               
                   
                 MCC 
                 Merchant Category 
                 Purse 
               
               
                   
                   
               
               
                   
                 8099 
                 Medical Services 
                 Benefits Purse 
               
               
                   
                 8062 
                 Hospitals 
                 Benefits Purse 
               
               
                   
                 8042 
                 Optometrists 
                 Benefits Purse 
               
               
                   
                 7832 
                 Motion Picture Theaters 
                 Cash Purse 
               
               
                   
                 7922 
                 Theatrical Ticket Agencies 
                 Cash Purse 
               
               
                   
                   
               
            
           
         
       
     
     For example, the server can analyze the amount of available funds in one or more purses of the electronic account in order to select one or more purses to conduct a transaction. For example, multiple purses can be approved or qualify for a transaction based on a merchant code (e.g., both a benefits purse and a cash purse). In some embodiments, a first purse can have a higher priority than a second purse, which can cause the server to select the first purse for funds prior to selecting the second purse. 
     If multiple accounts are approved based on a merchant category, the server can determine an available amount in each purse. For example, the server can access a data record in memory for the electronic account. The data record can indicate a first available amount and a first configuration for the first purse (e.g., as a benefits purse with $100), and a second available amount and a second configuration for the second purse (e.g., a cash purse with $500). The server can determine, based on the first available amount and the first configuration, to use the first purse for the first electronic transaction. For example, the first electronic transaction can be $100 for prescriptions medications. Further, the server can determine based on the first available amount and the first configuration, not to use the second purse for the first electronic transaction. For example, the first purse can have a higher priority because it has greater restrictions than the second purse, and the transaction parameters satisfies the policy and restrictions of the first purse. 
     Thereafter, the server can receive an indication of a second transaction. The server can receive a second one or more data packets with second header information and second payload information. The second payload information can include data about the second transaction. The server can parse or otherwise process the second one or more data packets to identify the second payload information and data about the second transaction. Using information about the second transaction, such as a merchant identifier, merchant code, or amount of the second transaction, the server can determine, based on the first configuration of the first purse, not to use the first purse for the second electronic transaction. For example, the second transaction can be for $30 for movie tickets which may not be approved for a benefits purse based on a MCC. Further, the server can determine, based on the second available amount and the second configuration, to use the second purse for the second electronic transaction. For example, the second purse can be a cash purse that is approved for any type of MCC, and the cash purse has sufficient funds for the transaction. 
     C. Multi-Purse Transaction and Notification System 
     The systems and methods of the present solution are directed to the technical problems and challenges of implementing the functionality of conducting a multi-purse transaction of an electronic transaction based technology and platform. Existing electronic transaction based technologies and platforms do not effectively and efficiently make use of the computing and network resources deployed for multi-purse transaction based technologies and platforms to include such functionality. Without implementing such functionality, existing electronic transaction based technologies and platforms have the problems of excessive server-client requests and responses, processing delays, increase bandwidth usage, or erroneous transactions. 
     The systems and methods of the present solution are directed to the improvement of the performance and operation of the electronic transaction based technology and platform and computing and networking resource used by such electronic transaction based technology and platform. In some aspects, the present solution improves and enhances the implemented functionality of the electronic transaction based technology and platform implemented on, integrated with and inherently tied to the processor, memory, network and computing resources of one or more computing devices. In some aspects, the present solution more effectively performs the functionality of the electronic transaction based technology and platform thereby making and causing more effective use of the computing and networking resources to achieve the improved functionality of the present solution. The same computing and network resources used by such electronic transaction based technology and platform will provide increased and improved functionality with implementation of the present solution. 
     In some aspects, the present solution more efficiently uses the computing and networking resources to implement the improved functionality of the electronic transaction based technology and platform. For example, systems and methods of the present solution can use a multi-purse transaction system that maintains an electronic account having multiple purses, such as an electronic benefits account and an electronic reimbursement account. Systems and methods of the present solution can adjudicate a single claim against the electronic benefits account (e.g., determine that the single claim is approved for reimbursing an electronic account by an amount of expenditures associated with the electronic transaction) and provide notifications relating to such claims. An electronic account can be maintained by a server and include a database in memory or a storage device. The electronic account can include sub structures or fields. The electronic account can include multiple purses that are configured with one or more rules, parameters, restrictions, or policies. For example, the electronic account can include a first purse that is configured for benefits as an electronic benefits account purse. A purse configured for benefits can refer to a purse that is configured for transactions made using a tax benefit account such as a flexible spending account (“FSA”), Dependent Care Account (“DCA”), Transport Account (e.g., for parking or monthly passes). In some embodiments, the FSA, DCA, and Transport Account can be further separated into sub-purses within the electronic benefits account purse of the electronic account. A flexible spending account, or flexible spending arrangement, can refer to a tax-advantaged financial account that can be set up through a cafeteria plan of an employer and used to set aside a portion of earnings to pay for qualified expenses as established in the cafeteria plan. Types of FSA can include medical expense FSA, health FSA, health savings account (HSA), health reimbursement account (HRA), health reimbursement plan (HRP), etc. Qualified expenses can include, for example, medical expenses, dependent care, dental expenses, vision expenses, parking, monthly passes, etc. An FSA can be tax-advantaged because funds deducted from an employee&#39;s account and transferred to the FSA is not subject to payroll taxes, resulting in payroll tax savings. 
     A user can make the transaction at an entity such as a merchant, pharmacy, retail store, medical supply store, or other entity that provides goods or services that are deemed to be qualified expenses in accordance with the tax benefit account or FSA. The transaction can occur via a point-of-sale terminal or device (e.g., checkout device, electronic point of sale device or other device that includes hardware and software to facilitate a transaction) configured to receive financial transaction information from the user (e.g., via a debit card, pin number, mobile payment device, near field communication-enabled device, mobile telecommunications device) and communicate with one or more servers or databases to authenticate the financial transaction information, identify a corresponding FSA of the user, and initiate or facilitate the transfer of funds from the FSA to the entity. The transaction can be associated with information such as an FSA account identifier, time stamp, entity identifier, and transaction amount. This information can be provided in real-time to a transaction repository. 
     When participants submit claims for reimbursement from their FSA, HRA or other benefit account, the present solution provides a real time credit to their electronic reimbursement account when the claim is approved for reimbursement. The present solution provides real time adjudication of the single claim. By adjudicating the single claim, the present solution improves over batch processed claims that cannot be processed until several hours, days, weeks, or months after the electronic transaction occurs. The present solution provides a real time notification via electronic mail or electronic messaging of the real time credit to the electronic reimbursement account, and can explain in real time that the reimbursed amount is now available for unrestricted spending at any merchant. The present solution uses one or more policy or logic engines to authorize transactions, such as by authorizing transactions based on a merchant category code (“MCC”), a goods and services code, a health care provider code, or other policy codes, to determine that the single claim against the electronic benefits account is approved for an amount of expenditures qualifying under the electronic benefits account. 
     For example, if the participant has $100 in their FSA which is setup for Medical, Rx, Vision and Dental purchases, and the participant swipes their card at a vision provider for $75, the system makes a determination based on a policy to select an FSA from which to deduct funds. If the card is swiped at a restaurant and the participant has an electronic reimbursement account on the card, the system can deduct funds from a reimbursement purse. If the participant has a transaction that exceeds the FSA for a qualified expense, the system can use the FSA funds plus an amount from the reimbursement purse. Participants can text a code such as “BAL” to the present solution to receive a current balance in one or more electronic accounts/purses, including the electronic reimbursement account, or call to obtain balances for all accounts through an interactive voice response, as well as view the balance through a mobile application or online portal. Participants can text a code such as “CLAIM” to the present solution to receive a status of the adjudication of the single claim. 
     Referring now to  FIG.  4   , a block diagram depicting an embodiment of a system  400  comprising a multi-purse transaction system (MPTS) is shown. In brief overview, the system  400  includes a multi-purse transaction system  408  (“MPTS”). The MPTS  408  can include the MPTS  120  depicted in  FIG.  2   , or one or more components or modules depicted in  FIG.  2   , and can perform the functions of the MPTS  120 . The MPTS  408  can receive and/or transmit data via a network  104  with clients  102   a - n  and POS terminals  202   a - n . The system  400  can include or interact with one or more clients  102   a - n  (or client device  102 ), and one or more point-of-sale (POS) terminals  202   a - n  (or POS terminal  202 ). 
     The MPTS  408  can include a communications interface  410 . The communications interface  410  can include the communications interface  210  depicted in  FIG.  2   , or one or more components or modules depicted in  FIG.  2   , and can perform the functions of the communications interface  210 . The communications interface  410  is configured with one or more communications ports, application programming interfaces, network protocols (e.g., TCP/IP), authentication protocols, or security protocols (e.g., SSL). The communications interface  410  can receive a request to adjudicate a single claim against an electronic benefits account. 
     The MPTS  408  can include a policy engine  412 . The policy engine  412  can include the policy engine  212  depicted in  FIG.  2   , or one or components or modules depicted in  FIG.  2   , and can perform the functions of the policy engine  212 . The policy engine  412  determines, responsive to the communications interface  410  receiving the request to adjudicate the single claim, that the single claim against the electronic benefits account is approved for an amount of expenditures qualifying under the electronic benefits account. 
     In some aspects, the policy engine  412  comprises an innovative, non-conventional or non-routine implementation. In some aspects, the policy engine  412  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, the policy engine  412  is implemented to make or cause more effective and efficient use of computing and networking resources. For example, the policy engine  412  can cause more effective and efficient use of computing and network resources by reducing the number of processing cycles, memory or network bandwidth used to adjudicate the single claim against the electronic benefits account. The policy engine  412  can provide an improved or faster result by integrating or interfacing with one or more of the communication interface  410 , electronic account  418 , database  420 , transaction engine  414 , notification engine  416  or claims processor  220  to perform the adjudication of the single claim. 
     The MPTS  408  can include a transaction engine  414 . The transaction engine  414  can include the transaction engine  214  depicted in  FIG.  2   , or one or more components or modules depicted in  FIG.  2   , and can perform the functions of the transaction engine  214 . The transaction engine  414  obtains electronic data representing funds from one or more electronic accounts or purses and transfers the funds to one or more accounts or purses or merchants. 
     In some aspects, the transaction engine  414  comprises an innovative, non-conventional or non-routine implementation. In some aspects, the transaction engine  414  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, the transaction engine  414  is implemented to make or cause more effective and efficient use of computing and networking resources. For example, the transaction engine  414  can cause more effective and efficient use of computing and network resources by reducing the number of processing cycles, memory or network bandwidth used to obtain electronic data regarding funds from one or more electronic accounts or purses to conduct a transfer. The transaction engine  414  can provide an improved system by integrating or interfacing with the communication interface  410 , electronic account  418 , database  420 , policy engine  412 , notification engine  416  or claims processor  220  to perform the transfer. 
     The MPTS  408  can include one or more databases or data structures that store information to facilitate the systems and methods of the present solution, such as database  418  and database  420 . The database  418  can include the database  216 , or one or more components or modules depicted in  FIG.  2   , and can perform the functions of the database  216 . The database  418  (or electronic account) can include an electronic account maintained on or configured on the MPTS  408  that includes one or more purses, such as a benefits purse and a cash purse. The database  418  can include a profile database of the electronic benefits account. The profile database can include an entry corresponding to a device configured to receive notifications for the electronic benefits account. The entry can include a unique identifier for the device and a notification mode including at least one of a Short Messaging Service (SMS) protocol or an electronic mail protocol. The database  420  can include one or more policies in a policy repository, user profiles, or merchant information. The user profiles can include biographical information associated with users, identifiers for clients  102  or other devices associated with users, security credentials associated with users, transaction histories, etc. In some embodiments, the user profile can include contact information such as an electronic mail protocol, a mobile telephone number, an SMS protocol, a landline telephone number, or a postal address associated with users. 
     The MPTS  408  can include a notification engine  416 . The notification engine  416  can be configured to generate notifications and transmit the notifications to devices of electronic benefits accounts. In some aspects, the notification engine  416  comprises an innovative, non-conventional or non-routine implementation. In some aspects, the notification engine  416  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, the notification engine  416  is implemented to make or cause more effective and efficient use of computing and networking resources. For example, the notification engine  416  can cause more effective and efficient use of computing and network resources by reducing the number of processing cycles, memory or network bandwidth used to generate notification and transmit the notifications to devices of electronic benefits accounts. The notification engine  416  can provide an improved or faster notification by integrating or interfacing with the communication interface  410 , electronic account  418 , database  420 , policy engine  412 , or claims processor  220  to perform the notification. 
     The MPTS  408 , communications interface  410 , policy engine  412 , transaction engine  414 , and notification engine  416  can each include one or more processing units or other logic devices such as programmable logic array engines, modules, or circuitry designed and constructed to facilitate managing security on a network infrastructure. The MPTS  408  can include the components  100  shown in  FIG.  1 C  or  FIG.  1 D , or be configured to operate as a service in cloud  108 . The MPTS  408  can include or interact with one or more servers  106   a - n  and clients  102   a - n.    
     In some embodiments, the MPTS  408  can employ a multitier architecture such as a client-server architecture in which presentation, application processing, and data management functions are logically or physically separated. The presentation tier, or front-end, can include the communications interface  410  that serves static content or dynamic content to be rendered by the client  102  (e.g., by a web browser executing on client  102 ). The presentation tier or web server  210  can interact or communicate with the application tier to obtain data to provide to the client  102  or POS terminals  202   a - n . The application tier can include the policy engine  412 , transaction engine  414 , and notification engine  416  that controls the system&#39;s functionality and performs additional processing or analysis on data. The application tier can interact with the data tier to obtain the transaction data. The data tier can include data persistence mechanisms (database servers, file shares, etc.) and the data access layer that encapsulates the persistence mechanisms and exposes the data. The data tier can include databases  418  and  420 . The data tier can include an application programming interface (API) to the application tier. The databases  418  or  408  can include stored procedures (e.g., SQL statements) that perform tasks with respect the stored data. 
     In further detail, and in some embodiments, the MPTS  408  includes a communications interface  410 . The communications interface  410  can execute on one or more processors of a server. The communications interface  410  can include one or more communications ports and be configured with one or more network protocols. Communications ports can include, e.g., network ports, Ethernet ports, WAN ports, I/O ports, or software ports. The communication port can be configured with a network protocol such as Transport Layer Protocols such as TCP/IP or UDP that are configured to receive and process data packets received via a computer network. The port can include or be associated with an IP address of a host and a protocol type of the communication. 
     In some embodiments, the communication interface  410  can receive data packets. The data packets can be generated by a device at a merchant to conduct an electronic transaction at the merchant. The device can refer to a point of sale terminal (“POS terminal”) such as POS terminal  202   a . In some embodiments, the POS terminal  202  is the device at which a retail transaction is initiated. The POS terminal  202  is the point at which a customer of the entity or merchant makes a payment to the merchant in exchange for goods or services. At the point of sale the merchant can calculate the amount owed by the customer and provide options for the customer to make payment. The merchant can also issue a receipt for the transaction. 
     The POS terminal  202  can include hardware and software. Merchants can utilize weighing scales, scanners, electronic and manual cash registers, EFTPOS terminals, touch screens and any other wide variety of hardware and software available for use with POS terminal  202 . For example, a pharmacy can use software to customize the item or service sold when a customer has a special medication request. 
     The POS terminal  202  can include advanced features to cater to different functionality, such as inventory management, CRM, financials, warehousing, flexible spending account transactions, etc., all built into the POS software. The POS terminal  202  can be configured to conduct a transactions using a debit card, multipurse card, Bluetooth, near field communications, smartphone, smartwatch, mobile telecommunications computing device, wearable communications, RFID, etc. 
     The communications interface  410  can receive data packets generated by the POS terminal  202   a  responsive to an electronic transaction resulting in transmission of a request to adjudicate a single claim against an electronic benefits account. In some embodiments, the request to adjudicate a single claim against the electronic benefits account is transmitted responsive to a user swiping a payment card at the POS terminal. The payment card can include identifying information that can be used to identify an account identifier of the electronic benefit account against which to adjudicate the claim. The data packets can include header information and payload information. Multiple data packets can be strung together in a sequence. The header information can refer to TCP/IP headers that include fields such as source port, destination port, sequence number, acknowledge number, window size, etc. The payload information of the data packet can include information related to the electronic transaction, the request to adjudicate a single claim, the merchant, or the customer. The MPTS  408  can receive the data packet with header information and payload information and process the packets to obtain information for further processing. The payload can include data identifying the POS terminal  202   a  at which the electronic transaction occurred, the merchant providing the POS terminal  202   a , a merchant category of the merchant, financial information associated with the user performing the electronic transaction (e.g., via a card swipe or other communication technique used to perform the electronic transaction), an amount of expenditures of the electronic transaction, and other information facilitating adjudication of the single claim. The data packets (e.g., via the payload) can include the request to adjudicate the single claim. The request can specify the electronic benefits account for adjudication. The request can specify information for identifying a policy for performing the adjudication. The payload can include data identifying a merchant category of the merchant, an electronic benefits account, and a monetary amount of the electronic transaction. 
     The data packets can carry data identifying a merchant or merchant category of the merchant. In some embodiments, the data carried by the data packets include a merchant category code or identifier (e.g., dental, medical, etc.). In some embodiments, the data identifies a merchant, and the MPTS  408  determines a merchant category based on the identification of the merchant by, for example, using a merchant to merchant category mapping or lookup table stored in database  420 . In some embodiments, the data packets carrying the request to adjudicate the single claim against the electronic benefits account include a data structure having a first field indicating a merchant identifier, a second field indicating a total amount of expenditures, and a third field indicating the electronics benefit account. In some embodiments, the data packets are generated by a merchant device (e.g., a client device  102  of a merchant) to conduct an electronic transaction at the merchant, and the data packets carry data identifying a merchant category of the merchant, the electronic benefits account maintained and configured on the MPTS  408 , and a total monetary amount of the electronic transaction. 
     The data packets (e.g., payload of the data packets) can further identify an electronic account maintained and configured on the server. The electronic account can be maintained and configured in a database  418 . The electronic account can correspond to a user and have a unique identifier. The unique identifier can include numbers, letters, characters, symbols, etc. The electronic account can be associated with the customer making the transaction at the merchant. The POS terminal  202   a  can receive or determine the electronic account identifier via a card swipe or other communication technique employed at the POS terminal  202   a , which the POS  202   a  can then convey to the MPTS  408 . 
     The communications interface  410  can further receive data packets (e.g., payload information) identifying a monetary amount of the electronic transaction, such as a total amount of expenditures. The monetary amount can be for the purchase of goods or services made at the merchant. The monetary amount of the transaction can refer to the amount of funds in consideration for goods or services obtained from the entity or merchant. The merchant or entity can refer to the entity at which a point-of-sale terminal or device used to make the transaction is located or with which the terminal is associated. The monetary amount can be in any currency (e.g., United States dollars) or units. The monetary amount can be further tied to a category, such as medical services. 
     In some embodiments, the POS terminal  202  can generate multiple data packets for a single transaction. The multiple data packets can each include a header and a payload. The header can indicate that the multiple data packets are to be grouped together for routing, transmission or processing purposes. 
     The MPTS  408  can be configured to authenticate communications and transactions. In some embodiments, the communications interface  410  receives communications such as the request to adjudicate the single claim. The request can include security credential such as a security certificate or security token. The security credential can be associated with a user or a merchant. The MPTS  408  can be configured to extract the security credential from the request, and authenticate the request by comparing the security credential against a known or verified security credential. For example, the user profiles and/or merchant information stored in database  420  can include known or verified security credentials for comparison with the security credential of the request. In some embodiments, the MPTS  408  receives the request to adjudicate the single claim via the communications interface  410 , extracts a security credential from the request, analyzes the extracted security credential to identify a user, queries the database  420  for a verified security credential stored with a user profile corresponding to the identified user, compares the extracted security credential to the verified security credential, and authenticates the request based on the extracted security credential matching the verified security credential. In some embodiments, the MPTS  408  analyzes the extracted security credential to identify a merchant, queries the database  420  for a verified security credential stored with merchant information corresponding to the identified merchant, compares the extracted security credential to the verified security credential, and authenticates the request based on the extracted security credential matching the verified security credential. 
     In some embodiments, the MPTS  408  includes a policy engine  412 . The policy engine  412  can execute on one or more processors of a server, such as a server of the MPTS  408 . The policy engine  412  can receive, retrieve, or otherwise obtain or access some or all of the data carried by the data packets. The policy engine  412  can receive, retrieve, or otherwise obtain or access policies, such as policies maintained in database  420 . The policy engine  412  can determine that the single claim against the electronic benefits account is approved for an amount of expenditures qualifying under the electronic benefits account, responsive to the communication interface  210  receiving the request to adjudicate the single claim. 
     The MPTS  408  can initiate a claim adjudication process responsive to receiving the data packets, such as by causing the policy engine  412  to execute policies maintained in the database  420 . The MPTS  408  can cause the policy engine  412  to identify a policy maintained in the database  420  to apply to the single claim to adjudicate the single claim based on information extracted from the received data packets. The MPTS  408  can cause the policy engine  412  to determine that a remote policy is required based on information extracted from the received data packets, and the MPTS  408  can request the remote policy by transmitting one or more data packets carrying a policy request to a remote server, such as a server of an insurance administrator or an employer. The policy request can cause the remote server to transmit the requested remote policy to the MPTS  408 . For example, the policy engine  412  can determine that the received data packets indicate a new insurance administrator or employer for which a policy is not yet maintained in the database  420 . 
     The policy engine  412  can identify a reimbursement policy of the electronic benefits account specifying an ordered list of account destinations for benefits account reimbursements via a configuration of the electronic benefits account maintained by the server, such as a server of the MPTS  408 . The ordered list of account destinations can include or refer to a set of electronic account identifiers or electronic account types that are in a sequence of priority. For example, each electronic account identifier or electronic account type can be associated with, correspond to, or configured with a priority. The priority can include a numeric value, score, text, symbol, or other indicator of a rank, preference, selection technique, selection protocol, or sequence. In some embodiments, the ordered list of account destinations includes at least one of: an electronic reimbursement account maintained by the MPTS  408 , such as a cash purse maintained in the database  418 ; an electronic reimbursement account maintained in a server by an entity remote from the MPTS  408 , such as a server of a financial institution, of an insurance administrator, or of an employer; a payroll account, such as a payroll account having direct deposit information for electronically transferring credits to the payroll account; or another account that can be credited by sending (e.g., mailing to a postal address) a check to the account. The electronic reimbursement account can include a tax benefit account, which may or may not include an HSA, an FSA, a checking account, a savings account, or other electronic accounts that can receive funds electronically. The ordered list can prioritize the electronic reimbursement account maintained by the MPTS  408  as a first-highest priority account destination; an electronic reimbursement account maintained remote from the MPTS  408  as a second-highest priority account destination; a payroll account having direct deposit information as a third-highest priority account destination; and another account requiring a check to be mailed as a fourth-highest priority account destination. Any other combination of account priorities are contemplated. In some embodiments, the MPTS  408  specifies a default ordered list. In some embodiments, a user associated with the request to adjudicate the single claim can specify the ordered list. In some embodiments, an insurance administrator or an employer can specify the ordered list. The MPTS  408  can be configured to receive the ordered list from client devices  102  of the user, the insurance administrator, or the employer. 
     The policy engine  412  can determine an electronic reimbursement account as a destination for a benefits account reimbursement via application of the reimbursement policy to the single claim. The electronic reimbursement account can be configured to allow transactions for non-qualifying benefits. For example, the electronic reimbursement account can be configured to be credited based on transactions that would otherwise not qualify under a policy applied during adjudication. The policy engine  412  can update the electronic reimbursement account maintained by the server with a value corresponding to a credit for the approved amount for the single claim. 
     The policy engine  412  can use or apply a policy that includes one or more techniques, algorithms, heuristics, rules or procedures. The policy can include decision points and utilize parameters or criteria. The policy can be based on criteria or rules that are established by an administrator of the MPTS  408  or another entity. The policy can facilitate determining whether the single claim against the electronic benefits account is approved for an amount of expenditures qualifying under the electronic benefits account. 
     The policy can be retrieved from a variety of entities, such as client devices  102  or servers associated with an insurance administrator, an employer, a financial institution (e.g., a bank administering or otherwise maintaining an electronic reimbursement account or a payroll account configured for direct deposit), or the claims processor  220 . The insurance administrator can establish or otherwise maintain the electronic benefits account. The employer can at least partially pay for or otherwise subsidize an insurance plan associated with the policy. In some embodiments, the policy defines a maximum amount of expenditures for all goods and services. For example, the policy can set maximum expenditures for a billing cycle, such as a monthly billing cycle, an annual billing cycle, or a billing cycle of another length of time. The maximum amount of expenditures can be prorated for billing cycles less than a year in length, based on a standardized annual amount of expenditures, such as when a user activates the electronic benefits account at a time other than a typical enrollment time for the annual billing cycle. 
     In some embodiments, the policy defines purchase type categories. Purchase type categories can be exclusive or overlap for various goods and services. For example, healthcare related expenditures can fall within a first category, and cafeteria expenditures can fall within a second category. Healthcare related expenditures can include services provided by a healthcare provider, goods purchased at a pharmacy, goods purchased based on a prescription. 
     In some embodiments, the policy can be to select the highest priority account destination for the reimbursement. The policy can be to select the highest priority account destination available for receiving funds electronically for reimbursement. The policy can be to select the highest priority account destination associated with the electronic benefits account used to adjudicate the single claim. For example, an insurance administrator or employer can provide both an electronic benefits account and an electronic reimbursement account to a particular user, or an electronics benefit account and an electronic reimbursement account can be otherwise associated with or linked to one another, and the policy can select the highest priority account destination associated with or linked to the electronics benefit account. 
     In some embodiments, the policy can be based on a merchant category. The policy can be based on a merchant category code (“MCC”). The MCC can refer to a code (e.g., a four-digit number) that can be assigned to a business by an entity, such as a credit card company or the MPTS  408 . This code can be used to classify the merchant by a business type, or type of goods or services provided. 
     For example, the policy can be: if merchant category corresponds to (or equals or maps to or is) medical, then use benefits purse. In another example, the policy can be: if merchant category corresponds to dental, then use benefits purse. In another example, the policy can be: if merchant category maps to qualified benefits category, then use benefits purse. In some embodiments, the electronic account can include a benefits purse that is preconfigured with merchant categories that map to qualified or approved categories, such as categories for funds exempt from payroll tax can be used to conduct a transaction. 
     In some embodiments, the policy defines geographical requirements for expenditures. For example, expenditures can be approved only if they take place within a particular country, state, county, city, or other geographical region. Expenditures can be approved only if they take place within a certain distance of a home location of the user. 
     In some embodiments, the policy defines a variety of approval levels for expenditures. For example, a first approval level for expenditures can automatically approve expenditures without further review. A second approval level for expenditures can approve expenditures following review by an administrator of the benefits account. A third approval level for expenditures can approve expenditures following confirmation received from the user. For example, after the MPTS  408  receives the request to adjudicate the single claim via the communications interface  410 , the MPTS  408  can transmit a request for confirmation to the client device  102 , and approve the expenditure responsive to receiving the confirmation. 
     In some embodiments, the MPTS  408  can process multiple policies before identifying a policy that is satisfied. For example, the policy can include geographic guidelines and provider guidelines, such that expenditures are approved for goods and services purchased within a geographical region from certain providers or merchants. The policy can prioritize guidelines. For example, the policy can include both geographic guidelines and merchant category guidelines, with merchant category guidelines having a higher priority such that expenditures at approved merchants are always approved independent of geographic location. 
     In some embodiments, the policy can include multiple criteria. For example, the policy can include: if merchant category corresponds to (or equals or maps to or is) medical or dental or vision or parking, then approve the expenditure. 
     In some embodiments, the policy can include an action to take when the policy is not satisfied. For example, when the policy is not satisfied, the policy can include generating a notification by the notification engine  416  and transmitting the notification to the client device  102   a  via the communications interface  410 , the notification indicating that the policy is not satisfied. The action can include transmitting a request for more information and preventing the transaction engine  414  or the policy engine  412  from performing further actions until the request for more information is satisfied. 
     In some embodiments, the policy engine  412  can use a policy that includes monetary amount thresholds. For example, a merchant category can correspond to an approved benefits purse. However, the approved benefits purse can include a threshold that limits a monetary amount of a transaction. For example, the benefits purse can be configured with a parking sub-purse with a monetary amount threshold. The monetary amount threshold can be for a time period, such as a month, quarter, year, week, or other time interval. For example, the transport or parking sub-purse can be approved for $200 per month for transactions made at merchants that correspond to merchant category transport or parking. Thus, the policy can include criteria such as merchant category, transaction amount, and time interval. For example: if merchant category corresponds to transport and if transaction amount less than or equal to approved transaction amount for time interval, then use transport sub-purse. 
     In some embodiments, the policy engine  412  can apply a second policy directed to additional factors after using a first policy. The policy engine  412  can select the second policy responsive to or based on the first policy. The second policy can be associated with a monetary amount, transaction amount, or reimbursement amount. The policy engine  412  can use the second policy to determine a reimbursement amount. The policy engine  412  can use a reimbursement policy. The reimbursement policy can be applied to the data that identifies the transaction amount, merchant category, and electronic account. The reimbursement policy can be selected based on an insurance policy tied to or associated with the electronic account. The electronic account can include a unique identifier that maps to or corresponds to a type of insurance policy or reimbursement policy. The reimbursement or insurance policy (e.g., second policy) can be established by an administrator of the MPTS  408 , an employer of the user/customer conducting the electronic transaction, or another entity. Using this reimbursement policy, the policy engine  412  can determine a reimbursement amount for the electronic transaction. For example, if electronic the transaction amount for the medical service was $100, the policy engine  412  can determine that 80% of the transaction is covered by insurance. The MPTS  408  can initially deduct $100 from the benefits purse of the electronic account in accordance with the first policy. Thereafter, applying the second policy using the policy engine  412  to adjudicate the single claim for the electronic transaction, the MPTS  120  can determine to credit or reimburse the electronic account $80. 
     In some embodiments, the policy engine  412  can receive an indication from a claims processor  220  external to the MPTS  408  via the network  104 . In some embodiments, the MPTS  408  or the policy engine  412  is configured with the claims processor  220  or configured to interface with the claims processor  220  via communications interface  410 . The claims processor  220  can process an insurance claim to determine a reimbursement amount. The claims processor  220  can be configured to use one or more policies or rules to process the insurance claim and determine a reimbursement amount. The policies can be based on a type of insurance coverage associated with a user of the electronic account. The claims processor  220  can automatically receive the insurance claim responsive to a user conducting a transaction using the multipurse card connected with the electronic account. The claims processor  220  can obtain, via database  418  or  420 , policies, profiles and merchant information to adjudicate the claim. The claims processor  220  can adjudicate the claim, determine a reimbursement amount, and provide an indication to the MPTS  408  regarding the reimbursement amount. The indication can identify the electronic account, user identifier, time, original transaction amount, reimbursement policy, or reimbursement amount. 
     The MPTS  408  can include a transaction engine  414 . The transaction engine  414  can receive information or instructions from the policy engine  412  regarding a transaction, and conduct the transaction. The transaction engine  414  can obtain merchant information from database  420  and electronic account information from database  418  to perform the transaction. The transaction can include electronically transferring funds from a first account to a second account. The first account can be an electronic account, and the second account can be an account of a merchant (such as a financial account). In some cases, the transaction engine  414  can facilitate a transfer of funds between an electronic account of a claims processor  220  and the electronic account  418 . The transaction engine  414  can receive account identifiers, transaction amounts, credentials, authentication information, etc. The transaction engine  414  can conduct the transaction via communications interface  410 , thereby using the network protocols, security protocols and other components or interfaces provided by the communications interface  410 . 
     For example, the transaction engine  414  can be configured to receive a request from the policy engine  412  to execute a transaction, such as to execute a reimbursement transaction in which the electronic reimbursement account is updated with the value corresponding to the credit for the approved amount for the single claim. The request can include an identifier for the electronic reimbursement account, such as the user profile associated with the electronic reimbursement account. The transaction engine  414  can perform a lookup in the database  420  to retrieve the user profile. The transaction engine  414  can extract an identifier for an electronic source account from which the funds are to be transferred, such as electronic financial account. The transaction engine  414  can transmit a fund request to a server maintaining the electronic financial account, such as a server of a financial institution. The fund request can include an identifier of the electronic financial account, such as a routing number and an account number in the case of funds to be transferred from an electronic checking or savings account, or a credit card number in the case of funds to be transferred from an electronic credit card account. The fund request can cause the electronic financial account to release an amount of funds from the electronic financial account for transfer. The fund request can cause the server maintaining the electronic financial account to release an amount of funds corresponding to the credit for the approved amount for the single claim, and transmit a confirmation to the transaction engine  414  of the release of the amount of funds. 
     The transaction engine  414  can perform a lookup in the database  218  in which the electronic reimbursement account is maintained, and update the amount of funds in the electronic reimbursement account responsive to receiving the confirmation. In some embodiments, the transaction engine  414  can receive the confirmation, extract the amount of funds from the confirmation, and compare the amount of funds to an expected credit for the approved amount for the single claim. 
     Responsive to the amount of funds from the confirmation matching the expected credit for the approved amount for the single claim, the transaction engine  414  can update the amount of funds in the electronic reimbursement account, and the transaction engine  414  can generate a confirmation message indicating the successful transfer of funds to be transmitted to the client device  102  via the communications interface  410 . Responsive to the amount of funds from the confirmation not matching the expected credit, the transaction engine  414  can transmit an additional fund request to the server maintaining the electronic financial account via the communications interface  410 . The additional fund request can include an error message generated by the transaction engine  414  based on the amount of funds from the confirmation not matching the expected credit. The transaction engine  414  can also generate an error message to be transmitted to the client device  102  via the communications interface  410 . 
     The MPTS  408  can include a notification engine  416 . The notification engine  416  can be executed on one or more processors of a server. The notification engine  416  can generate a notification, responsive to the request adjudicated by the server and the update by the policy engine  412  of the electronic reimbursement account with the value corresponding to the credit for the approved amount for the single claim, a notification identifying the update to the electronic reimbursement account corresponding to the credit. The notification engine  416  can transmit one or more packets carrying data indicating the notification of the credit to a device of the electronic benefits account, such as a client  102 . 
     In some embodiments, the notification engine  416  can be configured to provide the notification in real-time via the communications interface  410 . The communications interface  410  can be configured to provide the notification via an electronic mail protocol, SMS protocol, notification or prompt on a mobile telecommunications devices (e.g., a smartphone, tablet, smartwatch, wearable telecommunications device, laptop computer, desktop computer, etc.). A user profile maintained in the database  420  can include contact information corresponding to the client  102 , and the notification engine  416  can be configured to transmit the first one or more packets to the client  102  using the contact information via the communications interface  410 . In some embodiments, the user profile can include a priority order associated with multiple contact information, a preferred contact information, and/or an indication of multiple contact information for receiving notifications. For example, the user profile can indicate an electronic mail protocol as a preferred contact information, and the notification engine  416  can be configured to identify the electronic mail protocol as the preferred contact information, and transmit the one or more data packets to the client  102  using the electronic mail protocol via the communications interface  410 . 
     In some embodiments, a profile database of the electronic benefits account, such as a profile database maintained in database  418 , includes an entry corresponding to a device configured to receive notifications for the electronic benefits account. The entry includes a unique identifier for the device and a notification mode including at least one of an SMS protocol or an electronic mail protocol. The MPTS  408  can be configured to perform a lookup in the profile database to identify the device configured to receive notifications for the electronic benefits account. The MPTS  408  can be configured to retrieve, from the profile database, the unique identifier for the device and the notification mode, the notification mode including at least one of an SMS protocol or an electronic mail protocol. The MPTS  408  can be configured to configure the first one or more packets carrying the data indicating the notification based on the notification mode. For example, if the notification mode includes an SMS protocol, then the MPTS  408  can be configured to configure the first one or more packets into packets having a file size less than or equal to a maximum file size for an SMS protocol transmission. 
     The notification can be delivered in real-time. A real-time notification can refer to providing the notification soon after completion of an action by the MPTS  408  (e.g., within 30 seconds, within 1 minute, within 5 minutes). The action resulting in a real-time notification can be an adjudication of a single claim against the electronic benefits account; an application of a reimbursement policy to the single claim; an update of the electronic benefits account with a value corresponding to a credit for the approved amount for the single claim, among others. For example, responsive to the MPTS  408  adjudicating the request and the policy engine  412  updating a purse (e.g., a benefits purse) of the electronic account of database  418 , the notification engine  416  can generate a notification identifying the update to the benefits purse of database  418  and cause the notification to be transmitted to the client  102   a  via the communications interface  410 . 
     The notification can be transmitted within a pre-determined time interval of receiving the request to adjudicate the single claim. The predetermined time interval can be a time period after an action, e.g. 10 minutes, 5 minutes, 1 minute, 30 seconds. The action can include receiving the request to adjudicate the single claim, receiving one or more packets generated by a merchant device to conduct an electronic transaction at the merchant, and/or generating the notification of the initiation of the single claim adjudication process. The pre-determined time interval can be set in a configuration file or profile maintained by the MPTS  408  in the database  418  or the database  420 , the configuration file or profile corresponding to the electronic benefits account. The pre-determined time interval can be set by an entity remote from the MPTS  408 . For example, the MPTS  408  can transmit a time interval request to a remote server of an insurance administrator or an employer. The time interval request can cause the remote server to transmit the configuration file or profile setting the pre-determined time interval to the MPTS  408 . The notification engine  416  can process the configuration file or profile to extract the pre-determined time interval in order to transmit the notification within the pre-determined time interval. 
     In some embodiments, responsive to the action occurring that initiates the pre-determined time interval, the notification engine  416  can generate a placeholder notification to be transmitted to the client device  102  independent of the status of adjudication of the single claim. For example, the placeholder notification can indicate that the claim adjudication process has been initiated. The placeholder notification can indicate that further information is required to complete the claim adjudication process. The notification engine  416  can transmit the placeholder notification prior to expiry of the pre-determined time interval via the communications interface  410  to provide real-time communication of the adjudication process. 
     In some embodiments, the pre-determined time interval can be based on the type of electronic reimbursement account or an expected time required to update the electronic reimbursement account with the reimbursement. For example, if the electronic reimbursement account can be updated by wire transfer, than the pre-determined time interval can be approximately ten seconds, thirty seconds, one minute, etc. If the electronic reimbursement account can be updated by direct deposit, then the pre-determined time interval can be a time associated with electronic communication between the MPTS  408  and an electronic payroll account, such as ten minutes. The pre-determined time interval can be based on a time required to transfer funds from an electronic bank account associated with an insurance administrator or with an employer to the electronic reimbursement account. The pre-determined time interval can be based on a time required for an indication of the adjudication of the single claim to be received at a remote server in order to cause the funds to be transferred to the electronic reimbursement account. 
     In some embodiments, the notification can include status information regarding the single claim adjudication (e.g., single claim approved, single claim denied, single claim submitted for transfer, single claim adjudication complete, single claim adjudication incomplete, single claim adjudication pending, or single claim adjudication pending further review). In some embodiments, the notification can include status information regarding the application of the reimbursement policy to the single claim (e.g., processing reimbursement, reimbursement approved, reimbursement denied, reimbursement submitted for transfer, transferring reimbursement, or reimbursement complete). In some embodiments, the notification can include status information regarding the update of the electronic benefits account with the value corresponding to the credit for the approved amount for the single claim (e.g., update complete, processing update, update incomplete, credit complete, processing credit, or credit incomplete). In some embodiments, the notification engine  416  is configured to generate notification of the initiation of the single claim adjudication process, and transmit the notification via the communications interface  410  to the client device  102   a.    
     In some embodiments, the notification engine  416  is configured to generate electronic reports regarding the electronic transaction and the update of the electronic reimbursement account. The notification engine  416  can retrieve an electronic report template configured for the electronic benefits account responsive to transmitting the instructions including the value (e.g., a value corresponding to the approved amount for the single claim) to update the electronic reimbursement account. The notification engine  416  can generate the notification using the electronic report template. The notification can include a balance of the electronic reimbursement account subsequent to updating the electronic reimbursement account with the credit. The notification engine  416  can transmit the one or more data packets carrying the notification generated using the electronic report template to the client device  102   a  via the communications interface  410 . For example, the communications interface  210  can transmit the one or more data packets via at least one of an SMS protocol or an electronic mail protocol. 
     In some embodiments, the notification engine  416  is configured to retrieve an electronic report template configured for the electronic benefits account and configured for transmission via a particular transmission protocol. For example, the notification engine  416  can retrieve an SMS-compatible electronic report template configured to be compatible with SMS protocol, such as an electronic report template having a particular character limit and an organization configured to use plain text. The SMS-compatible electronic report template can be configured to prioritize particular notification information, such as a status of the request to adjudicate the single claim, and/or the total amount of expenditures approved. The notification engine  416  can retrieve an electronic mail-compatible electronic report template configured to be compatible with electronic mail protocol, such as an electronic report template using rich text or HTML. In some embodiments, the notification engine  416  can retrieve multiple electronic report templates compatible with multiple transmission protocols, generate multiple notifications using the multiple transmission protocols, and transmit the multiple notifications via the multiple transmission protocols via the communications interface  410 . 
     In some embodiments, the notification engine  416  is configured to transmit an instruction to the client device  102   a  to trigger an application on the client device  102   a  to launch a user interface (e.g., a prompt, a graphical user interface, etc.) or application program interface configured to display the information provided via the electronic report. The notification engine  416  can be configured to generate the notification to include the instruction and the electronic report. The notification engine  416  can be configured to transmit an application configuration request to the client device  102   a  that causes the client device  102   a  to transmit details regarding the user interface, and the notification engine  416  can configure the electronic report based on the received details. The notification engine  416  can be configured to transmit an application program interface to the client device  102   a  in a format configured for use by the client device  102   a , causing the client device  102   a  to install the application program interface in order to display the electronic report received in the notification. The notification engine  416  can configure the one or more data packets carrying the notification to cause the client device  102   a  to launch the user interface or application program interface in order to display the electronic report included in the notification. 
     In some embodiments, the MPTS  408  (e.g., via communication interface  410 ), receives a request for account information from a client device  102  associated with an electronic account maintained or configured on the MPTS  408 . The request for information can include information about a balance of the electronic account, available purses, balance of an individual purse, status of an adjudication associated with the account, status of a reimbursement, status of an update notification, policies associated with purses, policies associated with adjudication, or transaction history. The request can further include authentication information or credentials associated with the request. The authentication information can include network security credentials, such as security certificates or tokens. The authentication information can further include a username, password, two-tier authentication information (e.g., date of birth, cell phone number, verification code sent via text message to cell phone number in profile associated with electronic account). The authentication can include credentials depending on a security level associated with the account information requested. For example, a first security level requiring a first item of authentication information can be associated with information such as a balance of the electronic account, and a second security level requiring both a first item of authentication information and a second item of authentication information can be associated with personal identification information of associated with the account, such as a date of birth or social security number associated with the account. The request can be from a client device such as a smartphone. The request can be sent using a text messaging protocol such as SMS. The MPTS  408  can authenticate a request sent via SMS based on the cell phone number of the device sending the SMS request, and matching the cell phone number with a corresponding number maintained in a profile in database  418  for the electronic account. 
     Responsive to authenticating or otherwise approving the request, the MPTS  408  can access a data record in database  418  for the electronic account to generate a report with the requested information, or generate a standard report, or generate another preconfigured report. The report can identify the account holder information, available purses, benefits purses, reimbursement purse, subpurses, and available amounts for each purse. The report can further identify a transaction history for the electronic account or each subpurse thereof. The report can further identify or indicate if one or more purses have reached a maximum limit. The report can further include a forecast based on current/previous transaction history that indicates whether the user can likely deplete available resources or exceed maximum limits based on current spending for a time interval. The report can further include information associated with adjudication of a single claim, such as an adjudication status, a credit associated with the adjudication, and/or a reimbursement account updated based on the credit associated with the adjudication. 
     In some embodiments, the MPTS  408  is configured to determine a balance of the electronic reimbursement account maintained in the database  418 . The MPTS  408  can determine the balance prior to transmitting the notification of the credit to the electronic reimbursement account via the communications interface  410 . The MPTS  408  can determine that the balance includes the value used to update the electronic reimbursement account, and then transmit the one or more data packets carrying data indicating the notification of the credit responsive to determining that the balance includes the value. 
     In some embodiments, the MPTS  408  is configured to parse data packets carrying the request to adjudicate the single claim in order to process the request. For example, the one or more data packets carrying the request to adjudicate the single claim can include the request data structure including the first field indicating a merchant ID, the second field indicating the total amount of expenditures, and the third field indicating the electronic benefits account (e.g., an electronic benefits account maintained in the database  418  of the MPTS  408 ). The MPTS  408  can be configured to parse the one or more packets to identify the electronic benefits account indicated by the third field. The MPTS  408  can be configured to perform a lookup in a benefits account policy database maintained by the MPTS  408  in the database  418  to retrieve the electronic benefits account policy corresponding to the single claim against the electronic benefits account. The MPTS  408  can be configured to apply the electronic benefits account policy using the merchant ID and the total amount of expenditures to adjudicate the single claim. Responsive to the application of the electronic benefits account policy, the MPTS  408  can be configured to generate the indication that the single claim against the electronic benefits account policy is approved for the amount of expenditures qualifying under the electronic benefits account. 
     The MPTS  408  can be further configured to determine that the amount of expenditures qualifying under the electronic benefits account is different from the total amount of expenditures. For example, the MPTS  408  can be configured to use the determination to identify multiple electronic reimbursement accounts, to provide a qualifying amount to a reimbursement account, or to notify a user associated with the electronic benefits account that the amount of expenditures qualifying under the electronic benefits account is different from the total amount of expenditures. The amount of expenditures qualifying under the electronic benefits account can be less than the total amount of expenditures. For example, the policy engine  412  can determine that a maximum amount of expenditures in a particular time period or billing cycle will be exceeded if the total amount of expenditures is reimbursed, and instead an amount less than the total amount of expenditures is to be reimbursed. The policy engine  412  can determine based on a product category or merchant category of the goods or services associated with the electronic transaction that the goods or services qualify for less than a full reimbursement, such as a percentage reimbursement (e.g., 10%, 25%, 50%, 75%, 80%, 90%, etc.). For example, the policy engine  412  can receive the request to adjudicate the single claim and process the request to extract the product category or merchant category. The policy engine  412  can perform a lookup in the reimbursement policy maintained in the database  420  to determine whether the extracted product category or merchant category corresponds to or qualifies for a particular amount of reimbursement, such as percentage reimbursement. 
     The amount of expenditures qualifying under the electronic benefits account can be different from the total amount of expenditures based on the policy engine  412  determining that the reimbursement policy is not congruent with the goods or services associated with the electronic transaction, such as if a reimbursement policy associated with the electronic benefits account does not correspond to the goods or services. For example, the reimbursement policy can only apply to goods purchased at a pharmacy based on a prescription, and the electronic transaction can be based on a non-prescription purchase at a pharmacy. The policy engine  412  can process the reimbursement policy to retrieve a list of qualifying goods or services. The policy engine  412  can process the reimbursement policy to retrieve a list of non-qualifying goods or services. The request to adjudicate the single claim can include an identifier of the merchant category and an identifier of the goods or services purchased in the electronic transaction. The policy engine  412  can process the identifiers and perform a lookup in the reimbursement policy maintained in the database  420  to determine whether the goods or services purchased in the electronic transaction correspond to qualifying goods or services by comparing the identifiers to merchant categories and goods or services that are located in the list of qualifying goods or services or in the list of non-qualifying goods or services. 
     In some aspects, the system of the present solutions implements a combination of the communication interface  410 , policy engine  412 , electronic account  418 , database  420 , transaction engine  414 , notification engine  416  or claims processor  220  in an innovative, non-conventional or non-routine manner. In some aspects, the system of the present solutions integrates the communication interface  410 , policy engine  412 , electronic account  418 , database  420 , transaction engine  414 , notification engine  416  or claims processor  220  in an innovative, non-conventional or non-routine manner to implement the improved functionality, performance and operation of the present solution. In some aspects, the system of the present solutions integrates the communication interface  410 , policy engine  412 , electronic account  418 , database  420 , transaction engine  414 , notification engine  416  or claims processor  220  in an innovative, non-conventional and/or non-routine manner to more efficiently and effectively use computing and networking resources. The communication interface  410 , policy engine  412 , electronic account  418 , database  420 , transaction engine  414 , notification engine  416  or claims processor  220  are integrated in an innovative, nonconventional manner to mitigate, reduce, prevent, or resolve the technical problems of adjudicating a single claim in real-time and notifying a user of the result. The communication interface  410 , policy engine  412 , electronic account  418 , database  420 , transaction engine  414 , notification engine  416  or claims processor  220  integrated in the innovative, non-conventional manner address at least these technical problems by determining, responsive to the communication interface receiving the request to adjudicate the single claim, that the single claim against the electronic benefits account is approved for an amount of expenditures qualifying under the electronic benefits account; identifying, via a configuration of the electronic benefits account maintained by the server, a reimbursement policy of the electronic benefits account specifying an ordered list of account destinations for benefits account reimbursements; determining, via application of the reimbursement policy to the single claim, an electronic reimbursement account as a destination for a benefits account reimbursement, the electronic reimbursement account configured to allow transactions for non-qualifying benefits account expenditures; updating the electronic reimbursement account maintained by the server with a value corresponding to a credit for the approved amount for the single claim; generating, responsive to the request adjudicated by the server and the update by the policy engine of the electronic reimbursement account with the value corresponding to the credit for the approved amount for the single claim, a notification identifying the update to the electronic reimbursement account corresponding to the credit; and transmitting, via the computer network to a device of the electronic benefits account, a first one or more packets carrying data indicating the notification of the credit. 
     Referring now to  FIG.  5   , a flow diagram depicting an embodiment of an electronic computer network  500  using the MPTS  408  is shown. The MPTS  408  can include any of the components or modules depicted in  FIG.  4   , such as the MPTS  120 , and can perform the functions of the MPTS  120  and the components or modules depicted in  FIG.  4   . The electronic computer network  500  illustrates how an electronic transaction is received by the MPTS  408  and used by the MPTS  408  to cause transmission of a notification to the client device  102   a . The electronic transaction occurs at the POS terminal  202   a , such as when the participant swipes their card at the POS terminal  202   a . The electronic computer network  500  is shown to include the MPTS  408  in electronic communication with specific electronic entities including the client device  102   a , the POS terminal  202   a , a merchant server  506 , an insurance administrator server  508 , and an employer server  510 . 
     While  FIG.  5    depicts the insurance administrator server  508  and the employer server  510  as being remote from the MPTS  408 , in some embodiments, the MPTS  408  can include the insurance administrator server  508  and/or the employer server  510 . The MPTS  408  can maintain the insurance administrator server  508  and/or the employer server  510 . The MPTS  408  can include local modules of the insurance administrator server  508  and/or the employer server  510  that are maintained by the MPTS  408  and then synchronized or mirrored to the insurance administrator server  508  and/or the employer server  510 . 
     In some embodiments, the MPTS  408  includes interfaces configured to receive and process electronic data transmissions from the electronic entities. Each interface can be configured to authenticate the data transmissions, such as by using security credentials. Each of the electronic entities can also include an interface configured to receive electronic data transmissions from the MPTS  408 , and the electronic entity interfaces can be configured to authenticate the data transmissions from the MPTS  408 , such as by using security credentials. The MPTS  408  can be configured to transmit interface software to the electronic entities to cause the electronic entities to be compatible with the MPTS  408 . 
     In some embodiments, responsive to the electronic transaction at the POS terminal  202   a , a request to adjudicate the single claim  520  is received at the MPTS  408  via the merchant server  506  as one or more data packets  524 . The MPTS  408  can include a merchant server-facing interface configured to receive the request  520  from the merchant server  506  as the one or more data packets  524 , and extract data from the one or more data packets  524  into a format for the MPTS  408  to process. For example, the one or more data packets  524  can carry data identifying a merchant category of the merchant, the electronic benefits account maintained and configured on the MPTS  408 , and a total monetary amount of the electronic transaction; the MPTS  408  can parse the one or data packets  524  to extract the carried data. The one or more data packets  524  can include a request data structure having a first field indicating a merchant ID, a second field indicating a total amount of expenditures, and a third field indicating the electronic benefits account. The MPTS  408  can parse the one or more data packets to identify the electronics benefit account indicated via the third field; perform, with the identification of the electronic benefits account, a lookup in the benefits account policy database  420  maintained by the MPTS  408 ; retrieve, responsive to the lookup, the electronic benefits account policy corresponding to the single claim against the electronic benefits account; and generate, responsive to application of the electronic benefits account policy using the merchant ID and the total amount of expenditures, the indication that the single claim against the electronic benefits account is approved for the amount of expenditures qualifying under the electronic benefits account. 
     In some embodiments, a request to adjudicate the single claim  522  is received at the MPTS  408  directly from the POS terminal  202   a . The MPTS  408  can include a POS terminal-facing interface configured to receive the request  522  from the POS terminal  202   a  as one or more data packets, and extract data from the one or more data packets into a format for the MPTS  408  to process. 
     In some embodiments, responsive to receiving the one or more data packets  524  of the request  520  or the one or more data packets of the request  522 , the MPTS  408  executes the policy engine  412  using a policy maintained in the database  420  to determine that the single claim against the electronic benefits account (e.g., an electronic benefits account maintained in the database  418 ) is approved for an amount of expenditures qualifying under the electronic benefits account. The MPTS  408  can process the one or more data packets  524  (or the one or more data packets of the request  522 ) to extract information such as identification information associated with a user of the electronic benefits account, transaction information such as identification information associated with the merchant of the merchant server  506 , an amount of expenditures associated with the electronic transaction that occurred at the POS terminal  202   a , a category of the goods or services associated with the expenditures, and other information for adjudicating the single claim. The MPTS  408  can process the extracted information to acquire identification information corresponding to an appropriate policy maintained in the database  420 , perform a lookup in the database  420  to access the appropriate policy, and execute the policy engine  412  using the appropriate policy to determine that the single claim against the electronic benefits account is approved for an amount of expenditures qualifying under the electronic benefits account. 
     In some embodiments, responsive to receiving the one or more data packets  524  of the request  520  or the one or more data packets of the request  522 , the MPTS  120  transmits an adjudication request  526  for adjudicating the single claim to an insurance administrator server  508 . The adjudication request  526  can be provided as one or more data packets including payload information such as the information extracted from the one or more data packets. The MPTS  408  can include an insurance administrator server-facing interface configured to receive a response  528  to the adjudication request  526  from the insurance administrator server  508 . The response  528  can include information specific to an insurance administrator managing the insurance administrator server  508 , such as adjudication policies, identification information for electronic benefits accounts administered by the insurance administrator, or reporting requirements of the insurance administrator for reporting expenditure approvals. 
     The adjudication request  526  can be configured to cause the insurance administrator server  508  to transmit the response  528  to the adjudication request  526 . The adjudication request  526  can include a request for the insurance administrator server  508  to adjudicate the single claim, and the response  528  can indicate whether the expenditures of the single claim have been approved, or provide another indication of an adjudication status of the single claim. 
     The adjudication request  526  can be a request configured to cause the insurance administrator server  508  to transmit a policy with the response  528  so that the MPTS  408  can adjudicate the single claim using the policy engine  412  based on the transmitted policy. The response  528  can be received as one or more data packets, and the MPTS  408  can extract the policy from the response  528  and update the policies maintained in database  420  of the MPTS  408  based on the extracted policy. The MPTS  408  can compare the extracted policy from the response  528  to the policies maintained in the database  420 , verify a version status of the extracted policy against a similar policy maintained in the database  420  (e.g., a similar policy having a matching version history), and update the policy maintained in the database  420  responsive to determining that the policy engine maintained in the database  420  is out of date. 
     In some embodiments, responsive to receiving the one or more data packets  524  of the request  520  or the one or more data packets of the request  522 , the MPTS  408  transmits an adjudication request  530  for adjudicating the single claim to an employer server  510 . The adjudication request  530  can be provided as one or more data packets including payload information such as the information extracted from the one or more data packets. The MPTS  408  can include an employer server-facing interface configured to receive a response  532  to the adjudication request  530  from the employer server  508 . The response  532  can include information specific to an employer funding managing the employer server  510 , such as adjudication policies, identification information for electronic benefits accounts funded or otherwise administered by the employer, tax information, or reporting requirements of the employer for reporting expenditure approvals. 
     The adjudication request  526  can be configured to cause the insurance administrator server  508  to transmit the response  528  to the adjudication request  526 . The adjudication request  526  can include a request for the insurance administrator server  508  to adjudicate the single claim, and the response  528  can indicate whether the expenditures of the single claim have been approved, or provide another indication of an adjudication status of the single claim. 
     The adjudication request  530  can be a request configured to cause the employer server  510  to transmit a policy with the response  532  so that the MPTS  408  can adjudicate the single claim using the policy engine  412  based on the transmitted policy. The response  532  can be received as one or more data packets, and the MPTS  408  can extract the policy from the response  532  and update the policies maintained in database  420  of the MPTS  408  based on the extracted policy. The MPTS  408  can compare the extracted policy from the response  532  to the policies maintained in the database  420 , verify a version status of the extracted policy against a similar policy maintained in the database  420  (e.g., a similar policy having a matching version history), and update the policy maintained in the database  420  responsive to determining that the policy engine maintained in the database  420  is out of date. 
     In some embodiments, responsive to receiving a response  528  or  532  indicating that the single claim against the electronic benefits account is approved, or responsive to the policy engine  412  determining that the single claim against the electronic benefits account is approved, the policy engine  412  is executed to identify, via a configuration of the electronics benefit account maintained by the MPTS  408 , the reimbursement policy of the electronic benefits account specifying an ordered list of account destinations for benefits account reimbursements. The policy engine  412  can be executed to determine, via application of the reimbursement policy to the single claim, an electronic benefits account maintained in database  418  as a destination for a benefits account reimbursement, the electronic reimbursement account configured to allow transactions for non-qualifying benefits account expenditures. The policy engine  412  can be executed to update the electronic reimbursement account maintained by the MPTS  408  with a value corresponding to a credit for the approved amount of the single claim. 
     In some embodiments, the MPTS  408  is configured to generate a notification identifying the update to the electronic reimbursement account maintained by the MPTS  408  corresponding to the credit, and transmit, via the electronic computer network  500 , one or more notification data packets  534  carrying data indicating the notification of the credit to the client device  102   a . The MPTS  408  can be configured to transmit the one or more notification data packets  534  to the client device  102   a  via the communications interface  410 . 
     In some embodiments, the MPTS  408  is configured to perform a lookup in the database  420  for a contact protocol for the user associated with the electronic reimbursement account, identify the appropriate contact protocol for the user, and transmit the one or more notification data packets  534  to the client device  102   a  using the appropriate contact protocol for the user. The MPTS  408  can perform the lookup by querying the user profiles maintained in the database  420  for the contact protocol based on a user identity extracted from the request for adjudication of the single claim  522  or the one or more data packets  524 . The MPTS  408  can identify an electronic mail protocol as an appropriate contact protocol for the user, and transmit the one or more notification data packets  534  to the client device  102   a  using an electronic mail address of the electronic mail protocol associated with the client device  102   a . The MPTS  408  can be configured to transmit the one or more notification data packets  534  to the client device  102   a  in real time. The MPTS  520  can be configured to transmit the one or more notification data packets  534  to the client device  102   a  within a predetermined time interval of receiving data transmissions such as the request  522 , the one or more data packets  524 , the response  528 , or the response  532 . 
     Referring now to  FIG.  6   , a flow diagram depicting an embodiment of a method  600  of conducting electronic transactions via a computer network is shown. The method can be performed by one or more component or module of system  400 , the MPTS  408 , or one or more component or module depicted in  FIGS.  1 A- 1 D . In brief overview, at step  605 , a server of a multipurse transaction system receives a request to adjudicate a single claim against an electronic benefits account. At step  610 , the server determines that the single claim against the electronic benefits account is approved for an amount of expenditures qualifying under the electronic benefits account. At step  615 , the server identifies a reimbursement policy of the electronic benefits account specifying an ordered list of account destinations for benefits account reimbursements. At step  620 , the server determines an electronic reimbursement account as a destination for a benefits account reimbursement to allow transactions for non-qualifying benefits account expenditures. At step  625 , the server transmits instructions to update the electronic reimbursement account with a value corresponding to a credit for the approved amount for the single claim. At step  630 , the server generates a notification identifying the update to the electronic reimbursement account. At step  635 , the server transmits a first one or more packets carrying data indicating the notification of the credit to a device of the electronic benefits account. 
     Still referring to  FIG.  6   , and in further detail, a server of a multipurse transaction system receives a request to adjudicate a single claim against an electronic benefits account at step  605 . In some aspects, step  605  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  605  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  605  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     The server can include one or more processors. The server can include a communications interface for receiving the request. One or more data packets carrying data indicating the request can be received. The request can be received via a computer network using a networking protocol. The request can be generated by a device at a merchant, such as a POS Terminal. The data packets can include header information and payload information. The header information can include, e.g., TCP header information that can facilitate the routing and transmission of the data packet. The payload information can include data related to, describing, defining, associated with or otherwise about the request to adjudicate the single claim, including information regarding the electronic transaction occurring between the POS terminal, merchant, or customer. The one or more data packets can include data identifying a merchant category of the merchant, an electronic benefits account maintained and configured on the server, and a total monetary amount of the electronic transaction. The one or more data packets can include a request data structure having a request data structure having a first field including a merchant ID, a second field indicating a total amount of expenditures, and a third field indicating the electronic benefits account. The data packets can further include an electronic account associated with a multipurse card swiped at a POS terminal of a merchant conducting the transaction. The multipurse card can be a plastic card (e.g., debit card or debit card with a magnetic stripe or RFID), or be an electronic card stored on a telecommunications device which transmits an electronic account identifier corresponding to the electronic card via a wireless technology (e.g., Bluetooth, or NFC). The POS terminal can generate or obtain information that allows the server to conduct the transaction, encapsulate or process the information using a protocol to generate data packets, and transmit the data packets in a secure manner over a network to the server for further processing. The server can initiate a claim adjudication process responsive to receiving the one or more data packets. 
     At step  610 , the server determines that the single claim against the electronic benefits account is approved for an amount of expenditures qualifying under the electronic benefits account. In some aspects, step  610  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  610  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  610  is implemented to make or cause more effective and efficient use of computing and networking resources. The server can execute a policy engine maintained by the server to perform the determination. The server can perform the determination responsive to the communication receiving the request to adjudicate the single claim. In some embodiments, the server identifies a merchant category of the merchant from which the request received, and executes the policy engine using a policy applying to the identified merchant category to perform the determination. In some embodiments, the server parses the one or more data packets to identify the electronic benefits account, and performs a lookup in a benefits account policy database maintained by the server using the identification of the electronic benefits account to retrieve a benefits account policy corresponding to the single claim against the electronic benefits account. 
     The server can parse, process, or otherwise identify, from the header information or payload information of the one or more data packets, information about the request to adjudicate the single claim, including information regarding the electronic transaction occurring between the POS terminal, merchant, or customer. The server can identify the merchant category, the merchant ID, the electronic benefits account, and/or the total amount of expenditures. 
     At step  615 , the server identifies a reimbursement policy of the electronic benefits account specifying an ordered list of account destinations for benefits account reimbursements. In some aspects, step  615  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  615  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  615  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     The policy engine of the server can perform the identification via a configuration of the electronic benefits account maintained by the server. The policy engine can parse information regarding the electronic transaction or the request to adjudicate the single claim from the one or more data packets, such an identity of the user of the electronic benefits account, to identify the reimbursement policy. The policy engine can parse the configuration of the electronic benefits account to identify the reimbursement policy associated with the electronic benefits account. For example, the electronic benefits account configuration can include a data structure including a link or association field for associating the electronic benefits account to one or more electronic reimbursement accounts. For example, an insurance administrator or employer can provide both the electronic benefits account and an associated electronic reimbursement account. The ordered list can include one or more account destinations ordered by priority, such as an ordered list specifying that an electronic benefits purse has highest priority for reimbursement, an electronic cash purse has second-highest priority for reimbursement, and a paper check mailed to a postal address has third-highest priority for reimbursement. 
     At step  620 , the server applies the reimbursement policy to the single claim to determine an electronic reimbursement account as a destination for a benefits account reimbursement. In some aspects, step  620  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  620  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  620  is implemented to make or cause more effective and efficient use of computing and networking resources. The electronic reimbursement account is configured to allow transactions for non-qualifying benefits account expenditures. The policy engine of the server can perform the application and can perform the determination. The policy engine can process the reimbursement policy identified at step  615  to extract an identifier of the electronic reimbursement account that is the destination for the benefits account reimbursement. The policy engine can process the ordered list to identify the highest-priority account destination for reimbursement. The policy engine can process the ordered list to identify the high-priority account destination for reimbursement associated with the electronic benefits account. 
     At step  625 , the server transmits instructions to update the electronic reimbursement account with a value corresponding to a credit for the approved amount for the single claim. In some aspects, step  625  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  625  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  625  is implemented to make or cause more effective and efficient use of computing and networking resources. The server can maintain the electronic reimbursement account in a database and cause the maintained electronic reimbursement account to be updated. The electronic reimbursement account can be maintained by a remote server such as a financial institution server, an insurance administrator server, or an employer server, and the transmitted instructions can cause the remote server to update the electronic reimbursement account with the value corresponding to the credit for the approved amount. 
     In some embodiments, the server generates electronic reports regarding the electronic transaction and the update of the electronic reimbursement account. The server can retrieve an electronic report template configured for the electronic benefits account responsive to transmitting the instructions including the value to update the electronic reimbursement account. The server can generate the notification using the electronic report template. The notification can include a balance of the electronic reimbursement account subsequent to updating the electronic reimbursement account with the credit. The server can transmit the one or more data packets carrying the notification generated using the electronic report template to the client device. For example, the server can transmit the one or more data packets via at least one of an SMS protocol or an electronic mail protocol. The notification can cause the client device to launch or execute an interface (e.g., a graphical user interface or prompt) to display an electronic report based on the electronic report template. 
     In some embodiments, the server retrieves an electronic report template configured for the electronic benefits account and configured for transmission via a particular transmission protocol. For example, the server can retrieve an SMS-compatible electronic report template configured to be compatible with SMS protocol, such as an electronic report template having a particular character limit and an organization configured to use plain text. The SMS-compatible electronic report template can be configured to prioritize particular notification information, such as a status of the request to adjudicate the single claim, and/or the total amount of expenditures approved. The server can retrieve an electronic mail-compatible electronic report template configured to be compatible with electronic mail protocol, such as an electronic report template using rich text or HTML. In some embodiments, the server can retrieve multiple electronic report templates compatible with multiple transmission protocols, generate multiple notifications using the multiple transmission protocols, and transmit the multiple notifications via the multiple transmission protocols. 
     In some embodiments, the server performs a lookup in a profile database of the electronic benefits account. The lookup identifies the client device configured to receive the notifications for the electronic benefits account. For example, the profile database can include a preferred client device defined by a user of the electronic benefits account. The server retrieves from the profile database a unique identifier for the device and a notification mode. The notification mode includes at least one of an SMS protocol or an electronic mail protocol. The server configures the one or more packets carrying the data indicating the notification based on the notification mode. 
     At step  630 , the server generates a notification identifying the update to the electronic reimbursement account. In some aspects, step  630  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  630  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  630  is implemented to make or cause more effective and efficient use of computing and networking resources. The notification can include an indication of the electronics benefit account, and indication of the electronic reimbursement account, the value of the credit, an update status indicating whether the update was successful, a report of the adjudication of the single claim, a balance of the electronic reimbursement account, an indication of the electronic transaction, the merchant ID, the POS terminal at which the electronic transaction occurred, and/or the amount of expenditures approved by adjudication of the single claim. In some embodiments, responsive to initiating the claim adjudication process, the sever generates a notification of the initiation. 
     In some embodiments, responsive to the application of the electronic benefits account policy using the merchant ID and the total amount of expenditures, the server generates the indication that the single claim against the electronic benefits account is approved for the amount of expenditures qualifying under the electronic benefits account. For example, based on the electronic benefits account policy, the server can determine that the merchant falls within an approved network of the electronic benefits account. The server can perform a lookup in a database that can include a list of approved merchants and can include a list of non-approved merchants. The server can compare the merchant ID to the list of approved merchants. Responsive to the merchant ID corresponding to an entry in the list of approved merchants, the server can determine that the merchant is in the approved list. In some embodiments, the server can compare the merchant ID to both the list of approved merchants and the list of non-approved merchants; if the merchant ID does not correspond to an entry in either list, then the server can generate an indication that further information is necessary to adjudicate the single claim. The server can determine that the total amount of expenditures is less than a difference between a current balance of the electronic benefits account and a maximum balance of the electronic benefits account, such that approving the total amount of expenditures will not exceed the maximum balance. For example, the server can process the electronics benefit account to identify the current balance and maximum balance, and compare the sum of the current balance and the total amount of expenditures to the maximum balance to determine that approving the total amount of expenditures will not exceed the maximum balance. 
     In some embodiments, the server determines that the amount of expenditures qualifying under the electronic benefits account is different from the total amount of expenditures. The server can determine that the amount of expenditures qualifying is different from the total amount of expenditures based on the case that approving the total amount of expenditures would exceed a maximum balance of the electronic benefits account. The server can process the electronic benefits account to identify the current balance and maximum balance, and compare the sum of the current balance and the total amount of expenditures to the maximum balance to determine that approving the total amount of expenditures would exceed the maximum balance. The server can determine that an amount of expenditures qualifying under the electronic benefits account is the amount that would reach the maximum balance without exceeding the maximum balance. The server can be configured to update multiple electronic reimbursement accounts based on expenditures qualifying under the electronic benefits account and also using the electronic reimbursement configured to allow transactions for non-qualifying benefits expenditures. The server can determine that that the maximum amount of expenditures in a particular time period or billing cycle will be exceeded if the total amount of expenditures is reimbursed, and instead the server causes an amount less than the total amount of expenditures to be reimbursed. The server can determine based on a product category or merchant category of the goods or services associated with the electronic transaction that the goods or services qualify for less than a full reimbursement, such as a percentage reimbursement. For example, the server can process the request to adjudicate the single claim to extract the product category or merchant category, and perform a lookup in the database maintaining the reimbursement policy to identify a list of qualifying goods or services and/or a list of qualifying merchants, in which the lists are associated with a less than full reimbursement such as a percentage reimbursement. The server can compare the product category or merchant category to the list of qualifying goods or services or the list of qualifying merchants to determine whether to apply a less than full reimbursement for the request to adjudicate the single claim. 
     The amount of expenditures qualifying under the electronic benefits account can be different from the total amount of expenditures based on the server determining that the reimbursement policy is not congruent with the goods or services associated with the electronic transaction, such as if a reimbursement policy associated with the electronic benefits account does not correspond to the goods or services. For example, the reimbursement policy can only apply to goods purchased at a pharmacy based on a prescription, and the electronic transaction can be based on a non-prescription purchase at a pharmacy. The server can process the reimbursement policy to retrieve a list of qualifying goods or services. The server can process the reimbursement policy to retrieve a list of non-qualifying goods or services. The request to adjudicate the single claim can include an identifier of the merchant category and an identifier of the goods or services purchased in the electronic transaction. The server can process the identifiers and perform a lookup in the reimbursement policy to determine whether the goods or services purchased in the electronic transaction correspond to qualifying goods or services by comparing the identifiers to merchant categories and goods or services that are located in the list of qualifying goods or services or in the list of non-qualifying goods or services. 
     At step  635 , the server transmits one or more packets carrying data indicating the notification of the credit to a device of the electronic benefits account. In some aspects, step  635  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  635  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  635  is implemented to make or cause more effective and efficient use of computing and networking resources. The server can transmit the one or more packets in real time. The server can transmit the one or more packets within a predetermined time interval of a preceding action, such as receiving the request to adjudicate the single claim, receiving one or more packets generated by a merchant device to conduct an electronic transaction at the merchant, and/or generating the notification of initiation of the single claim adjudication process. 
     In some embodiments, prior to transmitting the one or more packets carrying the data indicating the notification of the credit, the server determines a balance of the electronic reimbursement account. For example, the server can process an identifier of the electronic reimbursement account, and perform a lookup in the database maintaining the electronic reimbursement account using the identifier to retrieve the balance of the electronic reimbursement account. The balance includes the value used to update the electronic reimbursement account. The server transmits the one or more data packets responsive to determining that the balance includes the value. Accordingly, the server is able to provide confirmation in the notification that the electronic reimbursement account has been updated with the credit. 
     In some embodiments, merchant category can refer to a merchant category code (“MCC”). Table 1 is an example mapping of merchant categories to purses in accordance with an embodiment: 
     
       
         
           
               
             
               
                 TABLE 1 
               
             
            
               
                   
               
               
                 Example mapping of merchant categories to 
               
               
                 purses in accordance with an embodiment. 
               
            
           
           
               
               
               
               
            
               
                   
                 MCC 
                 Merchant Category 
                 Purse 
               
               
                   
                   
               
               
                   
                 8099 
                 Medical Services 
                 Benefits Purse 
               
               
                   
                 8062 
                 Hospitals 
                 Benefits Purse 
               
               
                   
                 8042 
                 Optometrists 
                 Benefits Purse 
               
               
                   
                 7832 
                 Motion Picture Theaters 
                 Cash Purse 
               
               
                   
                 7922 
                 Theatrical Ticket Agencies 
                 Cash Purse 
               
               
                   
                   
               
            
           
         
       
     
     In some aspects, the methods of the present solutions implements a combination of steps in an innovative, non-conventional or non-routine manner. In some aspects, the method of the present solution combines the steps of  FIG.  6    in an innovative, non-conventional and/or non-routine combination to implement the improved functionality, performance and operation of the present solution. In some aspects, the method  600  of the present solution combines the steps of  FIG.  6    in in an innovative, non-conventional or non-routine manner to more efficiently and effectively use computing and networking resources. In some aspects, the method  600  of the present solution provides innovative, non-conventional or non-routine ordered combination of steps. 
     D. Electronic Transaction Enforcement Portal System 
     The systems and methods of the present solution are directed to the technical problems and challenges of implementing the functionality of resource allocation in electronic transaction portal based technology and platforms. Existing resource allocation based technologies and platforms do not effectively and efficiently make use of the computing and network resources deployed for electronic transaction portals. Without implementing such functionality, existing electronic transaction portal based technologies and platforms have the problems of excessive server-client requests and responses, processing delays, increase bandwidth usage, or erroneous resource allocations. 
     The systems and methods of the present solution are directed to the improvement of the performance and operation of the electronic transaction portal based technology and platform and computing and networking resource used by such electronic transaction portals. In some aspects, the present solution improves and enhances the implemented functionality of the electronic transaction portal based technology and platform implemented on, integrated with and inherently tied to the processor, memory, network and computing resources of one or more computing devices. In some aspects, the present solution more effectively performs the functionality of the electronic transaction portal technology and platform thereby making and causing more effective use of the computing and networking resources to achieve the improved functionality of the present solution. The same computing and network resources used by such electronic transaction portal technology and platform will provide increased and improved functionality with implementation of the present solution. 
     In some aspects, the present solution more efficiently uses the computing and networking resources to implement the improved functionality of the electronic transaction based technology and platform. For example, systems and methods of the present solution are directed to managing or conducting electronic transactions using an electronic transaction portal. Systems and methods of the present solution can manage the electronic transaction portal to prevent single electronic benefits account transactions from exceeding threshold limits for contributions. Systems and methods of the present solution can use a multi-purse transaction system that maintains an electronic account having multiple purses. An electronic account can be maintained by a server and include a database in memory or a storage device. The electronic account can include sub structures or fields. The electronic account can include multiple purses that are configured with one or more rules, parameters, restrictions, or policies. For example, the electronic account can include a first purse that is configured as a benefits a purse. A purse configured for benefits can refer to a purse that is configured for transactions made using a tax benefit account such as a flexible spending account (“FSA”), Dependent Care Account (“DCA”), Transport Account (e.g., for parking or monthly passes). In some embodiments, the FSA, DCA, and Transport Account can be further separated into sub-purses within the benefits purse of the electronic account. A flexible spending account, or flexible spending arrangement, can refer to a tax-advantaged financial account that can be set up through a cafeteria plan of an employer and used to set aside a portion of earnings to pay for qualified expenses as established in the cafeteria plan. Types of FSA can include medical expense FSA, health FSA, health savings account (HSA), health reimbursement account (HRA), health reimbursement plan (HRP), etc. Qualified expenses can include, for example, medical expenses, dependent care, dental expenses, vision expenses, parking, monthly passes, etc. An FSA can be tax-advantaged because funds deducted from an employee&#39;s account and transferred to the FSA is not subject to payroll taxes, resulting in payroll tax savings. 
     A client device can initiate an electronic transaction, responsive to receiving user input via a user interface, to transfer funds to an electronic benefits account, or an entity such as server of an employer, an insurance administrator, or a financial institution can manually, periodically, and/or automatically make the electronic transaction. The transaction can be associated with information such as an FSA account identifier, time stamp, entity identifier, and transaction amount. This information can be provided in real-time to a transaction repository. The electronic transaction portal can receive electronic transaction requests from a plurality of electronic client devices corresponding to a heterogeneous plurality of electronic funding sources. The electronic funding sources can include an automatic clearinghouse (“ACH”), individual checking, bill pay, and savings accounts, credit card accounts, employer payroll (e.g., for funding Roth IRA, cafeteria, FSA, etc.), and other electronic funding sources. The heterogeneous electronic funding sources can be provided custom electronic benefits account transaction application programming interfaces to facilitate enforcement of a single transaction request from one of the electronic funding sources. The electronic transaction portal can transfer funds, such as when the electronic transaction request is generated based on transaction types such as point of sale transactions, manual transactions, and deposit transactions. The electronic transaction portal can maintain daily net general ledger files using enforcement rules, and transmit instructions to an electronic entity (e.g., a server) of the relevant financial institution that causes the financial institution server to transfer funds internally. 
     When multiple heterogeneous electronic funding sources initiate electronic funding transactions, the electronic funding transactions might all post to the electronic benefits account, even if the electronic funding transactions exceed a threshold limit for the electronic benefits account, requiring a participant associated with the electronic benefits account to withdraw excess contributions or later engage in complex tax management procedures. The present solution is configured to apply enforcement rules executed by a transaction enforcement portal system, on a single transaction basis, in order to prevent the contribution threshold limit from being exceeded even when multiple transactions are received from a plurality of heterogeneous electronic funding sources. The present solution provides the transaction enforcement portal system that receives indications of electronic transaction requests and executes enforcement rules based on the electronic transaction requests in order to deny transaction requests that would otherwise cause the threshold limit to be exceeded. 
     For example, if a participant initiates a single electronic transaction request to transfer funds to a flexible spending account (e.g., an HSA) from an electronic checking account, the present solution can receive the electronic transaction request, and parse the request to identify a transaction amount and the flexible spending account. The present solution can determine whether authorizing the transaction would cause a threshold limit (e.g., an IRS-established threshold limit) for contributions to the flexible spending account to be exceeded, before the transaction is posted to the flexible spending account. The present solution can prevent threshold limits to be exceeded in real-time, overcoming difficulties caused when the participant is not aware that the threshold limit is exceeded until the transaction is posted, often several days after the transaction is requested, at which point complex reimbursement procedures may be required to avoid tax penalties. 
     Referring now to  FIG.  7   , a block diagram depicting an embodiment of a system  700  comprising a Transaction Enforcement Portal System (TEPS) is shown. In brief overview, the system  700  includes a transaction enforcement portal system  708  (“TEPS”) that can receive and/or transmit data via a network  104  with clients  102   a - n  and POS terminals  202   a - n . The system  700  can include or interact with one or more clients  102   a - n  (or client device  102 ), and one or more point-of-sale (POS) terminals  202   a - n  (or POS terminal  202 ). The TEPS  708  can include a communications interface  710  that is configured with one or more communications ports, application programming interfaces, network protocols (e.g., TCP/IP), authentication protocols, or security protocols (e.g., SSL). The TEPS  708  can include an enforcement engine  712  that is configured to prevent an electronic transaction from exceeding an IRS threshold limit for an electronic benefits account. The TEPS  708  can include one or more databases or data structures that store information to facilitate the systems and methods of the present solution, such as database  714  and database  716 . The database  714  (or electronic benefits account) can include an electronic account maintained or configured on the TEPS  708  that includes one or more purses, such as a benefits purse and a cash purse. The database  714  can include a transaction queue indicating real-time electronic transactions of the electronic benefits account, and a code map mapping electronic transactions to a point in time, such as a year. The database  716  can include one or more enforcement rules, profiles, or alerts. 
     The TEPS  708 , communications interface  710 , and enforcement engine  712  can each include one or more processing units or other logic devices such as programmable logic array engines, modules, or circuitry designed and constructed to facilitate managing security on a network infrastructure. The TEPS  708  can include the components  100  shown in  FIG.  1 C  or  FIG.  1 D , or be configured to operate as a service in cloud  108 . The TEPS  708  can include or interact with one or more servers  106   a - n  and clients  102   a - n , and can interact with one or more heterogeneous electronic funding sources  702   a - n  via the clients  102   a - n . Examples of heterogeneous electronic funding sources  702   a - n  can include an ACH, an electronic checking account, an electronic bill pay account, an electronic savings account, an electronic credit card account, or an electronic employer payroll account. In some implementations, two electronic funding sources can be heterogeneous to one another if they are maintained by two separate entities. In some implementations, two electronic funding sources can be heterogeneous to one another if they are administered or managed by two separate business entities. In some implementations, two electronic funding sources can be heterogeneous to one another if they use different data communication channels, transaction types, or payment processing techniques. For example, a wire transfer from a first financial institution and a wire transfer from a second financial institution may be heterogeneous to each other. In another example, a wire transfer from a first financial institution and a deposit from initiated by a mobile application of a user may be heterogeneous to one another. 
     In some embodiments, the TEPS  708  can employ a multitier architecture such as a client-server architecture in which presentation, application processing, and data management functions are logically or physically separated. The presentation tier, or front-end, can include the communications interface  710  that serves static content or dynamic content to be rendered by the client  102  (e.g., by a web browser executing on client  102 ). The presentation tier or web server can interact or communicate with the application tier to obtain data to provide to the client  102  or POS terminals  202   a - n . The application tier can include the transaction engine  414  that controls the system&#39;s functionality and performs additional processing or analysis on data. The application tier can interact with the data tier to obtain the transaction data. The data tier can include data persistence mechanisms (database servers, file shares, etc.) and the data access layer that encapsulates the persistence mechanisms and exposes the data. The data tier can include databases  714  and  716 . The data tier can include an application programming interface (API) to the application tier. The databases  714  and  716  can include stored procedures (e.g., SQL statements) that perform tasks with respect the stored data. 
     In further detail, and in some embodiments, the TEPS  708  includes a communications interface  710 . In some aspects, the communications interface  710  comprises an innovative, non-conventional or non-routine implementation. In some aspects, the communications interface  710  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, the communications interface  710  is implemented to make or cause more effective and efficient use of computing and networking resources. For example, the communications interface  710  can cause more effective and efficient use of computing and network resources by reducing the number of processing cycles, memory or network bandwidth used to receive requests to adjudicate a single claim. The communications interface  710  can provide an improved adjudication of a single claim by integrating or interfacing with an enforcement engine  712 , database  714 , database  716 , claims processor  220 , or POS terminals  202   a - n , or clients  102   a - n  to receive requests to adjudicate a single claim. 
     The communications interface  710  can execute on one or more processors of a server. The communications interface  710  can include one or more communications ports and be configured with one or more network protocols. Communications ports can include, e.g., network ports, Ethernet ports, WAN ports, I/O ports, or software ports. The communication port can be configured with a network protocol such as Transport Layer Protocols such as TCP/IP or UDP that are configured to receive and process data packets received via a computer network. The port can include or be associated with an IP address of a host and a protocol type of the communication. 
     The communications interface  710  can receive data packets. The data packets can be generated by a client device  102   a . The communications interface  710  can receive data packets generated by the client device  102   a  responsive to an electronic transaction request. The data packets can include header information and payload information. Multiple data packets can be strung together in a sequence. The header information can refer to TCP/IP headers that include fields such as source port, destination port, sequence number, acknowledgment number, window size, etc. The payload information of the data packet can include information related to the transaction, merchant, or customer. The TEPS  708  can receive the data packet with header information and payload information and process the packets to obtain information for further processing. The payload can include data identifying a transaction destination, a transaction code, a transaction amount, and an identifier identifying the electronic funding source. 
     The transaction request can be configured as one or more data packets carrying data including a transaction destination, a transaction code, a transaction amount, and an identifier identifying the electronic funding source. The transaction destination can include an indication of an electronic benefits account to serve as the destination for transacted funds. The transaction code can include an indication of a date, such as an indication of a year. The transaction amount can include an amount of funds to be transferred as requested, according to user input received at the client device  102   a , from the electronic funding source to an electronic benefits account. The identifier can include a code or label corresponding to the electronic funding source. 
     The data packets (e.g., payload of the data packets) can further identify an electronic benefits account maintained and configured on the server. The electronic benefits account can be maintained and configured in a database  714 . The electronic benefits account can correspond to a user and have a unique identifier. The unique identifier can include numbers, letters, characters, symbols, etc. The electronic account can be associated with the user making the transaction request at the client device  102   a.    
     In some embodiments, the transaction request is configured with authentication or security credentials such as a security certificate or security token. The security credential can be associated with a user, client  102   a , or electronic funding source  702   a . The TEPS  708  can be configured to extract the security credential from the transaction request, and authenticate the transaction request by comparing the security credential against a known or verified security credential. For example, the profiles (e.g., user profiles, electronic funding source profiles, electronic benefits account profiles) stored in the database  716  can include known or verified security credentials for comparison with the security credential of the transaction request. In some embodiments, the TEPS  708  receives the transaction request via the communications interface  710 , extracts a security credential from the transaction request, analyzes the extracted security credential to identify an entity such as a user, electronic funding source  702   a , and/or client  102   a , queries the database  716  for a verified security credential stored with a profile corresponding to the identified entity, and authenticates the request based on the extracted security credential matching the verified security credential. 
     The communications interface  710  can provide, to the plurality of client devices  102   a - n  corresponding to the plurality of heterogeneous electronic funding sources  702   a - n , an electronic benefits account application programming interface (“API”) configured to receive transaction requests from the plurality of heterogeneous electronic funding sources  702   a - n  via the client devices  102   a - n . The client  102   a  can establish an electronic connection to the TEPS  708  responsive to receiving input via a user interface of the client  102   a . The TEPS  708  can receive, via the electronic connection, data packets including an indication of an operating system of the client device  102   a  and an indication of existing applications installed on the client device  102   a . The TEPS  708  can parse the data packets to use the indication of the operation system and/or the indication of existing applications installed on the client device  102 , perform a lookup in a database (e.g., database  716 ) to identify an appropriate electronic benefits account API for the client device  102   a , and transmit the appropriate electronic benefits account API to the client device  102   a  via the communications interface  710  in response to determining that the client device  102   a  requires the electronic benefits account API in order for the TEPS  708  to receive an electronic transaction request from the electronic funding source  702   a . The electronic benefits account API can be configured to match a specific electronic funding source  702   a . For example, the TEPS  708  can be configured to query the client device  102  for an indication of the specific electronic funding source  702   a , receive the indication of the specific electronic funding source  702   a  responsive to the query, compare the indication to a list of electronic funding sources stored in a database (e.g., in electronic funding source profiles in database  716 ), and retrieve an appropriate electronic benefits account API responsive to the comparison for providing to the client device  102   a.    
     The communications interface  710  can receive, via the electronic benefits account transaction API, from a first client device  102   a  of the plurality of client devices  102   a - n  corresponding to the plurality of heterogeneous electronic funding sources  702   a - n , a first one or more data packets including the electronic transaction request to initiate the single electronic benefits account transaction to fund an electronic benefits account. The electronic transaction request can be generated responsive to the first client device  102   a  receiving user input via a user interface, the user input configured to indicate a request that funds be transferred from a first electronic funding source  702   a  to the electronic benefits account to be funded. The one or more data packets can include the request identifying a transaction destination, a transaction code, a transaction amount, and an identifier identifying the first electronic funding source  702   a.    
     In some embodiments, the TEPS  708  includes an enforcement engine  712 . The enforcement engine  712  can execute on one or more processors of a server. In some aspects, the enforcement engine  712  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, the enforcement engine  712  is implemented to make or cause more effective and efficient use of computing and networking resources. For example, the enforcement engine  712  can cause more effective and efficient use of computing and network resources by reducing the number of processing cycles, memory or network bandwidth used to determine and map transaction codes. The enforcement engine  712  can provide an improved determination and mapping of transaction codes by integrating or interfacing with the communication interface  710 , database  714 , database  716 , claims processor  220 , POS terminals  202   a - n , or clients  102   a - n  to determine and map transaction codes. The enforcement engine  712  can receive, retrieve, or otherwise obtain or access some or all of the data carried by the data packets. The enforcement engine  712  can receive, retrieve, or otherwise obtain or access electronic transaction queues, code maps, enforcement rules, and profiles stored in databases  714 ,  716 . 
     In some embodiments, the enforcement engine  712  determines that the transaction code of the transaction request maps to one of a current year or a previous year. The enforcement engine  712  can receive the first one or more data packets including the request to initiate the single electronic benefits account transaction. The enforcement engine  712  can parse the first one or more data packets to extract the transaction code. 
     The enforcement engine  712  can perform a lookup in the code map stored in the database  714  to retrieve a list or other data structure mapping transaction codes to a time reference, such as a year, a current year, a previous year, etc. For example, the database  714  can include a hash table or a hash map that includes an array of data records mapping transaction codes to time references. The enforcement engine  712  can be configured with a hash function that can compute an index into the array of data records from which a value can be determined. For example, the enforcement engine  712  can input into the hash function the transaction codes and determine, via the hash function, an index value. The enforcement engine  712  can use the index value to retrieve, from the hash table or hash map, a data record that includes a time reference. Thus, the enforcement engine  712  can perform a lookup into a hash table using a hash function in order to map the transaction code to a time reference. 
     In some embodiments, the code map includes a list of transaction codes associated with a current year, a list of transaction codes associated with a previous year, and a list of transaction codes associated with other years. In some embodiments, the transaction code itself is a time reference such as a date or year, and the code map includes a value for a current year, and a value for a previous year. The enforcement engine  712  can then compare the transaction code to the retrieved code map to determine whether the transaction code corresponds to one of a current year or a previous year. 
     In some embodiments, the enforcement engine  712  can identify using a profile of the electronic benefits account stored in the database  716  that the first electronic funding source  702   a  enforces electronic benefits account limits. For example, the enforcement engine  712  can parse the electronic transaction request to extract the identifier of the first electronic funding source  702   a , perform a lookup in the database  716  to identify a profile corresponding to the first electronic funding source  702   a , and retrieve from the profile an indication of whether the first electronic funding source  702   a  enforces electronic benefits account limits. The enforcement engine  712  can determine, responsive to identifying that the first electronic funding source  702   a  enforces electronic benefits account limits, that the transaction code maps to one of the current year or the previous year. 
     In some embodiments, the enforcement engine  712  can determine an enforcement rule based on the single electronic benefits account transaction request. For example, the enforcement engine  712  can parse the electronic transaction request to extract the transaction destination and/or identifier of the first electronic funding source  702   a . The enforcement engine  712  can perform a lookup in the database  714  or the database  716  to identify the electronic benefits account associated with the transaction destination, and perform a lookup in the database  716  to identify an enforcement rule associated with the electronic benefits account. The enforcement engine can perform a lookup in the database  714  or the database  716  (e.g., in a profile database) using the identifier of the first electronic funding source  702   a  to retrieve an indicator of an enforcement rule, and perform a lookup in the database  716  to identify the enforcement rule associated with the first electronic funding source  702   a.    
     The enforcement engine  712  can identify the threshold limit based on the enforcement rule. The enforcement rules maintained in the database  716  can include a map associating electronic benefits accounts with threshold limits. The enforcement engine  712  can use or apply an enforcement rule that includes one or more techniques, algorithms, heuristics, or procedures. The enforcement rule can include decision points and utilize parameters or criteria. The enforcement rule can be based on criteria or rules that are established by an administrator of the TEPS  708 , the heterogeneous electronic funding sources  702   a - n , electronic employer payroll accounts, insurance entities, or another entity. The enforcement rule can facilitate determining a threshold limit to be applied to the electronic transactions. 
     For example, the map can associate electronic benefits accounts that are subject to IRS threshold limits with IRS threshold limits. The enforcement rule can include the rule: if transaction code maps to current year, then apply current year threshold limit; else if transaction code maps to previous year, then apply previous year threshold limit; else do not apply limit. The enforcement rule can include the rule: if an age value stored in a user profile for the user associated with the electronics benefits account is less than fifty-five, then the IRS threshold limit includes a family threshold limit value; else (if the age value is greater than or equal to fifty-five) the IRS threshold limit includes a family threshold limit value and a catchup value (e.g., a catchup value allowing for rollover of unused contribution capacity from previous years). The enforcement rule can include the rule: if a participant household type stored in a user profile for the user associated with the electronic benefits account corresponds to “single,” then the apply the IRS threshold limit for “single” households; if the participant household type corresponds to “family,” then apply the IRS threshold limit for “family” households. 
     In some embodiments, the enforcement rule can include multiple criteria. For example, the enforcement rule can include: if electronic funding source corresponds to (or equals or maps to or is) employer payroll account or individual checking account or insurance account, then apply IRS threshold limit. In some embodiments, the enforcement rule can be a negative enforcement rule. For example, the enforcement rule can include: if electronic funding source does correspond to employer payroll account or individual checking account or insurance account, then do not apply IRS threshold limit. In some embodiments, the enforcement rule can include an action to take when the enforcement rule is not satisfied. For example, if the electronic funding source corresponds to employer payroll account or individual checking account or insurance account, then apply IRS threshold limit; if not, then post transaction. In some embodiments, a single enforcement can include multiple enforcement rules. In some embodiments, the enforcement engine  712  can use process multiple enforcement rules before identifying an enforcement rule that is satisfied. 
     In some embodiments, the enforcement engine  712  can be configured to apply the electronic transaction to one of the current year or the previous year depending on the total contribution amount for each year. For example, the enforcement rule can include determining a virtual transaction balance for each of the current year and the previous year, comparing the virtual transaction balance for each of the current year and the previous year, and selecting one of the current year or the previous year for receiving the transaction amount. The enforcement rule can include: if the virtual transaction balance for both the current year and the previous year is less than a threshold limit, then apply the transaction amount to the current year; else if the virtual transaction amount for one of the current year or the previous year is less than a threshold limit, then apply the transaction amount to the one of the current year or the previous year; else do not apply the transaction amount. In some embodiments, the enforcement rule can include applying a partial amount of the transaction amount that will not exceed the threshold limit, such as a partial amount that will cause the virtual transaction balance to equal the threshold limit, or a partial amount that will cause the virtual transaction balance to equal a fraction of the threshold limit (e.g., 50%, 60%, 70%, 80%, 90%, 95%, 99%, etc. of the threshold limit). 
     In some embodiments, the enforcement engine  712  can parse or perform a lookup in the electronic transaction queue stored in the database  714  to retrieve and identify an in-process transaction amount and a reportable contribution amount. The in-process transaction amount can include a plurality of transactions request amounts for funding the single electronic benefits account that have been received (e.g., received by the TEPS  708 ) but not yet posted. For example, the in-process transaction amount can include a sum of multiple transaction requests, such as when a client device  102   a  receives user input indicating a request for funds to be transferred from an individual checking account in a first electronic transaction request, and an employer payroll server generates a second transaction request. The in-process transaction amount can include pending transactions that are future dated and not yet sent for processing, and can include processing transactions that have been sent for processing but have not yet posted. The reportable contribution amount can include transactions that have posted to the total amount of the electronic benefits account and thus will count against a threshold limit of the electronic benefits account (e.g., posted transactions that have updated an accumulator that groups or otherwise organizes transactions). 
     In some embodiments, the enforcement engine  712  generates a value by combining the transaction amount, the in-process transaction amount, and the reportable contribution amount identified from the electronic transaction queue of the electronic benefits account maintained in the database  714 . The value can indicate a virtual transaction balance, such as a balance of the electronic benefits account that would occur if all of the transactions of the transaction amount, the in-process transaction amount, and the reportable contribution amount were posted to the electronic benefits account. The enforcement engine  712  can generate the value by summing the transaction amount, the in-process transaction amount, and the reportable contribution amount. The enforcement engine  712  can store the value indicating the virtual transaction balance in a database, such as database  714  maintaining the electronic benefits account, or database  716  maintaining a profile associated with the electronic benefits account. For example, the enforcement engine  712  can generate the value, perform a lookup in the database  716  to identify a profile associated with the electronic benefits account, and store the virtual transaction balance in the profile. 
     In some embodiments, the enforcement engine  712  can compare the value with a threshold limit for the one of the current year or the previous year mapped to the transaction code to determine that the value exceeds the threshold limit. For example, the enforcement engine  712  can perform a lookup in the database  716  to identify an enforcement rule that includes threshold limits for the one of the current year or the previous year, retrieve the threshold limit for the one of the current year or the previous year mapped to the transaction code, and compare the value to the threshold limit. The enforcement engine  712  can determine that the value exceeds the threshold limit based on the value being greater than the threshold limit. 
     In some embodiments, the enforcement engine  712  can select the threshold limit based on a predetermined threshold limit configured for the first electronic funding source  702   a . For example, the enforcement engine  712  can parse the electronic transaction request to extract the identifier of the first electronic funding source  702   a , perform a lookup in a profile database maintained in the database  716  to retrieve a profile of the first electronic funding source  702   a , and perform a lookup in the profile to identify the predetermined threshold limit. 
     Enforcement rules and threshold limits can be received from entities including a claims processor  220 , a server of a remote entity such as the electronic funding sources  702   a - n , and/or a server of an employer, insurance administrator, or financial institution. In some cases, the client  102  can provide the enforcement rule or threshold limit. In some cases, the TEPS  708  can access a central data repository maintained by a third-party server such as an IRS server that stores threshold limits. For example, an employer contributing to the electronic benefits account can establish an enforcement rule and maintain it on a server. The enforcement engine  712  can receive an indication of the electronic benefits account, perform a lookup in the enforcement rules maintained in the database  716 , and responsive to determining that the database  716  does not include an appropriate enforcement rule for the electronic benefits account, the enforcement engine  712  can transmit a request for an enforcement rule to the server of the employer, causing the server of the employer to transmit the appropriate enforcement rule to the TEPS  708 . 
     In some embodiments, the enforcement engine  712  can receive the request to initiate the single electronic benefits account transaction from a remote device. The remote device can initiate the request. The remote device that initiates the request can be remote to the first client device  102   a  and configured with authentication credentials to access the first client device  102   a . For example, the remote device can be a portable electronic device, and the first client device  102   a  can be a server configured to communicate with the portable electronic device and the TEPS  708 . The remote device can include an electronic benefits account transaction API configured to receive a single transaction request from an electronic funding source  702   a . A user of the remote device can interact with a user interface of the remote device to initiate the single transaction request. The remote device can initiate the single transaction request responsive to receiving user input indicating a request to initiate the single transaction request via a user interface. The remote device can transmit the single transaction request as one or more data packets carrying the single transaction request and the authentication credentials. The first client device  102   a  can receive the one or more data packets, extract the authentication credentials, and compare the authentication credentials to corresponding authentication credentials stored on the first client device  102   a  (e.g., authentication credentials stored with an electronic benefits account transaction API) in order to determine whether to authenticate the single transaction request. Responsive to determining to authenticate the single transaction request, the first client device  102   a  can transmit the single transaction request to the TEPS  708 . In some embodiments, the stored authentication credentials are maintained by the TEPS  708 , and the electronic benefits account transaction API of the first client device  102   a  is configured to receive the single transaction request from the remote device, extract the authentication credentials and transmit only the authentication credentials to the TEPS  708 ; the TEPS  708  can receive the authentication credentials, compare the authentication credentials to the stored authentication credentials (e.g., by performing a lookup in the database  714  or the database  716  maintaining authentication credentials), and responsive to determining that the extracted authentication credentials match the stored authentication credentials, generate an acknowledgement to transmit to the client device  102   a  causing the client device  102   a  to transmit the single transaction request to the TEPS  708 . 
     In some embodiments, the enforcement engine  712  can apply a second enforcement rule directed to additional factors after using a first enforcement rule. The enforcement engine  712  can select the second enforcement rule responsive to or based on the first enforcement rule. The first enforcement rule can include a map of a transaction code to one of the current year or the previous year, and the second enforcement rule can be a threshold limit for the one of the current year or the previous year. 
     In some embodiments, the enforcement engine  712  can receive an indication from a claims processor  220  external to the TEPS  708  via network  104 . In some embodiments, the TEPS  708  or the enforcement engine  712  is configured with the claims processor  220  or configured to interface with the claims processor  220  via communications interface  710 . The claims processor  220  can process an electronic transaction request to determine whether applying an electronic transaction to the electronic benefits account would exceed a threshold limit for the electronic benefits account. The claims processor  220  can be configured to use one or more enforcement rules to process the electronic transaction request. The enforcement rules can be based on a type of insurance coverage associated with a user of the electronic benefits account. The claims processor  220  can automatically receive the electronic transaction request responsive to the client device  102   a  generating the electronic transaction request responsive to user input, or responsive to a server of an employer or insurance administrator generating the electronic transaction request. 
     The TEPS  708  can receive information or instructions from the enforcement engine  712  regarding an electronic transaction, and conduct the electronic transaction. The TEPS  708  can obtain electronic funding source information and/or electronic benefits account information from the databases  714 ,  716  to perform the transaction. The transaction can include electronically transferring funds from the electronic funding source  702   a  to the electronic benefits account. The transaction can include memo-posting or hard-posting the electronic transaction. For example, the TEPS  708  can receive instructions to post the electronic transaction, and responsive to receiving the instructions, the TEPS  708  performs a lookup in a profile of the electronic benefits account maintained in the database  716  to identify a financial institution associated with the electronic benefits account in order to transmit instructions to the financial institution to post the transaction, including the value. In some cases, the TEPS  708  can facilitate a transfer of funds between an electronic account of a claims processor  220  and the electronic benefits account maintained in the database  714 . The TEPS  708  can receive account identifiers, transaction amounts, credentials, authentication information, etc. The TEPS  708  can conduct the transaction via communications interface  710 , thereby using the network protocols, security protocols and other components or interfaces provided by the communications interface  710 . 
     In some embodiments, the TEPS  708  (e.g., via communication interface  710 ), receives a request for account information from a client device  102   a . The request for information can include information about a balance of the electronic benefits account (e.g., an in-process transaction amount, a reportable contribution amount, a virtual transaction balance), enforcement rules, or transaction histories. The request can further include authentication information or credentials associated with the request. The authentication information can include network security credentials, such as security certificates or tokens. The authentication information can further include a username, password, two-tier authentication information (e.g., date of birth, cell phone number, verification code sent via text message to cell phone number in profile associated with electronic account). The request can be from a client device such as a smartphone. The request can be sent using a text messaging protocol such as SMS. The TEPS  708  can authenticate a request sent via SMS based on the cell phone number of the device sending the SMS request, and matching the cell phone number with corresponding number stored in a profile in the database  716  for the electronic benefits account. 
     Responsive to authenticating or otherwise approving the request, the TEPS  708  can access a data record in the database  714  for the electronic benefits account to generate a report with the requested information, or generate a standard report, or generate another preconfigured report. The report can identify the account holder information and balances associated with the electronic benefits account. The report can further identify a transaction history for the electronic benefits account. The report can further identify or indicate if the electronic benefits account has reached or exceeded a threshold limit. The report can further include a forecast based on current/previous transaction history that indicates if and when the threshold limit for a time interval might be reached or exceeded. 
     In some embodiments, the enforcement engine  712  can select an alert format configured for an interface corresponding the first electronic funding source  702   a . The enforcement engine  712  can generate an alert in the alert format that includes instructions to terminate the single electronic benefits account transaction initiated by the request to prevent exceeding the threshold limit established for the electronic benefits account. The enforcement engine  712  can perform a lookup in the database  716  maintaining alert formats for alerts based on the identifier of the first electronic funding source  702   a  in order to identify and retrieve the alert format. The alert format can include a variety of fields configured to be read by the first electronic funding source  702   a . For example, the alert format can includes fields directed to an indication of an approval or denial of the single electronic benefits account transaction request; approval of a partial amount of the transaction amount, an indication of the electronic benefits account, an indication of a user of the electronic benefits account, and an indication of a current or projected balance of the electronic benefits account. The alert format can include fields similar to or directed to information provided by the TEPS  708  in a report responsive to a request for account information from a client device  102   a . The alert format can include authentication credentials configured to be read by the first electronic funding source  702   a  to authenticate the alert. The alert format can include a field including instructions for terminating or authorizing the request to initiate the single electronic benefits account transaction. 
     In some embodiments, the enforcement engine  712  can transmit, via the network  104  to the first client device  102   a , one or more packets carrying data in the alert format indicating a denial of the single electronic benefits account transaction request, responsive to the comparison and the transaction code mapping to the one of the current year or the previous year, the one or more packets configured to indicate to the first client device  102   a  termination of the single electronic benefits account transaction initiated by the request to prevent exceeding the threshold limit established for the electronic benefits account. For example, the enforcement engine  712  can retrieve the alert format, generate the one or more packets carrying the information organized in the selected alert format, and cause the communications interface  710  to transmit the one or more packets to the first client device  102   a . The enforcement engine  712  can retrieve the information required by the alert format from the electronic transaction request, the database  714 , and/or the database  716  to generate the one or more packets of the alert. For example, the enforcement engine can retrieve the identifier of the first electronic funding source  702   a  from the electronic transaction request, the indication of the denial of the electronic transaction request from the database  714  maintaining the electronic benefits account, and the authentication credentials from the profile of the first electronic funding source  702   a  maintained in the database  716 , in order to generate the alert as one or more packets carrying this information to be transmitted by the communications interface  710 . 
     The one or more packets can include a reason code or error code indicating a reason or error associated with the denial (or approval, if applicable) of the electronic transaction request. The reason code can be generated by the enforcement engine  712  responsive to the enforcement engine  712  applying an enforcement rule for identifying a threshold limit. The reason code can indicate that the transaction amount of the single electronic transaction request would exceed the threshold limit applied to the electronic benefits account. The reason code can indicate that the transaction amount would exceed the combined IRS family and catchup threshold limit that was applied because the age of the participant was greater than or equal to fifty-five. The reason code can indicate that the electronic benefits account does not segregate threshold limits into coverage tiers (e.g., coverage tiers based on age), and thus the threshold limit used was the combined IRS family and catchup threshold limit. The reason code can indicate that the transaction amount would exceed the IRS family threshold limit that was applied because the age of the participant was less than fifty-five and the household type was “family.” The reason code can indicate that the transaction amount would exceed the IRS single threshold limit that was applied because the age of the participant was less than fifty-five and the household type was “single.” 
     The one or more packets can include instructions that cause the electronic benefits account transaction API of the client device  102   a  to reroute the one or more packets to the first electronic funding source  702   a  in order to cause the first electronic funding source  702   a  to terminate the single electronic benefits account transaction. For example, the electronic benefits account transaction API can receive the one or more packets, extract the indication of the denial of the electronic transaction request and the identifier of the first electronic funding source  702   a , and transmit the one or more packets to the first electronic funding source  702   a . The one or more packets can include instructions causing the electronic benefits account transaction API to generate instructions causing first electronic funding source  702   a  to terminate the single electronic benefits account transaction. For example, the electronic benefits account transaction API can receive the one or more packets, extract the indication of the denial of the electronic transaction request and the identifier of the first electronic funding source  702   a , and generate instructions to transmit to the first electronic funding source  702   a  to cause the first electronic funding source  702   a  to terminate the single electronic benefits account transaction. 
     In some embodiments, the enforcement engine  712  can transmit the alert to the first client device  102   a  to cause the first client device  102   a  to terminate the transaction, when the transaction was initiated by the remote device remote to the first client device  102   a . For example, a portable electronic device may have initiated the electronic transaction request, responsive to user input, and transmitted the request to the first client device  102   a  which manages the electronic funding source  702   a ; the enforcement engine  712  can identify this chain of command by parsing the electronic transaction request in order to transmit the alert to the first client device  102   a  with instructions causing the first client device  102   a  to terminate the transaction. 
     In some embodiments, the enforcement engine  712  can establish a bidirectional communication channel with the first client device  102   a . The enforcement engine  712  can transfer requests and instructions to terminate transactions. For example, the enforcement engine  712  can transmit a request to establish a bidirectional communication channel with the first client device  102   a  to the electronic benefits account transaction API provided to the first client device  102   a . The enforcement engine  712  can also transmit the bidirectional communication channel request when providing the electronic benefits account transaction API. The request can be configured to cause the client device  102   a  to establish a communication channel with the TEPS  708  and the enforcement engine  712  via the communications interface  710  automatically or responsive to approval received as user input at a user interface, or approval granted by another application of the client device  102   a . The TEPS  708  can then receive the responsive communication from the client device  102   a , and retrieve a communication protocol from the database  714  or the database  716  associated with the electronic benefits account transaction API of the client device  102   a  in order to establish the bidirectional communication channel based on the retrieved communication protocol. For example, the bidirectional communication channel can be based on an Internet-based communication channel in which data packets can be regularly transmitted between the client device  102   a  and the TEPS  708 . 
     The communication protocol for establishing the bidirectional communication channel can include authenticating communication between the client device  102   a  and the TEPS  708 . For example, the TEPS  708  can retrieve the identifier of the client device  102   a , perform a lookup in the database  716  to identify authentication credentials associated with the client device  102   a , transmit the authentication credentials to the client device  102   a , and responsive to the client device  102   a  authorizing communication based on the authentication credentials, receive a challenge from the client device  102   a , extract additional authentication credentials from the challenge, perform a lookup in the database  716  to compare the additional authentication credentials to stored authentication credentials, and authorize the bidirectional communication based on the additional authentication credentials matching the stored authentication credentials. 
     In some embodiments, the enforcement engine  712  can transmit, via the network  104  to the first client device  102   a , the response packets indicating the denial of the single electronic benefits account transaction request within a predetermined time interval from receiving the single electronic benefits account transaction request. The predetermined time interval can be a time period after an action, e.g. 10 minutes, 5 minutes, 1 minute, 30 seconds. The action can include receiving the electronic transaction request, posting the transaction or denying the transaction, and/or generating the alert including instructions to terminate the single electronic benefits account transaction. The pre-determine time interval can be set in a configuration file or profile maintained by the TEPS  708  in the database  714  or the database  716 , the configuration file or profile corresponding to the electronic benefits account. The pre-determined time interval can be set by an entity remote from the TEPS  708 . For example, the TEPS  708  can transmit a time interval request to a remote server of an insurance administrator, an employer, or a financial institution. The time interval request can cause the remote server to transmit the configuration file or profile setting the pre-determined time interval to the TEPS  708 . The enforcement engine  712  can process the configuration file or profile to extract the pre-determined time interval in order to transmit the notification within the pre-determined time interval. 
     In some embodiments, responsive to the action occurring that initiates the pre-determined time interval, the enforcement engine  712  can generate a placeholder notification to be transmitted to the first client device  102   a  independent of the status of the electronic transaction request. For example, the placeholder notification can indicate that enforcement of the electronic transaction request has been initiated. The placeholder notification can indicate that further information is required to complete the enforcement of the electronic transaction request. The enforcement engine  712  can transmit the placeholder notification prior to expiry of the pre-determined time interval via the communications interface  210  to provide real-time communication of the adjudication process. 
     In some embodiments, the pre-determined time interval can be based on the type of electronic benefits account, the type of electronic funding source, or an expected time required to perform transactions with the electronic benefits account or the electronic funding source. For example, if the electronic benefits account or the electronic funding source can perform transactions using wire transfer, than the pre-determined time interval can be approximately ten seconds, thirty seconds, one minute, etc. If the electronic benefits account or the electronic funding source can perform transactions by direct deposit, then the pre-determined time interval can be a time associated with electronic communication between the TEPS  708  and the electronic funding source, such as ten minutes. The pre-determined time interval can be based on a time required to transfer funds from an electronic bank account associated with an insurance administrator or with an employer to the electronic benefits account. The pre-determined time interval can be based on a time required for an indication of the enforcement of the electronic transaction request to be received at a remote server in order to authorize or deny the funds for being transferred to the electronic benefits account. 
     In some embodiments, the enforcement engine  712  can determine that the electronic funding source  702   a  corresponds to a funded payroll deposit. For example, the enforcement engine  712  can perform a lookup in the profiles maintained in the database  716  based on the identifier of the electronic funding source  702   a  to identify a funding source category and determine if the funding source category corresponds to a funded payroll deposit. The enforcement engine  712  can select an alert format corresponding to the funded payroll deposit, the alert format including a first field for the instructions to deny the single electronic benefits account transaction and a second field for a reason code. For example, the enforcement engine  712  can perform a lookup in the alert formats maintained in the database  716  based on the identified funded payroll deposit to select the alert format. The enforcement engine  712  can then generate the alert in the alert format that includes instructions to terminate the single electronic benefits account transaction and the reason code and transmit the one or more response packets carrying the alert. The reason code can include an indication that the virtual transaction balance exceeds the threshold limit for the electronic benefits account. The reason code can include an indication that the in-process transaction queue and/or the reportable contribution amount exceeds the threshold limit for the electronic benefits account. The reason code can include an indication of excess contribution. 
     In some embodiments, the enforcement engine  712  can access a profile database to determine that the electronic funding source corresponds to a non-payroll deposit. For example, the enforcement engine  712  can perform a lookup in the profiles maintained in the database  716  based on the identifier of the electronic funding source  702   a  to identify a funding source category and determine if the funding source category corresponds to a non-payroll deposit. The enforcement engine  712  can select the alert format for the instructions to terminate the single electronic benefits account transaction corresponding to the non-payroll deposit, the alert format including a first field for a reason code, and a second field for instructions to exclude the transaction from the in-process transaction amount. The enforcement engine  712  can then generate the alert in the alert format that includes instructions to terminate the single electronic benefits account transaction, the reasons code, and the instructions to exclude the transaction from the in-process transaction amount, and transmit the one or more response packets carrying the alert. 
     In some embodiments, the enforcement engine  712  is configured to receive a second one or more packets including a second request to initiate a second single electronic benefits account transaction to fund the electronic benefits account. The second request and the enforcement actions performed by the enforcement engine  712  regarding the second request can be similar to the first request and associated enforcement actions. The second request can include a second data structure identifying the transaction destination, the transaction code, a second transaction amount, and the first electronic funding source. The enforcement engine  712  can generate a second value by combining the second transaction amount, the in-process transaction amount, and the reportable contribution amount identified from the electronic transaction queue of the electronic benefits account maintained in the database  714 . The second value is different from the value of the first electronic transaction request. The enforcement engine  712  can determine that the second value is less than the threshold limit applied to the first value based on a comparison of the second value with the threshold limit. The enforcement engine can generate, responsive to the second value being less than the threshold limit, second response packets to authorize the second single electronic benefits account transaction. For example, the second response packets can include instructions similar to the response packets denying the first single electronic benefits account transaction, except that the second response packets cause the first client device  102   a  and/or the first electronic funding source  702   a  to authorize and perform the transaction. 
     In some aspects, the system of the present solutions implements a combination of the communication interface  710 , enforcement engine  712 , databases  714  or  716 , claims processor  220 , POS terminals  202   a - n , or clients  102   a - n  in an innovative, non-conventional or non-routine manner. In some aspects, the system of the present solutions integrates the communication interface  710 , enforcement engine  712 , databases  714  or  716 , claims processor  220 , POS terminals  202   a - n , or clients  102   a - n  in an innovative, non-conventional or non-routine manner to implement the improved functionality, performance and operation of the present solution. In some aspects, the system of the present solutions integrates the communication interface  710 , enforcement engine  712 , databases  714  or  716 , claims processor  220 , POS terminals  202   a - n , or clients  102   a - n  in an innovative, non-conventional and/or non-routine manner to more efficiently and effectively use computing and networking resources. The communication interface  710 , enforcement engine  712 , databases  714  or  716 , claims processor  220 , POS terminals  202   a - n , or clients  102   a - n  are integrated in an innovative, nonconventional manner to mitigate, reduce, prevent, or resolve the technical problems of allocating resources in real-time. The communication interface  710 , enforcement engine  712 , databases  714  or  716 , claims processor  220 , POS terminals  202   a - n , or clients  102   a - n  integrated in the innovative, non-conventional manner address at least these technical problems by providing, to a plurality of devices corresponding to a plurality of heterogeneous electronic funding sources, an electronic benefits account transaction application programming interface (“API”) configured to receive transaction requests from the plurality of heterogeneous electronic funding sources; receiving, via the electronic benefits account transaction API, from a first device of the plurality of devices corresponding to a first electronic funding source of the plurality of heterogeneous electronic transaction sources, a first one or more packets comprising a request to initiate a single electronic benefits account transaction to fund an electronic benefits account, the request identifying a transaction destination, a transaction code, a transaction amount and an identifier identifying the first electronic funding source; determining the transaction code maps to one of a current year or a previous year; performing a lookup in an electronic transaction queue of the electronic benefits account maintained in memory by the server to identify an in-process transaction amount and a reportable contribution amount; generating a value by combining the transaction amount, the in-process transaction amount and the reportable contribution amount identified from the electronic transaction queue of the electronic benefits account maintained in memory by the server, the value indicating a virtual transaction balance; comparing the value with a threshold limit for the one of the current year or the previous year mapped to the transaction code to determine that the value exceeds the threshold limit; selecting an alert format configured for an interface corresponding to the first electronic funding source; and transmitting, via a network to the first device, one or more packets carrying data in the alert format indicating a denial of the single electronic benefits account transaction request responsive to the comparison and the transaction code mapping to the one of the current year or the previous year, the one or more packets configured to indicate to the first device termination of the single electronic benefits account transaction initiated by the request to prevent exceeding the threshold limit established for the electronic benefits account. 
     Referring now to  FIG.  8   , a flow diagram depicting an embodiment of a method of managing an electronic transaction portal is shown. The method can be performed by system  700 , TEPS  708 , or one or more component thereof. In brief overview, at step  805 , a server provides an electronic benefits account transaction API to a plurality of devices corresponding to a plurality of heterogeneous electronic funding sources. At step  810 , the server receives a first one or more packets including a request to initiate a single electronic benefits account transaction from a first device corresponding to a first electronic funding source. At step  815 , the server determines that a transaction code of the request maps to one of a current year or a previous year. At step  820 , the server identifies an in-process transaction amount and a reportable contribution amount by performing a lookup in an electronic transaction queue of the electronic benefits account. At step  825 , the server generates a value indicating a virtual transaction balance by combining the transaction amount, the in-process transaction amount, and the reportable contribution amount. At step  835 , the server selects an alert format configured for an interface corresponding to the first electronic funding source. At step  840 , the server transmits data indicating a denial of the single electronic benefits account transaction request and indicating to the first device to terminate the transaction initiated by the request to prevent exceeding of the threshold limit. 
     Still referring to  FIG.  8   , and in further detail, a server of a transaction enforcement portal system provides an electronic benefits account transaction API to a plurality of devices corresponding to a plurality of heterogeneous electronic funding sources at step  805 . The server can include one or more processors. The server can include a communications interface for receiving the request. In some aspects, step  805  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  805  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  805  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     In some embodiments, one of the devices establishes an electronic connection to the server responsive to user input received at a user interface of the device. Via the electronic connection, the server receives data packets including an indication of an operating system of the device and an indication of existing applications installed on the device. The server parses the data packets to retrieve the indication of the operation system and/or the indication of existing applications installed on the device, performs a lookup in a database to identify an appropriate electronic benefits account API for the device, and transmits the appropriate electronic benefits account API to the device in response to determining that the device requires the electronic benefits account API in order for the server to receive an electronic transaction request from the electronic funding source. The electronic benefits account API can be configured to match a specific electronic funding source. For example, the can query the device for an indication of the specific electronic funding source, receive the indication of the specific electronic funding source responsive to the query, compare the indication to a list of electronic funding sources stored in a database, and retrieve an appropriate electronic benefits account API responsive to the comparison for providing to the device. 
     The server receives a first one or more data packets including the electronic transaction request to initiate the single electronic benefits account transaction to fund an electronic benefits account via the electronic benefits account transaction API from a first device of the plurality of devices corresponding to the plurality of heterogeneous electronic funding sources at step  810 . The request identifies a transaction destination, a transaction code, a transaction amount, and an identifier identifying the first electronic funding source. The device can generate the request responsive to the client device receiving user input at a user interface, which indicates a request for funds to be transferred from a first electronic funding source to the electronic benefits account to be funded. In some aspects, step  810  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  810  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  810  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     The server determines that the transaction code maps to one of a current year or a previous year at step  815 . The server can perform the determination by executing an enforcement engine. The enforcement engine can execute on one or more processors of the server. The server can receive, retrieve, or otherwise obtain or access electronic transaction queues, code maps, enforcement rules, and profiles stored in databases. The server can receive the first one or more data packets including the request to initiate the single electronic benefits account transaction and parse the first one or more data packets to extract the transaction code. The server can perform a lookup in a code map to retrieve a list or other data structure mapping transaction codes to a time reference, such as a year, a current year, a previous year, etc. In some embodiments, the code map includes a list of transaction codes associated with a current year, a list of transaction codes associated with a previous year, and a list of transaction codes associated with other years. In some embodiments, the transaction code itself is a time reference such as a date or year, and the code map includes a value for a current year, and a value for a previous year. The server can then compare the transaction code to the retrieved code map to determine whether the transaction code corresponds to one of a current year or a previous year. 
     In some aspects, step  815  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  815  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  815  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     In some embodiments, the server identifies, using a profile of the electronic benefits account stored in a database, that the first electronic funding source enforces electronic benefits account limits. For example, the server parses the electronic transaction request to extract the identifier of the first electronic funding source, performs a lookup in the database to identify a profile corresponding to the first electronic funding source, and retrieves from the profile an indication of whether the first electronic funding source enforces electronic benefits account limits. The server can determine, responsive to identifying that the first electronic funding source enforces electronic benefits account limits, that the transaction code maps to one of the current year or the previous year. 
     In some embodiments, the server determines an enforcement rule based on the single electronic benefits account transaction request. For example, the server parses the electronic transaction request to extract the transaction destination and/or identifier of the first electronic funding source. The server performs a lookup in a database to identify the electronic benefits account associated with the transaction destination, and performs a lookup in the database to identify an enforcement rule associated with the electronic benefits account. The server performs a lookup in a database using the identifier of the first electronic funding source to retrieve an indicator of an enforcement rule, and performs a lookup in a database to identify the enforcement rule associated with the first electronic funding source. 
     In some embodiments, the server identifies the threshold limit based on the enforcement rule. The enforcement rules maintained in a database can include a map associating electronic benefits accounts with threshold limits. The server can use or apply an enforcement rule that includes one or more techniques, algorithms, heuristics, or procedures. The enforcement rule can include decision points and utilize parameters or criteria. The enforcement rule can be based on criteria or rules that are established by an administrator of the server, the heterogeneous electronic funding sources, electronic employer payroll accounts, insurance entities, or another entity. The enforcement rule can facilitate determining a threshold limit to be applied to the electronic transactions. For example, the map can associate electronic benefits accounts that are subject to IRS threshold limits with IRS threshold limits. The enforcement rule can include the rule: if transaction code maps to current year, then apply current year threshold limit; else if transaction code maps to previous year, then apply previous year threshold limit; else do not apply limit. The enforcement rule can include multiple criteria. For example, the enforcement rule can include: if electronic funding source corresponds to (or equals or maps to or is) employer payroll account or individual checking account or insurance account, then apply IRS threshold limit. The enforcement rule can be a negative enforcement rule. For example, the enforcement rule can include: if electronic funding source does correspond to employer payroll account or individual checking account or insurance account, then do not apply IRS threshold limit. The enforcement rule can include an action to take when the enforcement rule is not satisfied. For example, if the electronic funding source corresponds to employer payroll account or individual checking account or insurance account, then apply IRS threshold limit; if not, then post transaction. A single enforcement can include multiple enforcement rules. The server can use process multiple enforcement rules before identifying an enforcement rule that is satisfied. 
     In some embodiments, the server applies the electronic transaction to one of the current year or the previous year depending on the total contribution amount for each year. For example, the enforcement rule can include determining a virtual transaction balance for each of the current year and the previous year, comparing the virtual transaction balance for each of the current year and the previous year, and selecting one of the current year or the previous year for receiving the transaction amount. The enforcement rule can include: if the virtual transaction balance for both the current year and the previous year is less than a threshold limit, then apply the transaction amount to the current year; else if the virtual transaction amount for one of the current year or the previous year is less than a threshold limit, then apply the transaction amount to the one of the current year or the previous year; else do not apply the transaction amount. In some embodiments, the enforcement rule can include applying a partial amount of the transaction amount that will not exceed the threshold limit, such as a partial amount that will cause the virtual transaction balance to equal the threshold limit, or a partial amount that will cause the virtual transaction balance to equal a fraction of the threshold limit (e.g., 50%, 60%, 70%, 80%, 90%, 95%, 99%, etc. of the threshold limit). 
     The server performs a lookup in the electronic transaction queue to identify an in-process transaction amount and a reportable contribution amount at step  820 . In some aspects, step  820  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  820  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  820  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     The server can execute an enforcement engine to perform the lookup in a database. The in-process transaction amount can include a plurality of transactions request amounts for funding the single electronic benefits account that have been received by the server but not yet posted. For example, the in-process transaction amount can include a sum of multiple transaction requests, such as when a client device receives user input indicating a request for funds to be transferred from an individual checking account in a first electronic transaction request, and an employer payroll generates a second transaction request. The in-process transaction amount can include pending transactions that are future dated and not yet sent for processing, and can include processing transactions that have been sent for processing but have not yet posted. The reportable contribution amount can include transactions that have posted to the total amount of the electronic benefits account and thus will count against a threshold limit of the electronic benefits account. 
     The server generates a value by combining the transaction amount, the in-process transaction amount, and the reportable contribution amount identified from the electronic transaction queue of the electronic benefits account maintained in a database, setting the generated value to indicate a virtual transaction balance, at step  825 . In some aspects, step  825  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  825  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  825  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     The server can execute an enforcement engine to perform the generation. The value can indicate a virtual transaction balance, such as a balance of the electronic benefits account that would occur if all of the transactions of the transaction amount, the in-process transaction amount, and the reportable contribution amount were posted to the electronic benefits account. In some embodiments, the server generates the value by summing the transaction amount, the in-process transaction amount, and the reportable contribution amount. The server can store the value indicating the virtual transaction balance in a database maintaining the electronic benefits account, or a database maintaining a profile associated with the electronic benefits account. For example, the server can generate the value, perform a lookup in a database to identify a profile associated with the electronic benefits account, and store the virtual transaction balance in the profile. 
     The server compares the value with a threshold limit for the one of the current year or the previous year mapped to the transaction code to determine that the value exceeds the threshold limit at step  830 . In some aspects, step  830  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  830  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  830  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     The server can execute an enforcement engine to perform the comparison. For example, the server can perform a lookup in a database to identify an enforcement rule that includes threshold limits for the one of the current year or the previous year, retrieve the threshold limit for the one of the current year or the previous year mapped to the transaction code, and compare the value to the threshold limit. The server can determine that the value exceeds the threshold limit based on the value being greater than the threshold limit. 
     In some embodiments, the enforcement engine selects the threshold limit based on a predetermined threshold limit configured for the first electronic funding source. For example, the server can parse the electronic transaction request to extract the identifier of the first electronic funding source, perform a lookup in a profile database maintained in the database to retrieve a profile of the first electronic funding source, and perform a lookup in the profile to identify the predetermined threshold limit. 
     In some embodiments, the server receives enforcement rules and threshold limits from entities including a claims processor, a server of a remote entity such as the electronic funding sources, and/or a server of an employer, insurance administrator, or financial institution. For example, an employer contributing to the electronic benefits account can establish an enforcement rule and maintain it on a remote employer server. The server can receive an indication of the electronic benefits account, perform a lookup in the enforcement rules maintained in a database, and responsive to determining that the database does not include an appropriate enforcement rule for the electronic benefits account, the server can transmit a request for an enforcement rule to the remote employer server, causing the remote employer server to transmit the appropriate enforcement rule to the server. 
     In some embodiments, the server receives the request to initiate the single electronic benefits account transaction, and the request is initiated by a remote device that is remote to the first device and configured with authentication credentials to access the first device. For example, the remote device can be a portable electronic device, and the first device can be a client server configured to communicate with the portable electronic device and the server. The remote device can include an electronic benefits account transaction API configured to receive a single transaction request from an electronic funding source. A user of the remote device can interact with a user interface of the remote device to initiate the single transaction request. The remote device can initiate the single transaction request responsive to receiving user input indicating a request to initiate the single transaction request via a user interface. The remote device can transmit the single transaction request as one or more data packets carrying the single transaction request and the authentication credentials. The client server can receive the one or more data packets, extract the authentication credentials, and compare the authentication credentials to corresponding authentication credentials stored on the client server (e.g., authentication credentials stored with an electronic benefits account transaction API) in order to determine whether to authenticate the single transaction request. Responsive to determining to authenticate the single transaction request, the client server can transmit the single transaction request to the server. 
     In some embodiments, the server maintains the stored authentication credentials, and the electronic benefits account transaction API of the client server receives the single transaction request from the remote device, extracts the authentication credentials and transmits only the authentication credentials to server; the server receives the authentication credentials, compares the authentication credentials to the stored authentication credentials (e.g., by performing a lookup in a database maintaining authentication credentials), and responsive to determining that the extracted authentication credentials match the stored authentication credentials, generates an acknowledgement to transmit to the client server causing the client server to transmit the single transaction request to the server. 
     In some embodiments, the server applies a second enforcement rule directed to additional factors after using a first enforcement rule. The server selects the second enforcement rule responsive to or based on the first enforcement rule. The first enforcement rule can include a map of a transaction code to one of the current year or the previous year, and the second enforcement rule can be a threshold limit for the one of the current year or the previous year. 
     In some embodiments, the server receives an indication from a claims processor external to the server via a network. In some embodiments, the server is configured with the claims processor or configured to interface with the claims processor via a communications interface. The claims processor can process an electronic transaction request to determine whether applying an electronic transaction to the electronic benefits account would exceed a threshold limit for the electronic benefits account. The claims processor can be configured to use one or more enforcement rules to process the electronic transaction request. The enforcement rules can be based on a type of insurance coverage associated with a user of the electronic benefits account. The claims processor can automatically receive the electronic transaction request responsive to a client device generating the electronic transaction request responsive to user input, or responsive to a server of an employer or insurance administrator generating the electronic transaction request. 
     In some embodiments, the server receives information or instructions from an enforcement engine regarding an electronic transaction, and conducts the electronic transaction. The server obtains electronic funding source information and/or electronic benefits account information from a database to perform the transaction. The transaction can include electronically transferring funds from the electronic funding source to the electronic benefits account. The transaction can include memo-posting or hard-posting the electronic transaction. For example, the server can receive instructions to post the electronic transaction, and responsive to receiving the instructions, the server performs a lookup in a profile of the electronic benefits account maintained in a database to identify a financial institution associated with the electronic benefits account in order to transmit instructions to the financial institution to post the transaction, including the value. In some cases, the server facilitates a transfer of funds between an electronic account of a claims processor and the electronic benefits. The server receives account identifiers, transaction amounts, credentials, authentication information, etc. The server conducts the transaction via a communications interface, thereby using the network protocols, security protocols and other components or interfaces provided by the communications interface. 
     In some embodiments, the server receives a request for account information from a device. The request for information can include information about a balance of the electronic benefits account (e.g., an in-process transaction amount, a reportable contribution amount, a virtual transaction balance), enforcement rules, or transaction histories. The request can further include authentication information or credentials associated with the request. The authentication information can include network security credentials, such as security certificates or tokens. The authentication information can further include a username, password, two-tier authentication information (e.g., date of birth, cell phone number, verification code sent via text message to cell phone number in profile associated with electronic account). The request can be from a device such as a smartphone. The request can be sent using a text messaging protocol such as SMS. The server can authenticate a request sent via SMS based on the cell phone number of the device sending the SMS request, and matching the cell phone number with corresponding number stored in a profile in a database for the electronic benefits account. 
     Responsive to authenticating or otherwise approving the request, the server can access a data record in a database for the electronic benefits account to generate a report with the requested information, or generate a standard report, or generate another preconfigured report. The report can identify the account holder information and balances associated with the electronic benefits account. The report can further identify a transaction history for the electronic benefits account. The report can further identify or indicate if the electronic benefits account has reached or exceeded a threshold limit. The report can further include a forecast based on current/previous transaction history that indicates if and when the threshold limit for a time interval might be reached or exceeded. 
     The server selects an alert format configured for an interface corresponding to the first electronic funding source at step  835 . In some aspects, step  835  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  835  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  835  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     The server can execute an enforcement engine to perform the determination. The server can generate an alert in the alert format that includes instructions to terminate the single electronic benefits account transaction initiated by the request to prevent exceeding the threshold limit established for the electronic benefits account. The server can perform a lookup in a database maintaining alert formats for alerts based on the identifier of the first electronic funding source in order to identify and retrieve the alert format. The alert format can include a variety of fields configured to be read by the first electronic funding source. For example, the alert format can includes fields directed to an indication of an approval or denial of the single electronic benefits account transaction request; approval of a partial amount of the transaction amount, an indication of the electronic benefits account, an indication of a user of the electronic benefits account, and an indication of a current or projected balance of the electronic benefits account. The alert format can include fields similar to or directed to information provided by the server in a report responsive to a request for account information from a device. The alert format can include authentication credentials configured to be read by the first electronic funding source to authenticate the alert. The alert format can include a field including instructions for terminating or authorizing the request to initiate the single electronic benefits account transaction. 
     The server transmits, via a network to the first device, one or more packets carrying data in the alert format indicating a denial of the single electronic benefits account transaction request, responsive to the comparison and the transaction code mapping to the one of the current year or the previous year, the one or more packets configured to indicate to the first device termination of the single electronic benefits account transaction initiated by the request to prevent exceeding the threshold limit established for the electronic benefits account at step  840 . In some aspects, step  840  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  840  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  840  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     The server can execute an enforcement engine and a communications interface to perform the transmission. For example, the server can retrieve the alert format, generate the one or more packets carrying the information organized in the selected alert format, and cause a communications interface to transmit the one or more packets to the first device. The server can retrieve the information required by the alert format from the electronic transaction request, and/or a database to generate the one or more packets of the alert. For example, the server can retrieve the identifier of the first electronic funding source from the electronic transaction request, the indication of the denial of the electronic transaction request from a database maintaining the electronic benefits account, and the authentication credentials from the profile of the first electronic funding source maintained in a database, in order to generate the alert as one or more packets carrying this information to be transmitted via a communications interface. 
     The one or more packets can include a reason code or error code indicating a reason or error associated with the denial (or approval, if applicable) of the electronic transaction request. The reason code can be generated by the server (or an enforcement engine executed by the server) responsive to the server applying an enforcement rule for identifying a threshold limit. The reason code can indicate that the transaction amount of the single electronic transaction request would exceed the threshold limit applied to the electronic benefits account. The reason code can indicate that the transaction amount would exceed the combined IRS family and catchup threshold limit that was applied because the age of the participant was greater than or equal to fifty-five. The reason code can indicate that the electronic benefits account does not segregate threshold limits into coverage tiers (e.g., coverage tiers based on age), and thus the threshold limit used was the combined IRS family and catchup threshold limit. The reason code can indicate that the transaction amount would exceed the IRS family threshold limit that was applied because the age of the participant was less than fifty-five and the household type was “family.” The reason code can indicate that the transaction amount would exceed the IRS single threshold limit that was applied because the age of the participant was less than fifty-five and the household type was “single.” 
     The one or more packets can include instructions that cause the electronic benefits account transaction API of the device to reroute the one or more packets to the first electronic funding source in order to cause the first electronic funding source to terminate the single electronic benefits account transaction. For example, the electronic benefits account transaction API can receive the one or more packets, extract the indication of the denial of the electronic transaction request and the identifier of the first electronic funding source, and transmit the one or more packets to the first electronic funding source. The one or more packets can include instructions causing the electronic benefits account transaction API to generate instructions causing first electronic funding source to terminate the single electronic benefits account transaction. For example, the electronic benefits account transaction API can receive the one or more packets, extract the indication of the denial of the electronic transaction request and the identifier of the first electronic funding source, and generate instructions to transmit to the first electronic funding source to cause the first electronic funding source to terminate the single electronic benefits account transaction. 
     In some embodiments, the server transmits the alert to the first device to cause the first device to terminate the transaction, when the transaction was initiated by the remote device remote to the first client device. For example, a portable electronic device may have initiated the electronic transaction request, responsive to user input, and transmitted the request to the first device which manages the electronic funding source; the server can identify this chain of command by parsing the electronic transaction request in order to transmit the alert to the first client device with instructions causing the first device to terminate the transaction. 
     In some embodiments, the server establishes a bidirectional communication channel with the first device. The server transfers requests and instructions to terminate transactions. For example, the server can transmit a request to establish a bidirectional communication channel with the first device to the electronic benefits account transaction API provided to the first device. The server can also transmit the bidirectional communication channel request when providing the electronic benefits account transaction API. The request can be configured to cause the device to establish a communication channel via a communications interface automatically or responsive to approval received as user input at a user interface, or approval granted by another application of the device. The server can then receive the responsive communication from the device, and retrieve a communication protocol from a database associated with the electronic benefits account transaction API of the device in order to establish the bidirectional communication channel based on the retrieved communication protocol. For example, the bidirectional communication channel can be based on an Internet-based communication channel in which data packets can be regularly transmitted between the device and the server. 
     The communication protocol for establishing the bidirectional communication channel can include authenticating communication between the device and the server. For example, the server can retrieve the identifier of the device, perform a lookup in a database to identify authentication credentials associated with the device, transmit the authentication credentials to the device, and responsive to the device authorizing communication based on the authentication credentials, receive a challenge from the device, extract additional authentication credentials from the challenge, perform a lookup in the database to compare the additional authentication credentials to stored authentication credentials, and authorize the bidirectional communication based on the additional authentication credentials matching the stored authentication credentials. 
     In some embodiments, the server transmits, via a network to the first device, the response packets indicating the denial of the single electronic benefits account transaction request within a predetermined time interval from receiving the single electronic benefits account transaction request. The predetermined time interval can be a time period after an action, e.g. 10 minutes, 5 minutes, 1 minute, 30 seconds. The action can include receiving the electronic transaction request, posting the transaction or denying the transaction, and/or generating the alert including instructions to terminate the single electronic benefits account transaction. The pre-determine time interval can be set in a configuration file or profile maintained by the server in a database, the configuration file or profile corresponding to the electronic benefits account. The pre-determined time interval can be set by an entity remote from the server. For example, the server can transmit a time interval request to a remote server of an insurance administrator, an employer, or a financial institution. The time interval request can cause the remote server to transmit the configuration file or profile setting the pre-determined time interval to the server. The server can process the configuration file or profile to extract the pre-determined time interval in order to transmit the notification within the pre-determined time interval. 
     In some embodiments, responsive to the action occurring that initiates the pre-determined time interval, the server generates a placeholder notification to be transmitted to the first device independent of the status of the electronic transaction request. For example, the placeholder notification can indicate that enforcement of the electronic transaction request has been initiated. The placeholder notification can indicate that further information is required to complete the enforcement of the electronic transaction request. The server can transmit the placeholder notification prior to expiry of the pre-determined time interval via a communications interface to provide real-time communication of the adjudication process. 
     In some embodiments, the pre-determined time interval can be based on the type of electronic benefits account, the type of electronic funding source, or an expected time required to perform transactions with the electronic benefits account or the electronic funding source. For example, if the electronic benefits account or the electronic funding source can perform transactions using wire transfer, than the pre-determined time interval can be approximately ten seconds, thirty seconds, one minute, etc. If the electronic benefits account or the electronic funding source can perform transactions by direct deposit, then the pre-determined time interval can be a time associated with electronic communication between the server and the electronic funding source, such as ten minutes. The pre-determined time interval can be based on a time required to transfer funds from an electronic bank account associated with an insurance administrator or with an employer to the electronic benefits account. The pre-determined time interval can be based on a time required for an indication of the enforcement of the electronic transaction request to be received at a remote server in order to authorize or deny the funds for being transferred to the electronic benefits account. 
     In some embodiments, the server determines that the electronic funding source corresponds to a funded payroll deposit. For example, the enforcement engine can perform a lookup in the profiles maintained in the database based on the identifier of the electronic funding source to identify a funding source category and determine if the funding source category corresponds to a funded payroll deposit. The server can select an alert format corresponding to the funded payroll deposit, the alert format including a first field for the instructions to deny the single electronic benefits account transaction and a second field for a reason code. For example, the server can perform a lookup in the alert formats maintained in a database, based on the identified funded payroll deposit, to select the alert format. The server can then generate the alert in the alert format that includes instructions to terminate the single electronic benefits account transaction and the reason code and transmit the one or more response packets carrying the alert. The reason code can include an indication that the virtual transaction balance exceeds the threshold limit for the electronic benefits account. The reason code can include an indication that the in-process transaction queue and/or the reportable contribution amount exceeds the threshold limit for the electronic benefits account. The reason code can include an indication of excess contribution. 
     In some embodiments, the server accesses a profile database to determine that the electronic funding source corresponds to a non-payroll deposit. For example, the server can perform a lookup in the profiles maintained in a database based on the identifier of the electronic funding source to identify a funding source category and determine if the funding source category corresponds to a non-payroll deposit. The server can select the alert format for the instructions to terminate the single electronic benefits account transaction corresponding to the non-payroll deposit, the alert format including a first field for a reason code, and a second field for instructions to exclude the transaction from the in-process transaction amount. The server can then generate the alert in the alert format that includes instructions to terminate the single electronic benefits account transaction, the reasons code, and the instructions to exclude the transaction from the in-process transaction amount, and transmit the one or more response packets carrying the alert. 
     In some embodiments, the server receives a second one or more packets including a second request to initiate a second single electronic benefits account transaction to fund the electronic benefits account. The second request and the enforcement actions performed by the server regarding the second request can be similar to the first request and associated enforcement actions. The second request can include a second data structure identifying the transaction destination, the transaction code, a second transaction amount, and the first electronic funding source. The server can generate a second value by combining the second transaction amount, the in-process transaction amount, and the reportable contribution amount identified from the electronic transaction queue of the electronic benefits account maintained in a database. The second value is different from the value of the first electronic transaction request. The server can determine that the second value is less than the threshold limit applied to the first value based on a comparison of the second value with the threshold limit. The server can generate, responsive to the second value being less than the threshold limit, second response packets to authorize the second single electronic benefits account transaction. For example, the second response packets can include instructions similar to the response packets denying the first single electronic benefits account transaction, except that the second response packets cause the first device and/or the first electronic funding source to authorize and perform the transaction. 
     In some aspects, the methods of the present solutions implements a combination of steps in an innovative, non-conventional and/or non-routine manner. In some aspects, the method  800  of the present solution combines the steps of  FIG.  8    in an innovative, non-conventional and/or non-routine combination to implement the improved functionality, performance and operation of the present solution. In some aspects, the method of the present solution combines the steps of  FIG.  8    in in an innovative, non-conventional and/or non-routine manner to more efficiently and effectively use computing and networking resources. In some aspects, the method of the present solution provides innovative, non-conventional and/or non-routine ordered combination of steps. 
     Referring now to  FIGS.  9 A- 9 D , process flow diagrams depicting embodiments of methods of managing an electronic transaction portal are shown. The methods can be performed by system  700 , TEPS  708 , or one or more components thereof. 
       FIG.  9 A  illustrates a method  900   a  of managing an electronic transaction portal to receive an electronic transaction request and execute authorization or denial of the electronic transaction request. At  904 , a single transaction process request is received at the electronic transaction portal from a device of an electronic funding source. For example, the electronic funding source may be an employer payroll account that regularly deposits funds in an electronic benefits account, such as an HSA, by transferring funds through the electronic transaction portal. 
     At  908 , the electronic transaction portal determines whether the electronic funding source enforces electronic benefits account limits. If the electronic funding source does not enforce electronic benefits account limits, then at  910 , the electronic transaction portal memo-posts the transaction. 
     Responsive to determining that the electronic funding source enforces electronic benefits account limits, at  912 , the electronic transaction portal determines whether a transaction code of the electronic transaction request maps to one of a current year or a previous year. The transaction code can be a time reference, such as a date or year. The electronic transaction portal can compare the time reference to the current year and the previous year to identify whether the transaction code maps to one of the current year or the previous year. Responsive to determining that the transaction code does not map to either the current year or the previous year, the electronic transaction portal memo-posts the transaction at  910 . 
     Memo posting can refer to a technique used in a computerized banking environments in which batch processing is employed. Memo posting can represent temporary credit or debit transactions or entries made to an account for which the complete posting to update the balance will be done as part of the end-of-day batch processing. The temporary transaction created as part of the memo-posting will be reversed or removed after the actual transaction is posted in batch processing. For example, a customer receives an electronic credit to an account with current day as effective date. The actual transaction for this entry will be made at the end-of-day in batch posting. In order to access this electronic credit for which the customer is eligible by rules, the bank can creates a temporary “memo” credit to increase the balance available (withdrawal). Later this entry will be removed as part of the end-of-day batch process. In another example, the actual transaction to record a withdrawal using an ATM (automated teller machine) will be posted to accounts in the end-of-day batch. In order to prevent the customer from overdrawing the customer&#39;s account later in the day, the amount of the cash withdrawal is memo-posted as a charge to the customer&#39;s account until the transaction actually posts in the batch update that evening. 
     Responsive to determining that the transaction code maps to one of the current year or the previous year, the electronic transaction portal determines a combined value and a threshold limit at  916 . The electronic transaction portal can perform a lookup in an enforcement rules database  920  to identify a threshold limit from an enforcement rule. The enforcement rules database  920  can be similar or identical to the database  716  depicted in  FIG.  7   . The electronic transaction portal can perform a lookup in an electronic benefits account transaction queue database  922  to identify an in-process transaction queue and a reportable contribution amount, in order to combine these values with a transaction amount of the electronic transaction request to determine a combined value. 
     At  926 , the electronic transaction portal determines whether the combined value exceeds the threshold limit. Responsive to determining that the combined value does not exceed the threshold limit, the electronic transaction portal authorizes the transaction by memo-posting the transaction and adding the transaction amount to the in-process transaction amount at  932 . At  936 , the electronic transaction portal can debit an employer payroll funding account, and at  938 , the electronic transaction portal can hard-post the transaction on the posting date. Actions  936  and  938  can also be performed responsive to the electronic transaction portal causing a financial institution to act. Action  838  can also be performed responsive to action  910 . 
     At  930 , responsive to determining that the combined value exceeds the threshold limit, the electronic transaction portal transmits a denial alert configured to deny the transaction, and thus prevent the threshold limit of the electronic benefits account from being exceeded. 
       FIG.  9 B  illustrates a method  900   b  for generating and executing alerts using an electronic transaction portal. Action  930  of  FIG.  9 A  may serve as an input to action  940  of  FIG.  9 B . At  940 , the electronic transaction portal determines whether the transaction indicated by the electronic transaction request is a funded payroll deposit. For example, the electronic transaction portal can extract a funding category of the transaction from the electronic transaction request and perform a lookup in a profile database  942  based on the funding category to identify the funding category of the transaction. The profile database can be similar or identical to the database  716  illustrated in  FIG.  7   . Responsive to determining whether the transaction is a funded payroll deposit, the electronic transaction portal selects an alert format corresponding to a funded payroll deposit at  944 , and selects an alert format corresponding to a non-payroll deposit at  952 . The alert format can be selected by performing a lookup in an alert database  946  based on the funding category to identify an appropriate alert format. The alert database  946  can be similar or identical to the database  716  depicted in  FIG.  7   . 
     The electronic transaction portal generates an alert using the alert format including instructions to terminate the transaction and a reason code at  948 . The electronic transaction portal then transmits the alert to the device of the electronic funding source at  950 . 
     The electronic transaction portal generates an alert including instructions to terminate the transaction, a reason code, an instructions to exclude the transaction from an in-process transaction amount at  954 . This can ensure that the transaction does not post in the event that the non-payroll deposit electronic funding source requires additional instructions to prevent the transaction. The electronic transaction portal then transmits the alert to the device of the electronic funding source at  956 , and determines not to post the transaction at  958  in order to prevent the transaction from causing the threshold limit for the electronic benefits account to be exceeded. The system can make a determination to not post the transaction, or the system can prevent the transaction from being posted by terminating the transaction. 
       FIG.  9 C  illustrates a method  900   c  of managing an electronic transaction portal to receive an electronic transaction request and execute authorization or denial of the electronic transaction request. Method  900   c  can be similar to method  900   a . The electronic transaction portal receives a single transaction process request from a device of an electronic funding source at  960 . 
     The electronic transaction portal determines whether the electronic funding source enforces electronic benefits account limits at  962 . Responsive to determining that the electronic funding source does not enforce electronic benefits account limits, the electronic transaction portal memo-posts the transaction at  964 . 
     Responsive to determining that the electronic funding source enforces electronic benefits account limits, the electronic transaction portal determines whether the electronic funding source is a bank for an HSA maintained by the electronic transaction portal at  966 , such as an HSA maintained by the WealthCare system provided by Alegeus Technologies (“WC HSA bank”). For example, the electronic transaction portal can extract an identifier of the electronic funding source from the electronic transaction request, and perform a lookup in a profile database based on the identifier to compare the identifier to a list of funding sources to determine whether the electronic funding source is a WC HSA bank. 
     Responsive to determining that the electronic funding source is not a WC HSA bank, the electronic transaction portal determines the combined value of the transaction, the in-process transaction amount, and the reportable contribution amount at  964 , in order to determine whether the combined value exceeds a threshold limit at  972 . Responsive to determining that the combined value exceeds the threshold amount, the electronic transaction portal transmits a denial alert with an excess contribution reason code at  978 . Responsive to determining that the combined value does not exceed the threshold amount, the electronic transaction portal approves the transaction at  974  and debits an employer payroll funding account at  976 . 
     Responsive to determining that the electronic funding source is a WC HSA bank, the electronic transaction portal determines whether the transaction code of the electronic transaction request maps to one of the current year or previous year at  968 . Responsive to determining that the transaction code maps to one of the current year or the previous year, the electronic transaction portal continues to execute the an enforcement engine at  970  (e.g., continues to action  916  of  FIG.  9 A , etc.). Responsive to determining that the transaction code does not map to one of the current year or the previous year, the electronic transaction portal memo-posts the transaction at  964 . 
       FIG.  9 D  illustrates a method  900   d  of managing an electronic transaction portal to receive an electronic transaction request and execute authorization or denial of the electronic transaction request. Method  900   c  can be similar to methods  900   a  and  900   b . The electronic transaction portal receives a single transaction process request from a device of an electronic funding source at  980 . The electronic transaction portal determines whether the electronic funding source enforces electronic benefits account limits at  982 . Responsive to determining that the electronic funding source does not enforce electronic benefits account limits, the electronic transaction portal memo-posts the transaction at  988 . 
     Responsive to determining that the electronic funding source enforces electronic benefits account limits, the electronic transaction portal determines whether the electronic funding source is a WC HSA bank at  984 . For example, the electronic transaction portal can extract an identifier of the electronic funding source from the electronic transaction request, and perform a lookup in a profile database based on the identifier to compare the identifier to a list of funding sources to determine whether the electronic funding source is a WC HSA bank. 
     Responsive to determining that the electronic funding source is not a WC HSA bank, the electronic transaction portal determines the combined value of the transaction, the in-process transaction amount, and the reportable contribution amount at  992 , in order to determine whether the combined value exceeds a threshold limit at  994 . Responsive to determining that the combined value exceeds the threshold amount, the electronic transaction portal transmits a denial alert with an excess contribution reason code at  998 . Responsive to determining that the combined value does not exceed the threshold amount, the electronic transaction portal approves the transaction at  996  and proceeds to memo-post the transaction at  988 . 
     Responsive to determining that the electronic funding source is a WC HSA bank, the electronic transaction portal determines whether the transaction code of the electronic transaction request maps to one of the current year or previous year at  986 . Responsive to determining that the transaction code maps to one of the current year or the previous year, the electronic transaction portal continues to execute the an enforcement engine at  990  (e.g., continues to action  916  of  FIG.  9 A , etc.). Responsive to determining that the transaction code does not map to one of the current year or the previous year, the electronic transaction portal memo-posts the transaction at  988 . 
     Referring now to  FIGS.  10 A- 10 D , block diagrams depicting embodiments of transaction enforcement portal interfaces for managing electronic transaction requests are shown. The interfaces can be executed on a server. The interfaces can include or be executed on system  700 , TEPS  708 , or one or more components thereof. The interfaces illustrated in  FIGS.  10 A- 10 D  allow the TEPS  708  to interact with various entities for managing electronic transaction requests, such as servers of insurance administrators, employers, and financial institutions.  FIG.  10 A  illustrates a system  1000  including a bank instance  1004  in which a financial institution entity (e.g., a bank entity) can manage electronic transactions related to electronic benefits accounts and electronic funding transaction requests.  FIG.  10 B  illustrates a system  1068  in which a product partner module  1072  can manage electronic benefits accounts, including updating electronic benefits accounts responsive to electronic transaction requests.  FIG.  10 C  illustrates a system  1096  in which a third party administrator module  1100  can manage electronic benefits accounts, such as for allowing an employer entity to manage electronic benefits accounts provided to employees.  FIG.  10 D  illustrates a system  1132  in which a financial institution entity can manage electronic financial accounts using a bank settlement module  1136 , such as via financial modules  1140   a - k , responsive to a net settlement request. Each of the systems  1000 ,  1068 ,  1096 , and  1132 , and/or the bank instance  1004 , the product partner module  1072 , the third party administrator module  1100 , and the bank settlement module  1136  can include communications interfaces configured to receive and transmit one or more data packets carrying electronic transaction amongst each other, such as for updating relevant databases and modules responsive to adjudication of a request to initiate a single electronic benefits account transaction. 
     Referring now to  FIG.  10 A , and in further detail, a system  1000  is shown in which an entity of a financial institution, such as a bank, can interface with the TEPS  708 . For example, a bank instance  1004  can be provided on the TEPS  708  as an electronic interface between the TEPS  708  and the bank entity. The bank instance  1004  can be provided as an extension of the TEPS  708  to be executed by a server of the bank entity. The bank instance  1004  allows the bank entity to process electronic transaction requests, 
     The bank instance  1004  includes an HSA custodian  1028  configured to manage transactions between individual HSA accounts  1032  and transaction modules such as settlement accounts module  1008 , ledger accounts module  1012 , transaction codes module  1016 , product partner HSA status codes module  1020 , and accumulator module  1024 . Responsive to the bank instance  1004  processing an electronic transaction request to transfer funds, the bank instance  1004  can update a settlement account maintained by the settlement accounts module  1008  and a ledger account maintained by the ledger accounts module  1012  corresponding the electronic benefits account, and transmit the transaction amount (if approved) to the accumulator module  1024  in order to update the total amount of funds maintained by the electronic benefits account. 
     The HSA custodian  1028  can be configured to manage a demographics module  1040  and a products ID module  1044 . The demographics module  1040  can store or otherwise maintain demographics data regarding the bank entity. The products ID module  1044  can store or otherwise maintain electronic financial products provided by the bank entity, such as HSA products. The products ID module  1044  can manage service charges module  1048   a  and interest plan module  1048   b . In some embodiments, the service charges module  1048   a  and interest plan module  1048   b  can allow the bank entity to provide custom financial products. For example, the bank entity can provide an electronic benefits account having a specific service charge per transaction. When the TEPS  708  processes an electronic transaction request, the bank instance  1004  can process an indication of the electronic benefits account associated with the electronic transaction request, identify a product ID based on the electronic benefits account, and perform a lookup in the service charges module  1048   a  in order to identify a service charge to apply with the electronic transaction. 
     The bank instance  1004  can include an HSA account accumulator module  1052 . The HSA account accumulator module  1052  can be similar to or identical to the accumulator module  1024 . When the accumulator module  1024  or the HSA account accumulator module  1052  receive an electronic transaction for transferring funds to the electronic benefits account, each module can generate one or more data packets carrying an indication of the transaction amount to transmit to the other module, in order to maintain updated transaction amounts for the electronic benefits account. 
     In some embodiments, responsive to the TEPS  708  approving an electronic transaction request to fund the electronic benefits account, the HSA account transactions module  1036  can transmit instructions to an HSA check events module  1008  to generate instructions causing a remote entity to generate or print a check. For example, the HSA check events module  1008  can generate instructions including the transaction amount to a remote client device  1060 , causing a print checks module  1064  of the remote client device  1060  to receive the instructions, extract the transaction amount from the instructions, and generate or print the check. 
     In some embodiments, responsive to a transaction causing the ledger accounts module  1012  to update a ledger account associated with an electronic benefits account, the ledger accounts module  1012  can generate one or more data packets carrying an indication of the transaction amount and an indication of a financial product associated with the transaction. The ledger accounts module  1012  can transmit the one or more data packets to one of a bank instance financial module  1056   a - k  configured to store information regarding bank financial products. The bank instance  1004  can be configured to generate one or more data packets carrying a net settlement of one or more bank financial products responsive to the bank instance financial modules  1056   a - k  receiving a transaction indication from the ledger accounts module  1012 . For example, the ledger accounts module  1012  can transmit one or more data packets carrying an indication to transfer funds from a payroll deposit account maintained by the payroll deposit module  1056   g  to a debit card maintained by the debit card module  1056   e . The bank instance financial modules  1056   a - k  can receive the indication of the funds to be transferred, subtract the transaction amount from the payroll deposit account, and add the transaction amount to the debit card account. In some embodiments, the bank instance financial modules  1056   a - k  can generate one or more data packets carrying an indication of the net settlement performed at the bank instance  1004  to be transmitted to a remote server of a financial institution in order to update the remote server regarding the transaction performed. 
     Referring now to  FIG.  10 B , and in further detail, a system  1068  is shown in which a product partner can interface with the TEPS  708  to remotely manage electronic transactions for electronic benefits accounts. The system  1068  can be executed on or as part of a server of a remote product partner entity, such as an insurance administrator server. The system  1068  can include a product partner module  1072  configured to communicate with the system  700 , the TEPS  708 , the bank instance  1004 , or components thereof. The product partner module  1072  can include a product partner interface  1080  for communicating with remote entities and managing electronic transactions. The product partner interface  1080  can include a user interface configured to receive user inputs indication electronic transaction requests. The product partner module  1072  can include modules or databases for maintaining information regarding electronic benefits accounts, including product partner transactions codes  1084  (e.g., transaction codes mapping electronic benefits account transactions to one of a current year or a previous year; transaction codes mapping transaction information to human-readable output, etc.); product partner HSA status codes  1088  (e.g., statuses of electronic transactions such as pending, in-process, posted, etc.); and product partner product IDs  1092  (e.g., IDs indicating a type of electronic financial product, such as an FSA, etc.). 
     Referring now to  FIG.  10 C , and in further detail, a system  1096  is shown in which a third party administrator (TPA) can interface with the TEPS  708  to remotely manage electronic transactions for electronic benefits accounts. The system  1096  can be executed on or as part of a server of a remote TPA entity, such as an employer administrator server. The system  1096  can include a TPA module  1100  configured to communicate with the system  700 , the TEPS  708 , the bank instance  1004 , the product partner module  1072 , or components thereof. The TPA module  1100  can include a TPA interface  1116  configured to manage electronic transactions. The TPA interface  1116  can include a user interface configured to display information maintained by the TPA module  1100  to a user and receive user inputs from a user. The TPA module  1100  can include an employers module  1120  configured to manage information regarding one or more employers. The one or more employers managed by the employers module  1120  can correspond to one or more employees managed by an employees module  1104 . Each employee corresponds to one HSA account managed by an HSA account module  1108 . Each HSA account managed by the HSA account module  1108  can transmit and receive one or more HSA transactions managed by the HSA transaction module  1112 . Each employer managed by the employers module  1120  can provide a plurality of HSA plans managed by an HSA plan module  1124 . The TPA module  1100  can store information regarding product IDs for each HSA plan in a product IDs module  1128 . The TPA module  1100  can include a communications interface configured to receive and transmit one or more data packets from each of the bank instance  1004  and the product partners module  1072 , and components thereof. 
     Referring now to  FIG.  10 D , and in further detail, a system  1132  is shown in which a financial institution entity (e.g., a bank entity) can locally manage electronic financial accounts. The system  1132  includes a bank settlement module  1136  including a plurality of financial modules  1140   a - 1140   k , such as payroll deposits module  1140   a , external account  1140   b , service charges/fees module  1140   c , lock box contributions  1140   d , HSA funds module  1140   e , accruals module  1140   f , interest module  1140   g , ACH module  1140   h , bill pay module  1140   i , debit card module  1140   j , and manual claim module  1140   k . Responsive to receiving net settlement requests generated by and transmitted from the bank instance  1004 , the bank settlement module  1136  can be caused to process the net settlement request, extract an indication of an electronic financial account associated with the request and a transaction amount, and update the corresponding electronic financial account based on the transaction amount. For example, the bank instance  1004  can transmit a net settlement request including an indication of an electronic benefits account and an interest charge transaction amount to the bank settlement module  1136 , causing the bank settlement module  1136  to extract the interest charge transaction amount and update the corresponding electronic benefits account interest charges maintained by the interest module  1140   g . As such, in some embodiments, the financial modules  1140   a - 1140   k  can be configured to mirror the bank instance financial modules  1056   a - k  shown in  FIG.  10 A . 
     The bank instance  1004 , the product partners module  1072 , and the TPA module  1100  can each include communications interfaces configured to receive and transmit one or more data packets from each other, such as one or more data packets configured to indicate electronic transaction requests, electronic transaction processings, and information regarding electronic benefits accounts. For example, the product partners module  1072  can receive and transmit information regarding settlement accounts with the bank instance  1004 , such as for mirroring information stored in the settlement accounts module  1008  and the product partners settlement account module  1076 . Similarly, the product partners module  1072  and the TPA module  1100  can receive and transmit information regarding product IDs in order to share and mirror information stored in the product partners ID module  1092  and the product ID module  1128 . The TPA module  1100  can receive and transmit information regarding electronic transactions in order to share and mirror information stored in the HSA accounts module  1032  and the HSA account module  1108 , and to share and mirror information regarding electronic benefits transactions stored in the HSA account transactions module  1036  and the HSA account transaction module  1112 . 
     In some embodiments, responsive to the TEPS  708  denying an electronic transaction request to transfer funds to an electronic benefits account and generating an alert indicating the denial, the bank instance  1004  can update the HSA account module  1032  and the HSA transactions module  1036  for the electronic benefits account corresponding to the electronic transaction request to indicate that the electronic transaction request was denied. The bank instance  1004  can generate one or more data packets carrying an indication of the electronic benefits account and an indication of the denial to be transmitted to the TPA module  1100 . The TPA module  1100  can process the one or more data packets to extract the indications, and perform a lookup in the modules  1108  and  1112  in order to identify corresponding entries for the electronic benefits account to update the modules  1108  and  1112  by writing the transaction denial to the corresponding entries. 
     In some embodiments, responsive to the TPA module  1100  generating a new HSA plan entry in the HSA plan module  1128 , the TPA module  1100  is configured to request a product ID for the new HSA plan. The TPA module  1100  can generate one or more data packets carrying the product ID request including an indication of the HSA plan, and transmit the one or more data packets to the product partners module  1072 . The product partners module  1072  can process the one or more data packets to extract the product ID request and the indication of the HSA plan, perform a lookup in the product partners ID module  1092 , extract the product ID corresponding the new HSA plan, and generate and transmit one or more data packets including the corresponding product ID to the TPA module  1100 . 
     E. Administrator Matching and Report Generating System (AMRGS) 
     The systems and methods of the present solution are directed to the technical problems and challenges of implementing the functionality of managing or generating an interface of an electronic transaction based technology and platform. Existing electronic transaction based technologies and platforms do not effectively and efficiently make use of the computing and network resources deployed for interface based technologies and platforms to include such functionality. Without implementing such functionality, existing electronic transaction based technologies and platforms have the problems of excessive server-client requests and responses, processing delays, increase bandwidth usage, or erroneous reports or interfaces. 
     The systems and methods of the present solution are directed to the improvement of the performance and operation of the electronic transaction based technology and platform and computing and networking resource used by such electronic transaction based technology and platform. In some aspects, the present solution improves and enhances the implemented functionality of the electronic transaction based technology and platform implemented on, integrated with and inherently tied to the processor, memory, network and computing resources of one or more computing devices. In some aspects, the present solution more effectively performs the functionality of the electronic transaction based technology and platform thereby making and causing more effective use of the computing and networking resources to achieve the improved functionality of the present solution. The same computing and network resources used by such electronic transaction based technology and platform will provide increased and improved functionality with implementation of the present solution. 
     In some aspects, the present solution more efficiently uses the computing and networking resources to implement the improved functionality of the electronic transaction based technology and platform. For example, systems and methods of the present solution can use an administrator matching and report generating system with respect to information regarding electronic accounts, such as an electronic benefits account. Systems and methods of the present solution can generate dynamic reports including multiple performance metrics based on similar administrators. 
     Administrators that establish or provide electronic tax benefits accounts can utilize backend information technology infrastructure to process, analyze, monitor or manage the electronic tax benefits accounts. An entity managing the backend information technology may have access to data regarding electronics tax benefit accounts across multiple administrators. This data may include the different parameters associated with respective electronic benefits accounts of the different administrators. As examples of parameters, one administrator may have a higher monthly fee compared with another administrator, or may set a higher minimum balance to be maintained compared to another administrator. Some administrators can change parameters associated with their accounts, for example, to increase the number of participants that use their accounts. 
     The present disclosure provides systems and methods of managing information technology to generate a dynamic interface. The dynamic interface can include a dynamic report based on analyzing peer administrators. For example, the system can provide benchmarking information on a predefined set of administrative indicators and enable administrators to manipulate parameters to compare their performance to similar administrators. The system can further allow an administrator to manipulate the data to further stratify the data on various industry measures and determine how their performance compares with the stratified data. 
     The system can be configured with an administrator matching technique to identify peer or similar administrators. Peer administrator may refer to administrators having characteristics, features, or parameters that satisfy a matching or similarity criterion or criteria using a matching technique. The matching technique can include a comparison function, a machine learning technique, a statistical technique, correlation techniques or cross-referencing techniques. For example, the matching technique can compare parameters associates with electronic tax benefit accounts between two or more administrators to identify two or more administrators having similar parameters. In some cases, the matching technique can include assigning weights to parameter such that a first parameter may have a higher weight than a second parameter and a third parameter. For example, with this weighting structure, the system can determine that a first administrator is similar to a second administrator if the first parameter with the highest weight matches between the first and second administrators, even though the second and third parameters do not match. In another example, the system may determine that two administrators are not similar because the first parameter with the highest weight does not match, even though the second and third parameters with lower weights do match. 
     Upon identifying similar administrators using one or more matching techniques, the system can generate a dynamic report. The dynamic report interface can include or be configured on a dashboard. In some cases, the dynamic report interface can be provided or streamed over a data network. The dynamic report interface can be configured to receive data manipulation indications via an input device. For example, the interface can receive indications to manipulate the data for a different time period, based on size of the administrator, geographic location of the administrator (or the administrator&#39;s customers), number of years in operation, marketing budget, number of employees, demographics, industry sectors, revenue, profit, expenses, types of electronic accounts, types of transaction configurations, funding sources, interest rate, or any other parameter that facilitates generating a dynamic report. 
     In an illustrative embodiment, the system can provide payment processing infrastructure and technology to an administrator such as an insurance company. The insurance company can provide various types of insurance (e.g., health, dental, vision, car, property, legal, construction, etc.) to its customers. A customer of the insurance company can include an employer that has employees. The system can enable the insurance company to generate a dynamic report to identify similar administrators and their performance. The insurance company can, for example, set parameters for: opening fee, minimum operating balance, monthly fee, annual fee, investment options, fund access type (e.g., checkbook, debit card). Parameters could also include interest rate, contribution from employer; how invest funds (e.g., investment bank funds, equity investing, mutual funds, or money market accounts). 
     The dynamic report can indicate a level of performance of the insurance company as well as how the insurance company&#39;s level of performance compares or relates to the identified similar administrators. Performance indicators can include, for example, success of investments, number of users, number of employers, percentage of employees per employer using a tax benefit account and amount of contributions. In some cases, the system can aggregate data among multiple similar administrators and display the aggregated data in the dynamic report in an anonymized data format. In some cases, manipulating parameters used to generate the dynamic report can cause the system to re-execute the matching technique and identify a different set of similar administrators based on the new parameters. The system can then regenerate, manipulate, or otherwise update the report provided by the dynamic report interface using the new set of similar administrators. 
     Referring now to  FIG.  11   , a block diagram depicting an embodiment of a system for managing information technology infrastructure. In brief overview, and in some embodiments, the system  1100  includes an administrator matching and report generating system  1150  (“AMRGS”). The AMRGS  1150  can include the MPTS  408  depicted in  FIG.  4    or the TEPS  708  depicted in  FIG.  7   , or one or more components, modules or functionality depicted in  FIG.  4    or  FIG.  7   , and can perform the functions of the MPTS  408  or the TEPS  708 . The AMRGS  1150  can receive or transmit data via a network  104  with clients  102   a - n , POS terminals  202   a - n , and administrator devices  1160   a - n . The system  1100  can include or interact with one or more clients  102   a - n  (or client device  102 ), one or more point-of-sale (POS) terminals  202   a - n  (or POS terminal  202 ), and one or more administrator devices  1160   a - n  (or administrator device  1160 ). 
     The AMRGS  1150  can include a communications interface  1152 . The communications interface  1152  can include the communications interface  410  depicted in  FIG.  4    or the communications interface  710  depicted in  FIG.  7   , or one or more components or modules depicted in  FIG.  4    or  FIG.  7   , and can perform the functions of the communications interface  210  or the communications interface  710 . In some aspects, the communications interface  1152  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, the communications interface  1152  is implemented to make or cause more effective and efficient use of computing and networking resources. For example, the communications interface  1152  can cause more effective and efficient use of computing and network resources by reducing the number of processing cycles, memory or network bandwidth used to generate dynamic interfaces or reports. The communications interface  1152  can provide an improved generation of a dynamic interface or reports by integrating with the admin matching engine  1154 , database  1158 , report generator  1156 , claims processor  220 , POS terminals  202   a - n , or clients  102   a - n  to generate dynamic interfaces or reports. 
     The communications interface  1152  is configured with one or more communications ports, application programming interfaces, network protocols (e.g., TCP/IP), authentication protocols, or security protocols (e.g., SSL). The communications interface  1152  can receive a request to match an administrator associated with the administrator device  1160  with other administrators similar to the matched administrator. In addition, the communications interface  1152  can receive a request to generate a dynamic report including performance metrics associated with the similar administrators. In some cases, the AMRGS  1150  can generate and process the request to identify similar administrators responsive to receiving a request to generate a report. 
     The AMRGS  1150  can include a matching engine  1154 . The matching engine  1154  can include the policy engine  412  depicted in  FIG.  4    or the enforcement engine  712  depicted in  FIG.  7   , or one or components or modules depicted in  FIG.  4    or  FIG.  7   , and can perform the functions of the policy engine  412  or the enforcement engine  712 . The matching engine  1154  identifies, responsive to the communications interface  1152  receiving the request to match an administrator with one or more similar administrators or receiving an identifier of an administrator, one or more administrator profiles that are similar to the administrator requesting the match or sending the identifier. In some aspects, the matching engine  1154  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, the matching engine  1154  is implemented to make or cause more effective and efficient use of computing and networking resources. For example, the matching engine  1154  can cause more effective and efficient use of computing and network resources by reducing the number of processing cycles, memory or network bandwidth used to generate matches. The matching engine  1154  can provide an improved generation of a match by integrating with the communications interface  1152 , database  1158 , report generator  1156 , claims processor  220 , POS terminals  202   a - n , or clients  102   a - n  to generate the match. 
     The AMRGS  1150  can include a report generator  1156 . The report generator  1156  can include the transaction engine  414  depicted in  FIG.  4   , or one or more components or modules depicted in  FIG.  4   , and can perform the functions of the transaction engine  414 . The report generator  1156  generates a dynamic report including one or more performance metrics associated with the one or more similar administrators identified by the matching engine  1154 . The report generator  1156  can generate a dynamic report and transmit one or more data packets carrying data indicating the report to an administrator device  1160  via the communications interface  1152  and the network  104 . In some aspects, the report generator  1156  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, the report generator  1156  is implemented to make or cause more effective and efficient use of computing and networking resources. For example, the report generator  1156  can cause more effective and efficient use of computing and network resources by reducing the number of processing cycles, memory or network bandwidth used to generate dynamic interfaces or reports. The report generator  1156  can provide an improved generation of a dynamic interface or reports by integrating with the admin matching engine  1154 , database  1158 , communications interface  1152 , claims processor  220 , POS terminals  202   a - n , or clients  102   a - n  to generate dynamic interfaces or reports. 
     The AMRGS  1150  can include one or more databases or data structures that store information to facilitate the systems and methods of the present solution, such as database  1158 . The database  1158  can include the database  418  or the databases  714  or  716 , or one or more components or modules depicted in  FIG.  4    or  FIG.  7   , and can perform the functions of the databases  418 ,  714 , or  716 . The database  1158  (or administrator profile) can include an administrator profile associated with an administrator maintained on or configured on the AMRGS  1150  that is associated with one or more parameters and one or more performance metrics. The parameters can include various characteristics and attributes associated with an electronic benefits account, such as, but not limited to, an account opening fee, a minimum operating balance, a monthly fee, an annual fee, an electronic fund access type, an interest rate, or the like. The performance metrics can include various resulting characteristics and attributes associated with an electronic benefits account, such as, but not limited to, percentage or number of participants of an electronic benefits account associated with a given administrator profile, amount of money contributed to an electronic benefits account associated with a given administrator profile, or the like. The database  1158  can include a profile database of the administrators. The profile database can include an entry corresponding to an administrator profile that may point to entries or values in the parameters and performance metrics databases associated with that particular administrator profile. The entry can include a unique identifier for the administrator. 
     The AMRGS  1150 , communications interface  1152 , matching engine  1154 , and report generator  1156  can each include one or more processing units or other logic devices such as programmable logic array engines, modules, or circuitry designed and constructed to facilitate managing security on a network infrastructure. The AMRGS  1150  can include the components  100  shown in  FIG.  1 C  or  FIG.  1 D , or be configured to operate as a service in cloud  108 . The  1108  can include or interact with one or more servers  106   a - n  and clients  102   a - n.    
     In some embodiments, the AMRGS  1150  can employ a multitier architecture such as a client-server architecture in which presentation, application processing, and data management functions are logically or physically separated. The presentation tier, or front-end, can include the communications interface  1152  that serves static content or dynamic content to be rendered by the client  102  or by the administrator device  1160  (e.g., by a web browser executing on client  102  or administrator device  1160 ). The presentation tier or web server  210  can interact or communicate with the application tier to obtain data to provide to the client  102 , POS terminals  202   a - n , or administrator device  1160 . The application tier can include the matching engine  1154  and the report generator  1156  that controls the system&#39;s functionality and performs additional processing or analysis on data. The application tier can interact with the data tier to obtain the transaction data. The data tier can include data persistence mechanisms (database servers, file shares, etc.) and the data access layer that encapsulates the persistence mechanisms and exposes the data. The data tier can include database  1158 . The data tier can include an application programming interface (API) to the application tier. The database  1158  can include stored procedures (e.g., SQL statements) that perform tasks with respect the stored data. 
     In further detail, and in some embodiments, the AMRGS  1150  includes a communications interface  1152 . The communications interface  410  can execute on one or more processors of a server. The communications interface  1152  can include one or more communications ports and be configured with one or more network protocols. Communications ports can include, e.g., network ports, Ethernet ports, WAN ports, I/O ports, or software ports. The communication port can be configured with a network protocol such as Transport Layer Protocols such as TCP/IP or UDP that are configured to receive and process data packets received via a computer network. The port can include or be associated with an IP address of a host and a protocol type of the communication. 
     In some embodiments, the communication interface  1110  can receive data packets. The data packets can be generated by a device at an administrator to request matching or a dynamic report. The device can refer to an administrator device (“administrator device”) such as administrator device  1160 . The administrator device  1160  may monitor data from the various electronic benefits accounts associated with the administrator. The accounts associated with the administrator may be accounts that are managed or maintained by the administrator. The administrator may be a point of contact for customers or participants of the associated accounts. In some embodiments, the client  102 , which may correspond to an individual participant of the administrator&#39;s electronic benefits account, may access the account and perform a number of actions with respect to the account, such as, fund the account (e.g., via heterogeneous electronic funding sources  702 ), withdraw from the account, charge the account, and the like. The administrator of the electronic benefits account, as the caretaker of the account, may adjust parameters associated with the account, such as, monthly fees, minimum running balances, etc. At the same time, the AMRGS  1150  may monitor the data, parameters, and performance of the account and store the information under an administrator profile associated with the administrator of the account. The AMRGS  1150  may receive the data associated with the individual participants and their individual accounts from the client&#39;s  102  and the parameter data associated with the accounts from the administrator device  1160  via the network  104 . 
     An administrator device  1160  is the place where an administrator may perform various functions of the administrator, for example, functions associated with electronic benefits accounts of the administrator. The administrator device  1160  is the point at an administrator may send requests to the AMRGS  1150  for generating a dynamic report. The administrator device  1160  may also be configured to transmit an identifier associated with the administrator corresponding to the administrator device  1160  for identification by the AMRGS  1150 . In some embodiments, the receiving of the identifier initiates the dynamic report generating process. 
     The administrator device  1160  can include hardware and software. Administrators can utilize scanners, EFTPOS terminals, touch screens and any other wide variety of hardware and software available for use with administrator device  1160 . For example, an administrator can use software to make adjustments to parameters associated with their electronic benefits accounts. 
     The administrator device  1160  can include advanced features to cater to different functionality, such as account participant forecasts and estimates, account simulation, communication with participants of accounts, performing actions associated with individual participant accounts (e.g., freezing an account), collecting data from one or more of the participant accounts, etc., all built into the administrator software. The administrator device  1160  can be configured to execute user-input commands with respect to the electronic benefits accounts of the administrator. 
     The communications interface  1152  can receive data packets generated by the administrator device  1160  responsive to a user command resulting in transmission of a request to perform administrator matching or generate a dynamic report. The data packets can include header information and payload information. Multiple data packets can be strung together in a sequence. The header information can refer to TCP/IP headers that include fields such as source port, destination port, sequence number, acknowledge number, window size, etc. The payload information of the data packet can include information related to the request, the request to match or generate a report, an identifier of the administrator of the administrator device  1160 , parameters associated with the requesting administrator, parameters adjusted by the administrator, and other information facilitating administrator matching and report generation. For example, with respect to the request for administrator matching, the payload information may include an identifier of the administrator sending the request. In response to receiving the identifier, the AMRGS  1150  can access the database  1158  to retrieve the administrator profile corresponding to the identifier, and may further access parameters and performance metrics associated with the retrieved administrator profile. The administrator profile can further include information associated with the administrator, such as, but not limited to, the number of employees or potential participants of electronic benefits accounts under the administrator, a geographic location of the administrator, geographic locations of participants associated with the administrator, size and location of employers associated with the administrator, and other information associated with the administrator. In other embodiments, the payload information of the data packet may include information associated with the requesting administrator. Furthermore, with respect to the request for generation of a dynamic report, the payload information may include an identifier of the administrator sending the request. In response to receiving the identifier, the AMRGS  1150  can access the database  1158  to retrieve the administrator profile corresponding to the identifier, and may further access parameters and performance metrics associated with the retrieved administrator profile. The parameters associated with the accessed administrator profile may include characteristics of the electronic benefits accounts of the administrator, such as, but not limited to, an account opening fee, a minimum operating balance, a monthly fee, an annual fee, an electronic fund access type, or an interest rate. In other embodiments, the payload information of the data packet may include the parameters. For example, a user of the administrator device  1160 , instead of relying on the parameters already associated with the stored administrator profile, may modify the administrator parameters to receive a dynamic report based on modified parameters, and send those modified parameters to the AMRGS  1150  as part of the request for generating a dynamic report. The AMRGS  1150  can receive the data packet with header information and payload information and process the packets to obtain information for further processing. The data packets (e.g., via the payload) can include the request to perform matching or generate a dynamic report. 
     The data packets can carry data identifying an administrator. In some embodiments, the data carried by the data packets include an administrator identifier. The administrator identifier can include strings, characters, numbers, alphanumeric characters, symbols, or other identifiers. In some embodiments, the data identifies a merchant, and the AMRGS  1150  determines an administrator profile based on the identification of the administrator. The AMRGS  1150  can determine the administrator profile by, for example, using an administrator mapping or lookup table stored in database  1158 . In some embodiments, the data packets carrying the request to identify matching administrators and generate a dynamic report includes a data structure having a first field indicating an administrator identifier and a second field indicating values of one or more parameters associated with electronic benefits accounts. In some embodiments, the data packets are generated by an administrator device  1160  when requesting matching and a report, and the data packets carry data identifying an administrator profile including information pertaining to the requesting administrator and the parameters. 
     The data packets (e.g., payload of the data packets) can further identify an administrator profile maintained and configured on the server. The administrator profile can be maintained and configured in a database  1158 . The administrator can correspond to an administrator profile and have a unique identifier. The unique identifier can include numbers, letters, characters, symbols, etc. The administrator can be associated with the administrator making the request at the administrator device  1160 . 
     The communications interface  1110  can further receive data packets (e.g., payload information) identifying parameters and values of those parameters pertaining to electronic benefits accounts, such as, but not limited to, an account opening fee, a minimum operating balance, a monthly fee, an annual fee, an electronic fund access type, an interest rate, and the like. In some embodiments, the values of the parameters received at the communications interface via the data packets may be modified or updated at the administrator device. Accordingly, the updated values of the parameters may be received at the AMRGS  1150  via the communications interface for operating on by the matching engine  1154  and the report generator  1156 . In such embodiments, the report generator  1156  may output results based on the updated values in real-time, and thus may generate dynamic reports based on updated values of parameters received from the administrator device  1160  in real-time. 
     In some embodiments, the administrator device  1160  can generate multiple data packets for a single request. The multiple data packets can each include a header and a payload. The header can indicate that the multiple data packets are to be grouped together for routing, transmission, or processing purposes. 
     The AMRGS  1150  can be configured to authenticate communications and requests. In some embodiments, the communications interface  1152  receives communications such as the request to identify similar or matching administrators and generate a dynamic report. The request can include security credentials such as a security certificate or security token. The security credentials can be associated with an administrator. The AMRGS  1150  can be configured to extract the security credential from the request, and authenticate the request by comparing the security credential against a known or verified security credential. For example, the user profiles or merchant information stored in database  1158  can include known or verified security credentials for comparison with the security credential of the request. In some embodiments, the AMRGS  1150  receives the request to generate a dynamic report via the communications interface  1152 , extracts a security credential from the request, analyzes the extracted security credential to identify an administrator, queries the database  1158  for a verified security credential stored with an administrator profile corresponding to the identified administrator, compares the extracted security credential to the verified security credential, and authenticates the request based on the extracted security credential matching the verified security credential. In some embodiments, the AMRGS  1150  analyzes the extracted security credential to identify an administrator, queries the database  1158  for a verified security credential stored with administrator information corresponding to the identified administrator, compares the extracted security credential to the verified security credential, and authenticates the request based on the extracted security credential matching the verified security credential. 
     In some embodiments, the AMRGS  1150  includes a matching engine  1154 . The matching engine  1154  can execute on one or more processors of a server, such as a server of the AMRGS  1150 . The matching engine  1154  can receive, retrieve, or otherwise obtain or access some or all of the data carried by the data packets. The matching engine  1154  can receive, retrieve, or otherwise obtain or access administrator profiles, such as administrator profiles maintained in database  1158 . The matching engine  1154  can determine one or more administrators that are similar (e.g., based on a similarity metric) or that match the administrator of the administrator device  1160 , responsive to the communication interface  1110  receiving the request to generate a dynamic report. 
     The AMRGS  1150  can initiate, launch, execute or perform a matching process responsive to receiving the data packets, such as by causing the matching engine  1154  to execute matching rules or logic maintained in the database  1158  or maintained in the matching engine  1154  itself. The AMRGS  1150  can cause the matching engine  1154  to identify an administrator profile maintained in the database  1158  identified by an identifier included in the received data packets. The AMRGS  1150  can cause the matching engine  1154  to determine that a remote administrator profile is required based on information extracted from the received data packets, and the AMRGS  1150  can request the remote administrator profile by transmitting one or more data packets carrying an administrator profile request to a remote server, such as a server of an insurance administrator or an employer. The administrator profile request can cause the remote server to transmit the requested remote administrator profile to the AMRGS  1150 . For example, the matching engine  1154  can determine that the received data packets indicate a new insurance administrator or employer for which an administrator profile is not yet maintained in the database  1158 . In some embodiments, the AMRGS  1150  receives in the data packets, along with the request to generate a dynamic report, the administrator profile of the requesting administrator at administrator device  1160 . The administrator profile may include information associated with the administrator, such as, but not limited to, the number of employees or potential participants of electronic benefits accounts under the administrator, a geographic location of the administrator, geographic locations of participants associated with the administrator, size and location of employers associated with the administrator, and other information associated with the administrator. 
     The matching engine  1154  can use any suitable logic or algorithm as a matching technique for identifying one or more administrator profiles that are similar to the administrator profile associated with the administrator device  1160  requesting a dynamic report. For example, the matching technique can include a comparison function that is a sorting algorithm that reads a list of elements through a single abstract comparison operation (e.g., “less than or equal to” operator or a three-way comparison) that determines which of two elements should occur first in the final sorted list. A requirement may be that the operator obey two of the properties of a total order. 
     As another example, the matching technique can include a machine learning technique that can learn from and make predictions on data. The machine learning can operate by building a model from example inputs in order to make data-driven predictions or decisions, rather than following strictly static program instructions. In some embodiments, inputs are divided into two or more classes (e.g., similar administrator profiles and not similar administrator profiles), and the learner produces a model that assigns unseen inputs to one (or multi-label classification) or more of these classes. 
     As another example, the matching technique can include a statistical analysis technique that includes a process or inspecting, cleaning, transforming, and modeling data. The statistical analysis can include one or more steps of data requirements, which identify data necessary as inputs to the analysis based upon requirements of those directing the analysis, data collection, data processing, and modeling and algorithms, which may be applied to the data to identify relationships among the variables, such as correlation and causation. Models may be developed to evaluate a particular variable in the data based on other variable(s) in the data. 
     As another example, the matching technique can include a correlation technique, which identifies a statistical relationship between two random variables or two sets of data. In some embodiments, measures of correlation to infer a presence or absence of association in a sample of data include one or more of an odds ratio, a risk ratio, an absolute risk reduction, distance correlation, tetrachroic correlation coefficient, mutual information, and the like. 
     As another example, the matching technique can include a cross-referencing technique. The cross-referencing technique may incorporate a database management system that follows a relational model. The database management system may use a table that has xref as a prefix or suffix to indicate it is a cross-reference table that joins two or more tables together via primary key. 
     In some embodiments, the matching engine  1154  retrieves the information included in the administrator profile associated with the requesting administrator device  1160 , and compares information of the administrator profile with the information of other administrator profiles stored in the database  1158  to determine a similarity metric between the requesting administrator profile and another given administrator profile. After determining a value of a similarity metric between the requesting administrator profile and another administrator profile, the matching engine  1154  may compare the determined value of the similarity metric to a predetermined similarity threshold, and if the similarity metric value meets or exceeds the similarity threshold, then the matching engine  1154  may flag that administrator profile as being similar to the requesting administrator profile. However, if the matching engine  1154  determines that the similarity metric value is below the similarity threshold, then the matching engine  1154  may not flag that administrator profile as being similar to the requesting administrator profile. 
     In some embodiments, the matching engine  1154  may determine the similarity metric based on the respective similarities of individual parameters included in the information of the administrator profiles (e.g., similarity in number of participants, proximity in locations, etc.). The matching engine  1154  may determine how many of the individual parameters meet or exceed the similarity threshold, and if enough of the individual parameters are sufficiently similar, then the matching engine  1154  may flag that administrator profile as being similar. 
     In some embodiments, the matching engine  1154  may allocate predetermined weightings to certain parameters of the administrator profiles based on how important some parameters are compared to others for the similarity analysis. For example, the parameter of number of employees or participants of an administrator may be weighted heavier than the parameter of location proximity in the similarity analysis of the matching engine  1154 . In some embodiments, the respective weightings associated with individual parameters may be modified at the administrator device  1160  depending on a preference of the administrator associated with the administrator device  1160 . 
     In some embodiments, the matching engine  1154  performs the similarity analysis for each administrator profile in the database  1158  to determine one or more administrator profiles similar to the requesting administrator profile. The one or more similar administrator profiles may be a subset of the total administrator profiles stored in the database  1158 . In some embodiments, the matching engine  1154  performs the similarity analysis on a subset of the total administrator profiles. For example, as an initial step, the matching engine  1154  may filter out some of the administrator profiles in the database  1158  that are easily exclude from the analysis, such as an administrator profile that has previously flagged as inactive. In some embodiments, a user at the administrator device  1160  may input a filter, and in response to the received filter information (e.g., via data packets), the matching engine  1154  may exclude administrator profiles from similarity analysis that are excluded due to the filter. For example, a user may input a filter indicating a desire to target administrator profiles that are less than five years old, in which case the matching engine  1154  may perform the similarity analysis only on those administrator profiles that satisfy the filter criteria. 
     In some embodiments, the matching engine  1154  may output an indication of the results of its similarity analysis and the findings of the one or more similar administrator profiles to the administrator device  1160 . The indication may provide a list of the administrators that are determined to be similar to the requesting administrator profile. In some embodiments, the AMRGS  1150  may not provide the list or anonymize the list such that an administrator cannot uniquely identify the similar administrators. For example, the AMRGS  1150  can aggregate the performance data of the identified set of similar administrators to anonymize the data. In some embodiments, the AMRGS  1150  can rename or redact a unique identifier of the similar administrators, and include the false name or a random identifier in the list. In some embodiments, the list of profiles may include a similarity score next to respective administrators for indicating the degree of similarity between the requesting administrator and the listed administrator. The similarity score may be determined by matching engine  1154  based on a matching technique. In some cases, the similarity score may be based on how much a given administrator exceeds the similarity threshold. The listed profiles may be ranked by their respective similarity scores. The similarity score can include a numeric score, word, phrase, color, symbol, grade, percentage or other indicator of similarity. The similarity score can be on a scale or include a range, such as 0 to 10 or 0 to 100, with 0 being least similar and 10 or 100 most similar (or 0 most similar and 10 or 100 least similar). The grade can include A to F, with A indicating most similar and F indicating least similar. In some cases, the numeric score can be on a logarithmic scale. 
     In some embodiments, the AMRGS  1150  trains an administrator profile model using one or more administrator profiles stored in the database  1158 . In some embodiments, the AMRGS  1150  inputs a parameter of an administrator profile into the administrator profile model to determine values of the performance metrics. The AMRGS  1150  may utilize the constantly updated profiles of the stored administrator profiles to extrapolate data and to formulate the model based on the updated profiles. For example, the model can include performance data for various time intervals or time periods, sizes, interest rates, etc. If the administrator sets the time interval from January to October 31, the system can input this time interval into the model to determine the performance (e.g., rate of return on investment or number of customers) during this time interval. In another example, the parameter can be a number of customers, and the system can input this into the model to determine one or more time interval during which this parameter is satisfied, and generate a report indicating the performance (e.g., rate of return on investment) whenever the administrator had this many customers. 
     In some embodiments, the matching engine  1154 , after identifying the one or more similar administrator profiles, can send an indication of the one or more similar profiles to the report generator  1156 . The report generator can utilize the one or more similar profiles in generating a dynamic report. 
     The AMRGS  1150  can include a report generator  1156 . The report generator  1156  can execute on one or more processors of a server. The report generator  1156  can generate a dynamic report, responsive to receiving the indication of the one or more similar administrator profiles from the matching engine  1154 . The dynamic report may be based on the one or more similar administrator profiles. 
     The report generator  1156  may access from the database  1158  the performance metrics information corresponding to each of the one or more similar administrator profiles. The performance metrics can include various resulting characteristics and attributes associated with an electronic benefits account, such as, but not limited to, percentage or number of participants or customers of an electronic benefits account associated with a given administrator profile (e.g., during a defined time interval), amount of money contributed to an electronic benefits account associated with a given administrator profile, number of geographic regions in which their customers are located, demographics data associated with customers, number of transactions associated with tax benefit accounts, size of the transactions, frequency of transactions, frequency of funding the tax benefit account, size of contributions, or statistics based on these parameters, performance metrics, or attributes. Values of the performance metrics may vary dependent on the parameters associated with the electronic benefits accounts. For example, an electronic benefits account may include a monthly fee (parameter) with a value of $5 and have a participation percentage (performance metric) with a value of 74%. In another example, an electronic benefits account may include a monthly fee of $10 and have a participation percentage of 86%. Accordingly, due to the lower fee associated with the first account, a higher rate of participation is achieved compared with that of the second account, since lower fees likely encourage participation. 
     The report generator  1156  may compile the values of the performance metrics of the one or more similar administrator profiles. In some embodiments, the report generator  1156  may average all the values of the similar profiles associated with a performance metric. In some embodiments, the report generator  1156  may simply retrieve the individual values of the performance metric without performing any operations on the values. In some embodiments, the report generator  1156  may perform a weighted average on the values of a performance metric, and assign certain ones of the similar profiles respective weightings. The weightings may be based on particular characteristics of the administrator profiles. For example, ones of the similar profiles that exceed the similarity threshold relatively higher than others may receive a higher weighting than those that barely meet the similarity threshold. 
     The report generator  1156  can transmit one or more packets carrying data indicating the results of the report generator  1156  to the administrator device  1160  for displaying a dynamic report including the information determined by the report generator  1156 . In some embodiments, the dynamic report may also display values of performance metrics associated with the requesting administrator, such that the administrator may compare its performance metrics with those of the one or more similar administrators. 
     In some embodiments, the report generator  1156  can update the report sent to the administrator device  1160  in real-time in response to an adjusted parameter at the administrator device  1160  and received at the AMRGS  1150 . For example, the report generator  1156  may generate a report based on the default parameters associated with the requesting administrator profile. The default parameters may correspond to the actual live parameters that the requesting administrator uses with respect to its electronic benefits accounts. However, in some embodiments, the generated dynamic report at the administrator device  1160  displays the parameters used in the report generator  1156  processes, and the user of the administrator device  1160  may adjust these parameters. In response to an adjusted parameter, the matching engine  1154  may identify a new set of similar administrator profiles and transmit the identification information to the report generator  1156 . In response to the new set of similar administrator profiles, the report generator  1156  may retrieve and operate on a new set of values of performance metrics associated with the new set of profiles, and generate a new report based on the new set of performance metric values. This process of dynamic reporting based on administrator adjustments to input parameters may occur in real-time. For example, an administrator may adjust a time interval associated with a number of participants metric of the administrator at the administrator device  1160  (e.g., from 1 year to 2 years), in doing so, the report generator  1156  may determine different values for the various performance metrics and display these updated values via the dynamic report. 
     In some embodiments, the administrator device  1160  may transmit filter information to the AMRGS  1150  via the dynamic report interface at the device  1160 . In response, the AMRGS  1150  may identify a subset of the one or more similar administrator profiles stored in the administrator profile database  1158 . Accordingly, the report generator  1156  may generate new values for the performance metric based on the new set of administrator profiles and render the electronic report to indicate the new values of the performance metrics while removing the values associated with the previous set of administrator profiles used before the filter was implemented. 
     In some embodiments, the report generator  1156  can be configured to provide the dynamic report in real-time via the communications interface  1152 . The communications interface  1152  can be configured to provide the report via an electronic mail protocol, SMS protocol, notification or prompt on a mobile telecommunications devices (e.g., a smartphone, tablet, smartwatch, wearable telecommunications device, laptop computer, desktop computer, etc.). An administrator profile maintained in the database  1158  can include other contact information corresponding to the administrator associated with the administrator device  1160 , and the report generator  1156  can be configured to transmit the one or more data packets including the report to the administrator using the contact information via the communications interface  1152 . In some embodiments, the administrator profile can include a priority order associated with multiple contact information, a preferred contact information, or an indication of multiple contact information for receiving notifications. For example, the administrator profile can indicate an electronic mail protocol as a preferred contact information, and the report generator  1156  can be configured to identify the electronic mail protocol as the preferred contact information, and transmit the one or more data packets to the administrator using the electronic mail protocol via the communications interface  1152 . 
     The report generator  1156  report delivery can be in real-time. A real-time report can refer to providing the notification soon after completion of an action by the AMRGS  1150  (e.g., within 1 minute, within 5 minutes, within 30 seconds). The action resulting in a real-time notification can be the report generator  1156  retrieving the metrics data of the similar profiles; an operation performed by the report generator  1156 ; an operation performed by the matching engine  1154 ; receiving adjusted parameters from the administrator device  1160 . For example, responsive to the AMRGS  1150  retrieving performance metrics values from the database  1158  and averaging the values, the report generator  1156  can generate a report detailing the results of the operations and cause the report to be transmitted to the administrator device  1160   a  via the communications interface  1152 . 
     The report can be transmitted within a pre-determined time interval of receiving the request for a dynamic report. The predetermined time interval can be a time period after an action, e.g. 10 minutes, 5 minutes, 1 minute, 30 seconds. The action can include receiving the request for a dynamic report, receiving one or more packets generated by the administrator device  1160 , or generating the notification of the initiation of the dynamic reporting process. The pre-determined time interval can be set in a configuration file or profile maintained by the AMRGS  1150  in the database  1158 . The pre-determined time interval can be set by an entity remote from the AMRGS  1150 . For example, the AMRGS  1150  can transmit a time interval request to a remote server of an insurance administrator or an employer. The time interval request can cause the remote server to transmit the configuration file or profile setting the pre-determined time interval to the AMRGS  1150 . The report generator  1156  can process the configuration file or profile to extract the pre-determined time interval in order to transmit the report within the pre-determined time interval. 
     In some embodiments, responsive to the action occurring that initiates the pre-determined time interval, the report generator  1156  can generate a placeholder notification to be transmitted to the administrator device  1160  independent of the status of generating the dynamic report. For example, the placeholder notification can indicate that the report generating process has been initiated. The placeholder notification can indicate that further information is required to complete the report generating process. The report generator  1156  can transmit the placeholder notification prior to expiry of the pre-determined time interval via the communications interface  1152  to provide real-time communication of the reporting process. 
     In some embodiments, the notification can include status information regarding the report generation (e.g., dynamic report complete, dynamic report incomplete, similar profiles retrieved, performance metrics retrieved, or dynamic report pending). In some embodiments, the notification can include status information regarding the request (e.g., processing request or request processed). In some embodiments, the report generator  1156  is configured to generate notification of the initiation of the report generation process, and transmit the notification via the communications interface  1152  to the administrator device  1160   a.    
     In some embodiments, the report generator  1156  can retrieve an electronic report template configured for the reporting the results of the operations of the report generator  1156 . The report generator  1156  can generate the notification using the electronic report template. The report generator  1156  can transmit the one or more data packets carrying the results generated using the electronic report template to the administrator device  1160   a  via the communications interface  1152 . For example, the communications interface  1152  can transmit the one or more data packets via at least one of an SMS protocol or an electronic mail protocol. 
     In some embodiments, the report generator  1156  is configured to retrieve an electronic report template configured for transmission via a particular transmission protocol. For example, the report generator  1156  can retrieve an SMS-compatible electronic report template configured to be compatible with SMS protocol, such as an electronic report template having a particular character limit and an organization configured to use plain text. The SMS-compatible electronic report template can be configured to prioritize particular results, such as a value of a prioritized performance metric. The report generator  1156  can retrieve an electronic mail-compatible electronic report template configured to be compatible with electronic mail protocol, such as an electronic report template using rich text or HTML. In some embodiments, the report generator  1156  can retrieve multiple electronic report templates compatible with multiple transmission protocols, generate multiple notifications using the multiple transmission protocols, and transmit the multiple notifications via the multiple transmission protocols via the communications interface  1152 . 
     In some embodiments, the report generator  1156  is configured to transmit an instruction to the administrator device  1160  to trigger an application on the administrator device  1160  to launch a user interface (e.g., a prompt, a graphical user interface, etc.) or application program interface configured to display the information provided via the electronic report. The report generator  1156  can be configured to transmit an application configuration request to the administrator device  1160  that causes the administrator device  1160  to transmit details regarding the user interface, and the report generator  1156  can configure the electronic report based on the received details. The report generator  1156  can be configured to transmit an application program interface to the administrator device  1160  in a format configured for use by the administrator device  1160 , causing the administrator device  1160  to install the application program interface in order to display the electronic report received in the notification. The report generator  1156  can configure the one or more data packets carrying the notification to cause the administrator device  1160  to launch the user interface or application program interface in order to display the electronic report. 
     In some embodiments, the AMRGS  1150  (e.g., via communication interface  1110 ), receives a request for profile information from an administrator device  1160  associated with an administrator profile on the AMRGS  1150 . The request for information can include information about a value of a performance metric for the requesting administrator. The request can further include authentication information or credentials associated with the request. The authentication information can include network security credentials, such as security certificates or tokens. The authentication information can further include a username, password, two-tier authentication information (e.g., verification code sent via text message to phone number in profile associated with administrator). The authentication can include credentials depending on a security level associated with the account information requested. For example, a first security level requiring a first item of authentication information can be associated with information such as a balance of the electronic account, and a second security level requiring both a first item of authentication information and a second item of authentication information can be associated with identification information associated with the profile. 
     Responsive to authenticating or otherwise approving the request, the AMRGS  1150  can access a data record in database  1158  for the electronic account to generate a report with the requested information, or generate a standard report, or generate another preconfigured report. The report can identify the administrator information, percentage of employees participating in electronic benefits accounts of the administrator, monthly fees of the accounts, and other parameter or performance metric information. 
     In some aspects, the system of the present solutions implements a combination of the communications interface  1152 , matching engine  1154 , report generator  1156 , database  1158 , claims processor  220 , POS terminals  202   a - n , or clients  102   a - n  in an innovative, non-conventional or non-routine manner. In some aspects, the system of the present solutions integrates the communications interface  1152 , matching engine  1154 , report generator  1156 , database  1158 , claims processor  220 , POS terminals  202   a - n , or clients  102   a - n  an innovative, non-conventional or non-routine manner to implement the improved functionality, performance and operation of the present solution. In some aspects, the system of the present solutions integrates the communications interface  1152 , matching engine  1154 , report generator  1156 , database  1158 , claims processor  220 , POS terminals  202   a - n , or clients  102   a - n  in an innovative, non-conventional and/or non-routine manner to more efficiently and effectively use computing and networking resources. The communications interface  1152 , matching engine  1154 , report generator  1156 , database  1158 , claims processor  220 , POS terminals  202   a - n , or clients  102   a - n  are integrated in an innovative, nonconventional manner to mitigate, reduce, prevent, or resolve the technical problems of generating dynamic interfaces or reports. The communications interface  1152 , matching engine  1154 , report generator  1156 , database  1158 , claims processor  220 , POS terminals  202   a - n , or clients  102   a - n  are integrated in the innovative, non-conventional manner address at least these technical problems by interfacing with a plurality of administrator devices remote from the device; receiving, via a network, an identifier of an administrator of an administrator device of the plurality of administrator devices; the tool further configured to retrieving, from an administrator profile data structure stored in memory, an administrator profile corresponding to the identifier; identifying one or more administrator profiles stored in the administrator profile data structure of one or more different administrators; determining, based on a parameter matching technique, from the one or more identified administrator profiles, a similarity metric between the administrator profile and each of the identified one or more administrator profiles; identifying the one or more administrator profiles having the similarity metric satisfying a predetermined threshold; instantiating a dynamic report interface to render for display via the administrator device, an electronic report indicating a first value of a first performance metric of the administrator based on the administrator profile and a second value of the first performance metric based on the identified one or more administrator profiles; and providing, via the dynamic report interface, the electronic report for display via the administrator device. 
     Referring now to  FIG.  12 A , a screenshot  1200   a  of an embodiment of a dynamic report interface for using in conjunction with the AMRGS  1150  is depicted. The dynamic report interface may be displayed at the administrator device  1160  or other computing device via which the administrator requests to access the dynamic report interface. The interface includes an input portion  1201  and an output portion  1203 . The input portion includes a requesting administrator field  1202 , a parameter column  1204 , and a parameter value column  1206 . The output portion  1203  includes a similar administrator field  1208 , a performance metric field  1210 , a requesting administrator performance metric field  1212 , and a performance metric display  1214 . 
     In some embodiments, the administrator associated with the administrator device  1160  that requested the dynamic report may be identified in the dynamic report interface  1200   a . For example, administrator “A” is identified as the requesting administrator of the dynamic report. In some embodiments, the AMRGS  1150  may obtain the information in field  1202  based on the identifier received at the AMRGS  1150 . Column  1204  includes a plurality of parameters for input into the dynamic report process. For example, column  1204  may include such parameters as account opening fee, minimum operating balance, monthly fee, electronic fund access type, and interest rate. Each parameter in parameter column  1204  may be associated with a respective value depicted in column  1206 . For example, the account opening fee may be associated with $50. In some embodiments, the values in column  1206  may be modified by an administrator and the modified values may be received at the AMRGS  1150 . As depicted in  FIG.  12 A , some of the parameter values in column  1206  are presented with a “slider” interface. The slide interface may allow a user at the administrator device  1160  to interact with the parameter values and adjust the parameter values. In some embodiments, the parameter values may include an interface other than a slider, such as, but not limited to, a dial, an input text box, a selectable list (see “electronic fund access type”), and the like. 
     In some embodiments, the AMRGS  1150  initially populates and calibrates the interactive parameter value fields to correspond with the default values stored in the database  1158  associated with the requesting administrator profile. For example, administrator “A” may be currently operating its electronic savings account with a $50 account opening fee, a $200 minimum operating balance, etc. As such, the AMRGS  1150  may initially utilize these parameter values in its report generation for display at the dynamic report interface. 
     Still referring to  FIG.  12 A , the output portion  1203  may indicate a number of administrator profiles upon which the report is based at the similar administrator field  1208 . These administrator profiles may correspond to the administrator profiles determined by the AMRGS  1150  to by sufficiently similar to the requesting administrator profile based on the parameters of the requesting administrator profile. For example, the output portion  1203  indicates that the results of the dynamic report are based on 7 similar administrator profiles. In some embodiments, the dynamic report interface  1200   a  may list by name each of the similar administrator profiles. In some embodiments, the names may not be listed or otherwise hidden from view. 
     The performance metric field  1210  may indicate a performance metric and a value associated with the performance metric based on the similar administrator profiles. For example, the performance metric field  1210  indicates a performance metric of “average employee participation” of the similar administrator profiles as being “81%”. In some embodiments, the dynamic report interface  1200   a  may list each of the respective employee participation rates of the individual similar administrator profiles. In some embodiments, the average is a weighted average. In addition, the output portion may indicate the performance metric value associated with the requesting administrator profile at the requesting administrator performance metric field  1212 . For example, the field  1212  indicates that the average employee participation rate for administrator A is 72%. In addition, further information calculated based on the performance metrics of the similar administrator profiles may be depicted at the performance metric display  1214 . Any suitable information relating to the performance parameters may be depicted at the field  1214 , including, trends over time of the performance metrics, graphical depictions of the performance metric values, forecasts of the values, and the like. For example, dynamic report interface  1200   a  depicts a lowest value (of the similar administrators) performance metric, a median value, and a high value. In addition, the performance metric display  1214  graphically illustrates where administrator A is ranked with respect to the performance metric. For example, administrator A is at the second quartile of the group consisting of the similar administrators. In some embodiments, the information generated in the output portion  1203  is based on the profile of the requesting administrator (in addition to the administrator profiles of the similar administrators). 
     Referring now to  FIG.  12 B , another screenshot  1200   b  of a dynamic report interface for using in conjunction with the AMRGS  1150  is depicted. The dynamic report interface may be displayed at the administrator device  1160  and is substantially similar to that depicted in  FIG.  12 A . The screenshot includes the input portion  1201  and the output portion  1203 . The input portion includes the requesting administrator field  1202 , the parameter column  1204 , and the parameter value column  1206 . The output portion  1203  includes the similar administrator field  1208 , the performance metric field  1210 , the requesting administrator performance metric field  1212 , and a performance metric display  1214 . 
       FIG.  12 B , illustrates a scenario in which one or more of the parameter values under column  1206  is modified. For example, the account opening fee is adjusted from $50 in  FIG.  12 A  to $100 in  FIG.  12 B . The parameter modification may be performed at the administrator device  1160  by interaction with the dynamic report interface. In response to a parameter modification, the dynamic report interface may output different performance metric values based on the updated set of parameters in the input portion  1201 . The performance metric value updates may occur in real-time. For example, after receiving the updated account opening fee parameter value, the AMRGS  1150  may perform the administrator matching or the report generating process, or both, based on the updated parameter value and the other parameter values that have not been modified. After performing operations on the new parameter set, the AMRGS  1150  may report the updated metric values to the administrator device  1160  via the dynamic interface  1200   b . For example, in response to the change of the account opening fee parameter value from $50 to $100, the average employee participation at field  1210  decreased to 74%, from 81% in  FIG.  12 A , and the average amount of contribution per month metric value decreased to $152, from $164 in  FIG.  12 A . In addition, the median and high values in the performance metric display  1214  decreased to 47% and 95%, respectively. 
     In some embodiments, the AMRGS  1150  may perform updated administrator matching based on the modified parameters. As such, the set of similar administrator profiles on which the performance metric calculations are based, may change, and thus the value of the similar administrator field  1208  may also change depending on how many similar administrator profiles are identified with respect to the updated parameters. For example, when the account opening fee is increased to $100, some administrator profiles may no longer be sufficiently similar to the administrator profile having the changed parameter, and those dissimilar profiles may no longer be used for purposes of the dynamic report. On the other hand, other previously dissimilar administrator profiles may become sufficiently similar due to the updated parameter, and those newly similar administrator profiles may be used in the dynamic report. 
     Referring now to  FIG.  13   , a flow diagram depicting an embodiment of a method  1300  of managing information technology infrastructure is shown. The method can be performed by one or more component or module of system  1100 , the AMRGS  1150 , or one or more component or module depicted in  FIGS.  1 A- 1 D . In brief overview, at step  1302 , a server of an administrator matching and report generating system receives an identifier of an administrator of an administrator device of a plurality of administrator devices. At step  1304 , the server retrieves an administrator profile corresponding to the identifier. At step  1306 , the server identifies one or more administrator profiles of one or more different administrators stored in the administrator profile data structure. At step  1308 , the server determines a similarity metric between the administrator profile and each of the one or more administrator profiles. At step  1310 , the server identifies the one or more administrator profiles having the similarity metric satisfying a similarity threshold. At step  1312 , the server generates an instance of a dynamic report interface to render for display, an electronic report indicating a first value of a first performance metric of the administrator based on the administrator profile and a second value of a first performance metric based on the identified one or more administrator profiles. At step  1314 , the server provides the electronic report for display via the administrator device. 
     Still referring to  FIG.  13   , and in further detail, at step  1302 , a server of an administrator matching and report generating system receives an identifier of an administrator of an administrator device of a plurality of administrator devices. In some aspects, step  1302  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  1302  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  1302  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     The received identifier can indicate a request for a dynamic report. The server can include one or more processors. The server can include a communications interface for receiving the request. One or more data packets carrying data indicating the request can be received. The request can be received via a computer network using a networking protocol. The request can be generated by a device at an administrator. The data packets can include header information and payload information. The header information can include, e.g., TCP header information that can facilitate the routing and transmission of the data packet. The payload information can include data related to, describing, defining, associated with or otherwise about the request for a dynamic report, including input parameters regarding electronic benefits accounts. The one or more data packets can include data identifying the administrator making the request. The administrator device can generate or obtain information that allows the server to conduct the report generation and profile matching, encapsulate or process the information using a protocol to generate data packets, and transmit the data packets in a secure manner over a network to the server for further processing. The server can initiate a report generating process responsive to receiving the one or more data packets. The server can also receive a parameter of the administrator profile, and the parameter may include at least one of an account opening fee, a minimum operating balance, a monthly fee, an annual fee, an electronic fund access type, or an interest rate. 
     At step  1304 , the server retrieves an administrator profile corresponding to the identifier. In some aspects, step  1304  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  1304  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  1304  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     The server can access a database maintained by the server to retrieve the stored administrator profile. The server can perform the retrieving responsive to receiving the identifier. In some embodiments, the server parses the one or more data packets to identify the administrator profile, and performs a lookup in an administrator profile database maintained by the server using the identifier to retrieve. The server can also generate an administrator profile of the requesting administrator with parameters received from the administrator device. The administrator device may be configured to receive data from a plurality of participant devices corresponding to the one or more tax benefit accounts configured using the administrator profile. The server can train (e.g., via a machine learning technique) an administrator profile model using a plurality of administrator profiles. The server can determine the first value of a first performance metric based on an output from the administrator profile model responsive to a parameter of the administrator profile input into the administrator profile model. 
     At step  1306 , the server identifies one or more administrator profiles of one or more different administrators stored in the administrator profile data structure. The server can access the administrator profile database to access or identify the one or more different administrator profiles different from the administrator profile identified in the previous step. The server can perform the identifying responsive to the retrieving. The different administrators may be a subset of the total administrator profiles stored in the database based on a filter received by the server. In some aspects, step  1306  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  1306  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  1306  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     At step  1308 , the server determines a similarity metric between the administrator profile and each of the one or more administrator profiles. The similarity metric can indicate the degree to which the administrator profile is similar to each of the one or more different administrator profile. The similarity metric may be executed by an administrator matching engine maintained on the server. The similarity metric may be obtained by determining the similarity between individual parameters between the two administrator profiles. In some aspects, step  1308  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  1308  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  1308  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     At step  1310 , the server identifies the one or more administrator profiles having the similarity metric satisfying a similarity threshold. The server can maintain the similarity thresholds on the database of the server. The similarity threshold may be adjustable, and an indication of adjustment of a similarity threshold may be received at the server. A similarity threshold may be implemented for each individual parameter being compared. The server can determine a subset of the different one or more administrator profiles based on the ones that satisfy the similarity threshold to obtain one or more administrator profile similar to the administrator profile associated with the identifier. In some aspects, step  1310  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  1310  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  1310  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     At step  1312 , the server generates an instance of a dynamic report interface to render for display, an electronic report indicating a first value of a first performance metric of the administrator based on the administrator profile and a second value of a first performance metric based on the identified one or more administrator profiles. In some aspects, step  1312  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  1312  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  1312  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     The dynamic report may be generated at a report generator maintained at the server. The first performance metric may be any resulting characteristic of an electronic benefits account, such as, customer participation percentage. The first value of the first performance metric may correspond to the administrator profile associated with the received identifier. The second value of the first performance metric may be associated with the one or more similar administrator profiles. The second value may be an average of each of the values associated with each similar administrator profile, or may be a weighted average value. The server can render an electronic report indicating the first value of a first performance metric based on a number of participants of the administrator during a time interval, and the second value of the first performance metric based on the number of customers of the identified one or more administrators. 
     At step  1314 , the server provides the electronic report for display via the administrator device. In some aspects, step  1314  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  1314  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  1314  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     The server can transmit the one or more packets in real time. The server can transmit the one or more packets within a predetermined time interval of a preceding action, such as receiving the identifier. In some embodiments, the server receives adjustment information regarding the input parameters and updates the dynamic report provided based on the updated parameters in real-time. The server can receive, via the instance of the dynamic report interface, an indication from the administrator device to adjust the time interval. The server can manipulate the first value of a first performance metric and the second value of a first performance metric indicated in the rendered electronic report responsive to the indication to adjust the time interval. The server can receive, via the instance of the dynamic report interface, a filter criterion. The server can use the filter criterion to identify a subset of the one or more administrator profiles stored in the administrator profile data structure. The server can generate a third value of a first performance metric based on the subset of the one or more administrator profiles. The server can render, via the dynamic report interface, the electronic report to indicate the first value of a first performance metric and the third value of a first performance metric. The server can remove the second value of a first performance metric from the rendered electronic report, the second value of a first performance metric different from the third value of a first performance metric. The server can receive an update to the administrator profile after the electronic report is rendered. The server can generate a third value of the first performance metric based on the update to the administrator profile. The server can render via the dynamic report interface, the electronic report to include the third value of the first performance metric and remove the first value of the first performance metric. The server can render the electronic report for display on the administrator device via the dynamic report interface, and receive from the administrator device via the dynamic report interface, an indication to manipulate the electronic report. 
     In some aspects, the methods of the present solutions implements a combination of steps in an innovative, non-conventional and/or non-routine manner. In some aspects, the method  1300  of the present solution combines the steps of  FIG.  13    in an innovative, non-conventional and/or non-routine combination to implement the improved functionality, performance and operation of the present solution. In some aspects, the method of the present solution combines the steps of  FIG.  13    in in an innovative, non-conventional and/or non-routine manner to more efficiently and effectively use computing and networking resources. In some aspects, the method of the present solution provides innovative, non-conventional and/or non-routine ordered combination of steps. 
     F. Predictive Resource Allocating System (PRAS) 
     The systems and methods of the present solution are directed to the technical problems and challenges of implementing the functionality of resource allocation on an electronic transaction based technology and platform. Existing electronic transaction based technologies and platforms do not effectively and efficiently make use of the computing and network resources deployed for electronic transaction based technologies and platforms to include such functionality. Without implementing such functionality, existing electronic transaction based technologies and platforms have the problems of excessive server-client requests and responses, processing delays, increase bandwidth usage, or erroneous or inefficient resource allocation. 
     The systems and methods of the present solution are directed to the improvement of the performance and operation of the electronic transaction based technology and platform and computing and networking resource used by such electronic transaction based technology and platform. In some aspects, the present solution improves and enhances the implemented functionality of the electronic transaction based technology and platform implemented on, integrated with and inherently tied to the processor, memory, network and computing resources of one or more computing devices. In some aspects, the present solution more effectively performs the functionality of the electronic transaction based technology and platform thereby making and causing more effective use of the computing and networking resources to achieve the improved functionality of the present solution. The same computing and network resources used by such electronic transaction based technology and platform will provide increased and improved functionality with implementation of the present solution. 
     In some aspects, the present solution more efficiently uses the computing and networking resources to implement the improved functionality of the electronic transaction based technology and platform. For example, systems and methods of the present solution are directed to allocating resources using an information technology infrastructure. Systems and methods of the present solution can determine amounts of funds a participant should allocate to a healthcare tax benefit account to cover predicted lifetime healthcare expenses. 
     Administrators that establish or provide electronic tax benefits accounts for various participants of those accounts can utilize backend information technology infrastructure to process, analyze, monitor or manage the electronic tax benefits accounts. An entity managing the backend information technology may have access to data regarding electronics tax benefit accounts across multiple administrators. This data may include financial and health information of the various participants across the various administrators, which the entity managing the backend information technology may advantageously utilize to provide unique services. 
     The present disclosure provides systems and methods of allocating resources using an information technology infrastructure. The interactive interface can include a report based on analyzing the financial and health data of the various participants across multiple administrators. For example, the system can use the data on participants in the system to build various profiles and saving or spending trends for those participants. The system enables existing or new participants to enter information about themselves, into an interactive interface, about their healthcare and retirement savings, income, or spending, and compare that to lifestyle profiles or expense prediction models to forecast the necessary retirement funds needed to fund not only their lifestyle, but their healthcare needs. Additionally the system can profile the economic advantage (e.g., tax advantage) of various retirement vehicles to determine the most beneficial savings approach for the participant (e.g., health savings accounts triple tax benefit vs. 401k vs. Roth IRA vs. other healthcare spending accounts like health retirement accounts and flexible spending accounts). 
     The system can be configured with a machine learning technique to constantly update and refine expense prediction models. The machine learning technique can be based on new financial and health data of the participants that is continuously received by the system. The system can parse the new information and determine how the data reinforces a predictive model or changes a predictive model. Upon receiving personal financial and health data from a participant seeking to identify how to optimally allocate funds to their electronic benefits accounts, the system can identify a predictive model based on the received information that is most similar to the seeking participant&#39;s information, and can then identify future healthcare and non-healthcare costs of the participant based on the identified predictive model. Based on the predicted expenses of the participant, the system can determine the economically optimal (e.g., most tax-advantaged) contribution scheme for the participant to invest in one or more healthcare benefits accounts and one or more non-healthcare benefits accounts (e.g., how much and into which accounts the participant should deposit funds). 
     Upon determining the optimal contribution plan, the system can generate an interactive interface for displaying the results of the system&#39;s calculations to the participant seeking the information. The interactive interface can include or be configured on a dashboard. In some cases, the interface can be provided or streamed over a data network. The interface can be configured to receive data manipulation indications via an input device, and the system can update the calculated results and display the results via the interface in real-time. For example, the interface can receive indications to manipulate the data corresponding to the amount of annual contribution to one or more of the electronic benefits account, the amount already saved in the accounts, health indicators (e.g., a promise to increase exercise activities), financial indicators (e.g., an imminent income raise), or the like. 
     In an illustrative embodiment, the system can provide payment processing infrastructure and technology to a plurality of administrators such as multiple insurance companies. The insurance companies can provide various types of insurance (e.g., health, dental, vision, car, property, legal, construction, etc.) to its customers. A customer of the insurance company can include an employer that has employees. The system can enable the employees that participate in the insurance company plans to initiate and receive a report indicating predicted expenses and a suggested contribution scheme to healthcare and non-healthcare benefits accounts for the employee. The suggestions presented to the employee are based on the health and financial data personal to the employee, and on the vast financial and health data of the various employees that are provided with the electronic benefits accounts from the multiple insurance companies. 
     Referring now to  FIG.  14   , a block diagram depicting an embodiment of a system  1400  comprising a predictive resource allocating system is shown. In brief overview, the system  1400  includes a predictive resource allocating system  1408  (“PRAS”). The PRAS  1408  can include the MPTS  120  depicted in  FIG.  2   , the MPTS  408  depicted in  FIG.  4   , the TEPS  708  depicted in  FIG.  7   , or the AMRGS  1108  depicted in  FIG.  11   , or one or more components or modules depicted in  FIG.  2 ,  4 ,  7   , or  11 , and can perform the functions of the MPTS  120 , MPTS  408 , TEPS  708 , or the AMRGS  1108 . The PRAS  1408  can receive or transmit data via a network  104  with clients  102   a - n . The system  1400  can include or interact with one or more clients  102   a - n  (or client device  102 ). 
     The PRAS  1408  can include a communications interface  1410 . The communications interface  1410  can include the communications interface  210  depicted in  FIG.  2   , the communications interface  410  depicted in  FIG.  4   , the communications interface  710  depicted in  FIG.  7   , or the communications interface  1110  depicted in  FIG.  11   , or one or more components or modules depicted in  FIG.  2 ,  4 ,  7   , or  11 , and can perform the functions of the communications interfaces  210 ,  410 ,  710 , or  1110 . The communications interface  1410  is configured with one or more communications ports, application programming interfaces, network protocols (e.g., TCP/IP), authentication protocols, or security protocols (e.g., SSL). The communications interface  1410  can receive financial data and health data of a participant of a client device  102  or a request to perform predictive resource allocation for the participant. In some aspects, the communications interface  1410  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, the communications interface  1410  is implemented to make or cause more effective and efficient use of computing and networking resources. For example, the communications interface  1410  can cause more effective and efficient use of computing and network resources by reducing the number of processing cycles, memory or network bandwidth used to determine resource allocations to reduce resource consumption. The communications interface  1410  can provide a reduction in resource consumption by integrating with a forecast engine  1412 , machine learning engine  1416 , database  1414 , clients  102   a - n , admin devices  1118   a - n , or heterogeneous electronic funding sources  702   a - n  to allocate resources or reduce resource consumption. 
     The PRAS  1408  can include a forecast engine  1412 . The forecast engine  1412  determines, responsive to the communications interface  1410  receiving the financial and health data, an amount of funds a participant should allocate to healthcare tax benefit accounts and an amount of funds the participant should allocate to non-healthcare tax benefits accounts. In some aspects, the forecast engine  1412  is implemented to make or cause more effective and efficient use of computing and networking resources. For example, the forecast engine  1412  can cause more effective and efficient use of computing and network resources by reducing the number of processing cycles, memory or network bandwidth used to determine resource allocations to reduce resource consumption. The forecast engine  1412  can provide a reduction in resource consumption by integrating with the communications interface  1410 , machine learning engine  1416 , database  1414 , clients  102   a - n , admin devices  1118   a - n , or heterogeneous electronic funding sources  702   a - n  to allocate resources or reduce resource consumption. 
     The PRAS  1408  can include a machine learning engine  1416 . The machine learning engine  1416  generates and trains on an ongoing basis healthcare expense prediction models based on stored and aggregated health and financial data of a plurality of account participants. In some aspects, the machine learning engine  1416  is implemented to make or cause more effective and efficient use of computing and networking resources. For example, the machine learning engine  1416  can cause more effective and efficient use of computing and network resources by reducing the number of processing cycles, memory or network bandwidth used to determine resource allocations to reduce resource consumption. The machine learning engine  1416  can provide a reduction in resource consumption by integrating with the communications interface  1410 , forecast engine  1412 , database  1414 , clients  102   a - n , admin devices  1118   a - n , or heterogeneous electronic funding sources  702   a - n  to allocate resources or reduce resource consumption. 
     The PRAS  1408  can include one or more databases or data structures that store information to facilitate the systems and methods of the present solution, such as database  1414 . The database  1414  can include the database  216 , the databases  418  and  420  depicted in  FIG.  4   , the databases  714  and  716  depicted in  FIG.  7   , or the database  1116  depicted in  FIG.  11   , or one or more components or modules depicted in  FIG.  2 ,  4 ,  7   , or  11 , and can perform the functions of the databases  216 ,  418 ,  420 ,  714 ,  716 , or  1116 . The database  1414  can include a financials database including financial information corresponding to a plurality of participants. The database  1414  can include a health database including health information corresponding to a plurality of participants. In some embodiments, the health and financial data stored in the database  1414  can be stored securely and can also be encrypted. In some embodiments, participants may be required to opt-in or volunteer to allow the PRAS  1408  to store their health and financial data. The database  1414  can include a models database including a plurality of healthcare expense prediction models. The financial and health data can include biographical information associated with users, identifiers for clients  102  or other devices associated with users, security credentials associated with users, transaction histories, etc. In some embodiments, the financial and health data can include contact information such as an electronic mail protocol address or identifier, a mobile telephone number, an SMS protocol, a landline telephone number, or a postal address associated with users. 
     In some embodiments, the data maintained at the database  1414  includes various pieces of aggregated information from a plurality of participants across various administrators of electronic benefits accounts. The administrators may correspond to the administrator devices  1118   a - n  at which the administrators may perform operations for caretaking, monitoring, or modifying electronic benefits accounts with which participants (e.g., those at client devices  102   a - n ) corresponding to a particular administrator are associated. As such, because the PRAS  1408  is connected to the one or more administrator devices  1118   a - n , the PRAS  1408  may access and accumulate information and data of the various participants across various administrators, and maintain the information at the database  1414  for future use. 
     In some embodiments, the database  1414  may aggregate financial data, health data, and personal data based on a plurality of participants. The financial information may include data such as, but not limited to, amount spent on healthcare per a given time period, household income, amount of contribution to healthcare benefits accounts, amount of contribution to non-healthcare benefits account, amount an employer of a participant matches contributions to electronic benefits accounts, amount a participant has saved for retirement (e.g., amount of funds saved in a healthcare benefits account or a non-healthcare benefits account), or the like. The health data may include data such as, but not limited to, diet information, fitness and exercise information, health insurance information, medical care information, or the like. The personal information may include data such as, but not limited to, age, gender, marital status, target retirement age, or the like. 
     In some embodiments, the health data, the financial data, and the personal information of the plurality of participants may be obtained by the administrator devices  1118  sending such data to the PRAS  1408 , since the administrator devices  1118  directly interface with the participants at the client devices  102 . For example, in some embodiments, the administrator at the administrator device  1118  is an employer and the participants are employees of the employer, and in such a case the administrator device  1118  may have information regarding personal and financial information pertaining to its employees that may be accessible by the PRAS  1408 . In some embodiments, the administrator may be an electronic benefits account (healthcare and non-healthcare accounts) provider to the participants, and thus may have health, financial, and personal information regarding the participants. In some embodiments, the PRAS  1408  may require or request the participants to fill out electronic surveys containing questions regarding their health, personal, and financial information, and the completed surveys may be sent to the PRAS  1408  for storing. In some embodiments, the health data may be determined by the PRAS  1408  by identifying and parsing electronic transactions by participants (e.g., buying medication with the multipurse debit card, paying for medical procedures or visits, transaction codes and the transaction code mapping). 
     The healthcare benefits account may include, but not be limited to, a health savings account, a medical savings account, a flexible savings account, or the like. The non-healthcare benefits account may include, but not be limited to, a 401k account, a  403   b  account, a  457   b  account, an individual retirement account (IRA), or the like. In some embodiments, the aggregated health data and financial data may be stored in database  1414  such that the participant information corresponding to a set of data is maintained anonymously. In other embodiments, the participant information corresponding to a set of health or financial data is identifiable. In some embodiments, the database  1414  may also maintain healthcare expense prediction models based on the aggregated financial and health data. 
     The PRAS  1408 , communications interface  1410 , forecast engine  1412 , and machine learning engine  1416  can each include one or more processing units or other logic devices such as programmable logic array engines, modules, or circuitry designed and constructed to facilitate managing security on a network infrastructure. The PRAS  1408  can include the components  100  shown in  FIG.  1 C  or  FIG.  1 D , or be configured to operate as a service in cloud  108 . The PRAS  1408  can include or interact with one or more servers  106   a - n  and clients  102   a - n.    
     In some embodiments, the PRAS  1408  can employ a multitier architecture such as a client-server architecture in which presentation, application processing, and data management functions are logically or physically separated. The presentation tier, or front-end, can include the communications interface  1410  that serves static content or dynamic content to be rendered by the client  102  (e.g., by a web browser executing on client  102 ). The presentation tier or web server can interact or communicate with the application tier to obtain data to provide to the client  102 . The application tier can include the forecast engine  1412  that controls the system&#39;s functionality and performs additional processing or analysis on data. The application tier can interact with the data tier to obtain the transaction data. The data tier can include data persistence mechanisms (database servers, file shares, etc.) and the data access layer that encapsulates the persistence mechanisms and exposes the data. The data tier can include database  1414 . The data tier can include an application programming interface (API) to the application tier. The database  1414  can include stored procedures (e.g., SQL statements) that perform tasks with respect the stored data. 
     In further detail, and in some embodiments, the PRAS  1408  includes a communications interface  1410 . The communications interface  1410  can execute on one or more processors of a server. The communications interface  1410  can include one or more communications ports and be configured with one or more network protocols. Communications ports can include, e.g., network ports, Ethernet ports, WAN ports, I/O ports, or software ports. The communication port can be configured with a network protocol such as Transport Layer Protocols such as TCP/IP or UDP that are configured to receive and process data packets received via a computer network. The port can include or be associated with an IP address of a host and a protocol type of the communication. 
     In some embodiments, the communication interface  1410  can receive data packets. The data packets can be generated by client device  102  or by administrator device  1118 . The client device  102  may be a device at which a participant of an electronic benefits account may access their account. In some embodiments, the client device  102  is the place at which a participant enters financial and health data personal to the participant to be sent to the PRAS  1408 . The client device  102  may be any device for entering information and sending the information to the PRAS  1408 , such as, but not limited to a laptop, a desktop, a smartphone, a tablet, or the like. In some embodiments, the client device  102  can interact with one or more heterogeneous electronic funding sources  702   a - n . The heterogeneous electronic funding sources  702   a - n  can include at least one of an ACH, an electronic checking account, an electronic bill pay account, an electronic savings account, an electronic credit card account, or an electronic employer payroll account. The heterogeneous electronic funding sources  702   a - n  are accessed to fund the electronic benefits accounts of a participant, and the PRAS  1408  can calculate amounts of funds, to be taken from one or more of the heterogeneous electronic funding sources  702   a - n , that a participant should transfer to one or more electronic benefits accounts based on the participant&#39;s health and financial information. 
     The administrator device  1118  may be a device at which an administrator of an electronic benefits account that is associated with a plurality of participants may access the account. In some embodiments, the administrator device  1118  is the place at which an administrator maintains personal, financial, and health information of a plurality of participants corresponding to that administrator device  1118 . The administrator device  1118  may be any device for storing information or for entering information and sending the information to the PRAS  1408 , such as, but not limited to a laptop, a desktop, a smartphone, a tablet, a server, or the like. In some embodiments, the administrator device  1118  can interact with the client device  102  for providing services related to the electronic benefits accounts in which a participant of the client device  102  contributes funds. For example, the administrator device  1118  may provide to the client device  102  troubleshooting support, investment advice, modifications to accounts, or the like. 
     The communications interface  1410  can receive data packets generated by the client device  102  or by the administrator device  1118  (e.g., financial or health information of a participant or a plurality of participants). In some embodiments, the communication interface  1410  receives data packets corresponding only to financial information, only to health information, or to both financial and health information. The data packets can include header information and payload information. Multiple data packets can be strung together in a sequence. The header information can refer to TCP/IP headers that include fields such as source port, destination port, sequence number, acknowledge number, window size, etc. The payload information of the data packet can include information related to the health or financial data or related to the participant associated with the health or financial data. The PRAS  1408  can receive the data packet with header information and payload information and process the packets to obtain information for further processing. The payload can include data identifying the client device  102  at which the financial and health data was entered, the customer associated with the health and data information, the financial and health data, personal information of the customer, and other information for predicting amounts of funds the customer should be investing into electronic benefits accounts. The data packets (e.g., via the payload) can include a request to provide a report displaying the calculated amounts of funds the customer should be investing into electronic benefits accounts. The request can specify the types of electronic benefits account for funding. The request can specify information for identifying a healthcare expense prediction model for estimating future healthcare expenses of the customer. 
     The data packets (e.g., payload of the data packets) can further identify an electronic account maintained and configured on the server. The electronic account can be maintained and configured in a database  1414 . The electronic account can correspond to a user and have a unique identifier. The unique identifier can include numbers, letters, characters, symbols, etc. The electronic account can be associated with the customer entering financial and health data or making the request for resource allocation calculations. The client device  102  can receive or determine the electronic account identifier via data saved at the client device  102 , data entered into the client device  102 , or the like, which the client device  102  can then convey to the PRAS  1408 . 
     In some embodiments, the client device  102  or administrator device  1118  can generate multiple data packets for the financial and health information being sent to the PRAS  1408 . The multiple data packets can each include a header and a payload. The header can indicate that the multiple data packets are to be grouped together for routing, transmission or processing purposes. 
     The PRAS  1408  can be configured to authenticate communications. In some embodiments, the communications interface  1410  receives communications such as the financial and health data of a participant. The data can include security credential such as a security certificate or security token. The security credential can be associated with a participant. The PRAS  1408  can be configured to extract the security credential from the data, and authenticate the data by comparing the security credential against a known or verified security credential. For example, user profiles stored in database  1414  can include known or verified security credentials for comparison with the security credential of the request. In some embodiments, the PRAS  1408  receives the financial and health data via the communications interface  1410 , extracts a security credential from the data, analyzes the extracted security credential to identify a user, queries the database  1414  for a verified security credential stored with a user profile corresponding to the identified user, compares the extracted security credential to the verified security credential, and authenticates the data based on the extracted security credential matching the verified security credential. 
     In some embodiments, the PRAS  1408  includes a forecast engine  1412 . The forecast engine  1412  can execute on one or more processors of a server, such as a server of the PRAS  1408 . The forecast engine  1412  can receive, retrieve, or otherwise obtain or access some or all of the data carried by the data packets. The forecast engine  1412  can receive, retrieve, or otherwise obtain or access healthcare expense prediction models, such as models maintained in database  1414 . The forecast engine  1412  can determine, responsive to the communications interface  1410  receiving the financial and health data of a participant, a lifetime of health care expenses particular to the participant and an amount of funds the participant should allocate to healthcare tax benefit accounts, based on the determined lifetime healthcare expenses, and an amount of funds the participant should allocate to non-healthcare tax benefits accounts. 
     A healthcare expense may include any expense related to the health of an individual. In some embodiments, a healthcare expense may be more restricted and pertain to medical expenses, such as, but not limited to optometry expenses, dental expenses, physical checkups, or the like. In some embodiments, a health care expense may be more inclusive and include personal well-being expenses related to health, such as, but not limited to, gym memberships, nutritional supplements, or the like. Non-healthcare expenses may correspond to any expense that isn&#39;t categorized as a healthcare expense. For example, procedures related to enhancing the looks of an individual, such as, hair transplants, cosmetic surgery, or the like. In addition, expenses that have little correlation with health may correspond to non-healthcare expenses, such as, but not limited to, home purchase, car purchase, clothing, or the like. 
     The PRAS  1408  can initiate a resource allocation process responsive to receiving the data packets, such as by causing the forecast engine  1412  to access healthcare expense prediction models maintained in the database  1414 . The healthcare expense prediction models may include a plurality of models stored in the database  1414 , and each model may dictate a lifetime of healthcare expenses. Each model may identify or indicate a different amount of lifetime healthcare expenses. Each model can be associated with a plurality of parameters having values. For example, each model can include a parameter for age, annual gross income, overall health, geographic location, contributions to tax deferred accounts, amount of savings, gender, marital status, and so on. In some embodiments, the values for the parameters for a given model may be discrete values (e.g., a participant age of 36). In other embodiments, the values for the parameters for a given model may be a range of values (e.g., a participant age in the range from 31-39). With each model indicating an amount of lifetime healthcare expenses based on a plurality of parameters having respective values, each model can be compared to the received financial and health data of a participant to identify a healthcare expense prediction model having values of parameters similar to those of the participant, and to determine the predicted lifetime healthcare expenses of the participant associated with the identified similar model. 
     The PRAS  1408  can cause the forecast engine  1412  to identify a healthcare expense predication model maintained in the database  1414  to perform resource allocation based on the information extracted from the received data packets (e.g., the financial and health data corresponding to a participant). The PRAS  1408  can cause the forecast engine  1412  to determine that a remote healthcare expense prediction model is required based on information extracted from the received data packets, and the PRAS  1408  can request the remote model by transmitting one or more data packets carrying a model request to a remote server, such as a server of an insurance administrator or an employer. The model request can cause the remote server to transmit the requested remote policy to the PRAS  1408 . For example, the forecast engine  1412  can determine that the received data packets indicate a new insurance administrator or employer for which models are not yet maintained in the database  1408 . 
     The forecast engine  1412  can identify a healthcare expense prediction model by specifying, or can otherwise determine, an ordered list of account destinations for allocating resources to benefits account. The ordered list of account destinations can include or refer to a set of electronic account identifiers or electronic account types that are in a sequence of priority. For example, each electronic account identifier or electronic account type can be associated with, correspond to, or configured with an allocation priority. The priority can include a numeric value, score, text, symbol, or other indicator of a rank, preference, selection technique, selection protocol, or sequence. In some embodiments, the ordered list of account destinations may include an electronic benefits account maintained in a server by an entity remote from the PRAS  1408  (e.g., at administrator device  1118 ), such as, but not limited to, a server of a financial institution, of an insurance administrator, or of an employer. The electronic benefits account can include, but not be limited to, a tax benefit account, an HSA, an FSA, a 401k account, a checking account, a savings account, an investment account provided by a financial institution, or other electronic accounts. For example, the ordered list can prioritize for resource allocation the healthcare benefits account first, and the non-healthcare benefits account second. Any other combinations of account allocation priorities are contemplated. In some embodiments, the PRAS  1408  specifies a default ordered list. In some embodiments, the PRAS  1408  can receive data specifying the ordered list, for example, from the client device  102  or the administrator device  1118 . 
     In some embodiments, the PRAS  1408  determines the prioritization of the accounts based on characteristics of the different accounts. For example, The PRAS  1408  can determine different rate of returns associated with different types of tax benefit accounts to determine how to optimally allocate funds. The PRAS  1408  may also utilize rules or policies associated with the accounts. For example, the PRAS  1408  may lookup rules for an HSA and determine that it can be used only for qualifying expenses, but the funds of the account can be used immediately. The PRAS  1408  may also determine that a 401k account cannot be used until the age of 65 without a penalty, but can be used for anything (not just qualifying expenses). As such, the PRAS  1408  can score the different accounts and prioritize allocation based on the situation and needs of the individual participants. For example, if a participant typically spends a high amount of funds on prescriptions, but is relatively young (e.g.,  35 ), the PRAS  1408  may prioritize the HAS over the 401k so that the participant can utilize the funds immediately on the prescription drugs (a qualifying expense). The rules regarding various accounts may be stored at the PRAS  1408 , or the PRAS  1408  may access the rules remotely. 
     The forecast engine  1412  can parse the received request for performance of resource allocation or the received financial and health data to determine amounts of funds a participant should contribute to a healthcare benefits account and a non-healthcare benefits account. From the received financial and health data of the participant, the forecast engine  1412  can generate a multi-dimensional feature vector or array corresponding to the data. In some embodiments, the forecast engine  1412  can parse the received financial and health data and organize the data into a multi-dimensional feature vector. The multi-dimensional feature array may be a data structure including a collection of elements, values, or variables that can be identified an index or key. The multi-dimensional feature vectors may be implemented as hash tables, linked lists, search trees, or as any other suitable data structure. The multi-dimensional feature vectors may include any suitable number of dimensions for organizing the received financial and health data, such as, but not limited, to two dimensions, three dimensions, and so on. For example, the multi-dimensional vector may include a feature indicating demographic information of the participant, a feature indicating healthcare spending amount, a feature indicating a health savings account contribution amount, and a feature indicating a health preference. 
     The forecast engine  1412  can identify a healthcare expense prediction model to predict the future healthcare expenses of the participant. The forecast engine  1412  may utilize the received financial and health data to identify a relevant healthcare expense prediction model. In some embodiments, the forecast engine  1412  identifies the healthcare expense prediction model based on how similar the model is to the values of the received financial and health data. The forecast engine  1412  may therefore perform a similarity analysis between the values of parameters of the received financial and health data to the values of the parameters of the models stored in database  1414  to determine which model is most similar to the received data. The forecast engine  1412  may determine a similarity metric between the received data and each of the healthcare expense prediction models or a subset of the models. After determining a value of a similarity metric for one or more of the healthcare expense prediction models, the forecast engine  1412  may rank the models and select the model having the highest rank. 
     In some embodiments, the forecast engine  1412  may determine the similarity metric based on the respective similarities of individual parameters included in the information of the models and the received financial and health data of a participant. The forecast engine  1412  may determine how similar the individual parameters are, and from these similarities, calculate an overall similarity value for a model. For example, the received data may include a first portion of information indicating that the participant has a gross annual income of $70,000 per year. The forecast engine  1412  can determine a difference between the received gross annual income and each gross annual income parameters associated with respective models stored in database  1414 , and rank the models based on difference or an absolute value of the difference. Accordingly, the forecast engine  1412  may calculate a higher similarity score for a model including a gross income of $67,000 than for a model including a gross income of $110,000 because the absolute difference between $70,000 and $67,000 is less than the absolute difference between $110,000 and $70,000. 
     In some embodiments, the forecast engine  1412  may allocate predetermined weightings to certain parameters of the healthcare expense models based on how important some parameters are compared to others for the similarity analysis. For example, the parameter of annual income may be weighted heavier than the parameter of geographic location proximity. In some embodiments, the respective weightings associated with individual parameters may be modified at the administrator device  1118 , at the client device  102 , or at the PRAS  1408 . 
     In some embodiments, the forecast engine  1412  performs the similarity analysis for each healthcare expense model in the database  1414  to determine the model most similar to the received financial, health, and personal data. In some embodiments, the forecast engine  1412  performs the similarity analysis on a subset of the total healthcare expense models. For example, in a first step, the forecast engine  1412  may perform a first pass filter to remove or exclude models in the database  1414  that are not yet reliable due to lack of information for that particular model. In some cases, certain models may be flagged as being inactive in the database  1414 . In some embodiments, a participant at the client device  102  may input a filter, and in response to the received filter information (e.g., via data packets), the forecast engine  1412  may exclude healthcare expense models from similarity analysis that are excluded due to the filter. For example, a user may input a filter indicating a desire to target models that are within a certain territory of a country (e.g., a state), in which case the forecast engine  1412  may perform the similarity analysis only on those models that satisfy the filter criteria. 
     The healthcare expense models can be retrieved from a variety of entities, such as client devices  102  or servers (e.g., administrator device  1118 ) associated with an insurance administrator, an employer, a financial institution (e.g., a bank administering or otherwise maintaining an electronic reimbursement account or a payroll account configured for direct deposit). The insurance administrator can establish or otherwise maintain the electronic benefits account. 
     In some embodiments, the forecast engine  1412  may identify non-healthcare expenses of the participant over the participant&#39;s lifetime. The non-healthcare expense model may also be dictated by the selected healthcare expense model that includes parameters similar to the parameters associated with the participant. In other embodiments, the non-healthcare expenses may be calculated based on the data received by the PRAS  1408  instead of, or in addition to, being based on the healthcare expense model. 
     In some embodiments, the forecast engine  1412  may perform a lookup in the database  1414  to identify a healthcare benefits account of the participant associated with the received financial, health, and personal data to provide funds towards the predicted lifetime healthcare expenses of the participant, and a non-healthcare benefits account of the participant to provide funds towards lifetime non-healthcare expenses of the participant. The healthcare account and the non-healthcare account may already be established and associated with the participant, and this information may be stored in the database  1414 . In some embodiments, the PRAS  1408  may remotely access the administrator device  1118  for the participant&#39;s accounts information. In some embodiments, the participant may not currently be enrolled in a healthcare benefits account, a non-healthcare benefits account, or both, and thus the forecast engine  1412  may identify a default one or more benefits account. In some embodiments, the participant may identify one or more accounts that are received by the PRAS  1408 . In some embodiments, the PRAS  1408  may identify one or more accounts that would provide the maximum tax advantage to the participant over a lifetime. For example, the PRAS  1408  may identify that an HSA account may be most beneficial to the participant, or the PRAS  1408  may identify that the participant is already enrolled in both an HSA account and a 401k account with a particular administrator. 
     In some embodiments, based on the predicted lifetime healthcare expenses of the participant, the forecast engine  1412  may determine an amount of funds to allocate per a time period to the identified healthcare tax benefit account. The amount may also be based on the received financial, personal, and health data of the participant. In some embodiments, the PRAS  1412  may determine the amount of funds to allocate to the healthcare tax benefit account based on the allocation priorities associated with each of the electronic benefits accounts (e.g., the health account and the non-health account), in addition to the identified healthcare expense prediction model. 
     For example, the forecast engine  1412  may determine that a healthy (e.g., health indicators such as blood pressure, weight, or cholesterol are within predetermined ranges) and young (e.g., less than 40 years old) participant will incur less lifetime health expenses (e.g., $50,000) as compared to someone who is unhealthy (e.g., health indicators such as blood pressure, weight, or cholesterol that exceed predetermined maximum limits) and young. Because the participant is young and may be able to contribute funds to an account for several years, and because the participant is relatively healthy, the forecast engine  1412  may determine that a lower amount of funds may need to be allocated to the healthcare tax benefit account on an annual basis as compared to a young participant that is unhealthy. The forecast engine  1412  can match the healthy and unhealthy participants with corresponding models to determine or predict the total lifetime healthcare expenses. The forecast engine  1412  can further determine the annual amount to contribute to the account based on configuration parameters. If the participant is middle-aged and particularly unhealthy (e.g., has a number of health complications), and may thus incur a relatively high amount of lifetime health expenses, the forecast engine  1412  can determine that the participant should allocate a relatively large amount of funds to their health benefits account. As another example, the forecast engine  1412  may determine the amount of funds to allocate per time period to the healthcare tax benefit account using a feature indicating demographic information, a feature indicating a healthcare spending amount, a feature indicating a health savings account contribution amount, and a feature indicating a health preference. 
     In some embodiments, based on the predicted lifetime non-healthcare expenses of the participant, the forecast engine  1412  may determine an amount of funds to allocate based on a time interval or period to the identified non-healthcare tax benefit account. The amount may also be based on the received financial, personal, and health data of the participant. The amount may further be based on the lifetime healthcare expenses amount determined by the forecast engine  1412 . The non-healthcare expenses may include, for example, costs or fees associated with everyday living, mortgage payments, rent payments, utility bills, gas, car payments, transportation, food, entertainment, cell phone, or costs associated with vacations. For example, the forecast engine  1412  may determine the amount of funds to allocate per time period to the non-healthcare tax benefit account using one or more features including a feature indicating demographic information, a feature indicating a geographic area or location, a feature indicating a non-healthcare spending amount, and a feature indicating a non-health retirement account contribution amount. 
     In some embodiments, the communication interface  1410  may provide, for presentation via an interactive user interface (UI) at the client device  102  associated with the participant, the amount of funds to allocate to the healthcare tax benefit account and the amount of funds to allocate to the non-healthcare tax benefit account. The interactive user interface may include a control object that receives an input to adjust the amount allocated to the healthcare tax benefit account. In addition, responsive to receiving the input to adjust the amount allocated to the healthcare tax account, the forecast engine  1412  may update a total amount of funds projected to be allocated to the healthcare tax benefit account. The interactive user interface may be sent to the client device  102  for interaction with the participant that initially transmitted the health, profile, and financial data. The interactive user interface may be sent as data packets including header and payload information, and the adjustments of control features at the interactive user interface may be transmitted as data packets including header and payload information. The data packets can include instructions that instruct central processing unit or a dedicated graphics processor of the client device to render the interactive user interface for display via a display device communicatively coupled to the client device and processor. 
     The PRAS  1408  may also generate the interactive UI with an electronic survey including one or more input elements. The interactive UI may receive the financial and health data of the participant. In some embodiments, the interactive UI is sent in response to a request from the client device  102 . The interactive UI may have a plurality of blank fields corresponding to information to be filled pertaining to the participant, and the participant may interact with the UI to fill out the requested information. After completing the electronic survey, the client device  102  may transmit the information entered into the UI to the PRAS  1408 , the information including the financial and health data of the participant. 
     In some embodiments, the PRAS  1408  may generate the interactive UI with a countdown timer set to a predetermined time interval. The predetermined time interval may be an interval set at the PRAS  1408 , at the administrator device  1118 , or at the client device  102 . The time interval may be set to a suitable amount of time for allowing a participant to enter information into the interactive UI, but also not too much time for security purposes. For example, the timer may be short enough such that if a participant were to leave the client device  102  for a period a time, another unauthorized user may access the interactive UI while the authorized participant is away. The PRAS  1408  may initiate the countdown timer responsive to enabling the interactive UI to receive the financial and health data. In some embodiments, once the PRAS  1408  sends the interactive UI to the client device  102  and enables a participant at the client device  102  to enter health and financial information, the PRAS  1408  may initiate the timer. The PRAS  1408  may disable input via the interactive UI responsive to expiration of the countdown timer. In some embodiments, the PRAS  1408  may transmit a time out notification to the client device  102  upon expiration of the timer. 
     In some embodiments, the forecast engine  1412  can update the UI sent to the client device  102  in real-time in response to the adjusted amount triggered at the client device  102  and received at the PRAS  1408  via the communications interface  1410 . The communications interface  1410  can be configured to provide the UI via an application package executed or rendered by a web browser of the client device. The communications interface  1410  can be configured to provide the UI via an application executed by the client device. The communications interface  1410  can be configured to provide the UI via an electronic mail protocol, SMS protocol, transport layer protocol, notification or prompt on a mobile telecommunications devices (e.g., a smartphone, tablet, smartwatch, wearable telecommunications device, laptop computer, desktop computer, etc.). A participant profile maintained in the database  1414  can include other contact information corresponding to the participant associated with the client device  102 , and the PRAS  1408  can be configured to transmit the one or more data packets including the UI to the participant using the contact information via the communications interface  1410 . In some embodiments, the participant profile can include a priority order associated with multiple contact information, a preferred contact information, or an indication of multiple contact information for receiving the UI. For example, the participant profile can indicate an electronic mail protocol as a preferred contact information, and the PRAS  1408  can be configured to identify the electronic mail protocol as the preferred contact information, and transmit the one or more data packets to the participant using the electronic mail protocol via the communications interface  1410 . 
     In some embodiments, the PRAS  1408  can retrieve an electronic UI template configured for the delivering of the results of the operations of the forecast engine  1412 . The forecast engine  1412  can generate the UI using the electronic UI template. The forecast engine  1412  can transmit the one or more data packets carrying the results generated using the electronic UI template to the client device  102  via the communications interface  1410 . For example, the communications interface  1410  can transmit the one or more data packets via at least one of an SMS protocol or an electronic mail protocol. 
     In some embodiments, the PRAS  1408  is configured to retrieve an electronic UI template configured for transmission via a particular transmission protocol. For example, the PRAS  1408  can retrieve an SMS-compatible electronic UI template configured to be compatible with SMS protocol, such as an electronic UI template having a particular character limit and an organization configured to use plain text. The PRAS  1408  can retrieve an electronic mail-compatible electronic UI template configured to be compatible with electronic mail protocol, such as an electronic UI template using rich text or HTML. In some embodiments, the PRAS  1408  can retrieve multiple electronic UI templates compatible with multiple transmission protocols, generate multiple UIs using the multiple transmission protocols, and transmit the multiple UIs via the multiple transmission protocols via the communications interface  1410 . 
     In some embodiments, the PRAS  1408  may include a machine learning engine  1416  executed by the server and configured to train the healthcare expense prediction model with the financial data and the health data of the plurality of participants. The PRAS  1408  may utilize the constantly updated profiles of the stored participant profiles to extrapolate data and to formulate the models based on similar profiles. The PRAS  1408  may constantly receive data regarding the various profiles of the various participants, and may constantly update and refine healthcare expense prediction models based on the newly received data. For example, the PRAS  1408  may store a healthcare expense prediction model corresponding to a middle-aged individual who is relatively healthy and who has an annual income of over $100,000. The PRAS  1408  may monitor the health care tendencies and outcome of this demographic and those who used to be in this demographic to refine the prediction model associated with this demographic. For instance, if an overwhelming majority of elderly people that used to be in this demographic when they were middle-aged do not have many health complications, the prediction model can adjust its predicted health care expenses associated with this middle-aged demographic to account for the likelihood that they will need minimal medical care in their future. The more indications that this demographic will realize good health, as ascertained by the various profiles accessible to the PRAS  1408 , the stronger this correlation becomes and the machine learning engine  1416  may update the healthy middle-aged demographic accordingly. 
     The machine learning engine  1416  can access the information maintained by the PRAS  1408 , due to the PRAS  1408  being connected to the various administrator devices  1118 , with each administrator device  1118  servicing various participants. In some embodiments, the machine learning engine  1416  may access the health-related spending habits of participants to deduce their health status and to directly identify how much and on what health-related costs they are spending on. In addition, the machine learning engine  1416  may parse survey data associated with participants (e.g., health surveys given to the participants by an insurance administrator to determine the participants&#39; level of health). Furthermore, because insurance administrators may require health records from their participants, the PRAS  1408  may access those health records of the participants (e.g., at the administrator devices  1118 ) for use in conjunction with the expense prediction models. In addition, the PRAS  1408  may utilize any other suitable and available information to use with the health expense prediction models for better predicting lifetime health-related expenses for various and diverse participants, such as, but not limited to, participant contribution to health benefits accounts, frequency of physical examinations, amount of exercise, diet, blood pressure, history of disease, family disease history, and so on. 
     In machine learning engine  1416  may access the wealth of information at the disposal of the PRAS  1408  and execute a machine learning technique or algorithm for generating and refining the health expense prediction models stored on the database  1414 . A machine learning algorithm operates by building a model from example inputs in order to make data-driven predictions or decisions, rather than following strictly static program instructions. In some embodiments, the machine learning engine  1416  may employ supervised learning in which a computer is presented with example inputs and their desired outputs, and the goal is to learn a general rule that maps inputs to outputs. In some embodiments, the machine learning engine  1416  may employ unsupervised learning in which no labels are given to the learning algorithm, leaving it alone to find structure in its input. 
     In some embodiments, the machine learning engine  1416  may employ decision tree learning, using a decisions tree as a predictive model, which maps observations out an item to conclusions about the item&#39;s target value. In some embodiments, the machine learning engine  1416  may employ association rule learning, which is a method for discovering interesting relations between variables in large databases. In some embodiments, the machine learning engine  1416  may employ support vector machines (SVM), which are a set of supervised learning methods used for classification and regression. Given a set of training examples, each marked belonging to one of two categories, an SVM training algorithm builds a model that predicts whether a new example falls into one category or the other. In other embodiments, the machine learning engine  1416  may employ any other suitable algorithm for generating and refining the healthcare expense models, such as, but not limited to, clustering, reinforcement learning, representation learning, Bayesian networks, or the like. 
     For example, the machine learning engine  1416  can receive healthcare information as sets of inputs or profiles of participants and divide the sets of inputs into groups using a clustering technique or a classification technique. In some cases, the machine learning engine  1416  can utilize a clustering technique in which the groups are not predetermined. In some cases, the machine learning engine  1416  can use a classification technique in which the groups are predetermined. The cluster generated by the machine learning engine  1416  can include sets of input data or profiles of participants that are more similar to profiles within the cluster as compared to profiles in a different cluster or adjacent cluster. The clustering technique can include generating vectors using multi-dimensional features associated with each profile, and determining a distance between vectors to identify a set of vectors within a threshold distance from one another. The identified set of vectors within the threshold distance from one another can form a cluster. 
     To generate a healthcare expense model, the machine learning engine  1412  can obtain healthcare information and expense data associated with profiles or participants, and train the healthcare model using the feature data and corresponding expense data of each of the participants. The healthcare information and expense data can be input into the PRAS  1408  by a participant or administrator via an interface. The PRAS  1408  can be configured to determine or identify various healthcare information or expense data of a participant or administrator via parsing electronic healthcare transaction processed or received by the PRAS  1408 . For example, the machine learning engine  1416  can be configured with a regression analysis technique that uses a statistical process to estimate the relationship between a feature (e.g., healthy or not healthy) determined from healthcare information (e.g., received from an electronic survey presented by an interactive user interface or determined from a healthcare transactions for purchasing a prescription medication for high cholesterol) and an expense signal (e.g., cost of the prescription medication or healthcare visits or expenses related to complications). The feature (e.g., healthy) can be a predictor or independent variable, and the signal (e.g., expense) can be a dependent variable or a criterion variable that can change as the features are varied. In some cases, the machine learning engine  1416  can estimate, determine or predict a conditional expectation of the dependent variable given the independent variables (e.g., an average value of the dependent variable when the independent variables are fixed; or other parameter or metric of the conditional distribution of the dependent variable or signal given the independent variable or feature). The predicted signal (e.g., expense) can be a function of the independent variables and can be referred to as a regression function. The machine learning engine  1416  can further identify, determine or characterize a variation of the dependent variable around the regression function which can be described by a probability distribution. The machine learning engine  1416  can use the probability distribution to generate a confidence score in the predicted signal value, or use the probability distribution as the confidence score. For a given feature or feature combination, the machine learning engine  1416  can identify the expense corresponding to the highest confidence score, and use this expense to predict an amount of resources or funds a participant should allocate to a tax benefit account based on a time interval in order to have sufficient resources to pay for the predicted healthcare expenses. 
     In some aspects, the system of the present solutions implements a combination of the communications interface  1410 , forecast engine  1412 , machine learning engine  1416 , database  1414 , clients  102   a - n , admin devices  1118   a - n , or heterogeneous electronic funding sources  702   a - n  in an innovative, non-conventional and/or non-routine manner. In some aspects, the system of the present solutions integrates communications interface  1410 , forecast engine  1412 , machine learning engine  1416 , database  1414 , clients  102   a - n , admin devices  1118   a - n , or heterogeneous electronic funding sources  702   a - n  in an innovative, non-conventional and/or non-routine manner to implement the improved functionality, performance and operation of the present solution. In some aspects, the system of the present solutions integrates communications interface  1410 , forecast engine  1412 , machine learning engine  1416 , database  1414 , clients  102   a - n , admin devices  1118   a - n , or heterogeneous electronic funding sources  702   a - n  in an innovative, non-conventional and/or non-routine manner to more efficiently and effectively use computing and networking resources. The communications interface  1410 , forecast engine  1412 , machine learning engine  1416 , database  1414 , clients  102   a - n , admin devices  1118   a - n , or heterogeneous electronic funding sources  702   a - n  are integrated in an innovative, nonconventional manner to mitigate, reduce, prevent, or resolve the technical problems of resource allocation in an electronic transaction based technology platform. The communications interface  1410 , forecast engine  1412 , machine learning engine  1416 , database  1414 , clients  102   a - n , admin devices  1118   a - n , or heterogeneous electronic funding sources  702   a - n  integrated in the innovative, non-conventional manner address at least these technical problems by, for example, receiving financial data indicating a financial snapshot of a participant of a client device and health data of the participant to predict lifetime healthcare expenses of the participant; generating a multi-dimensional feature vector of the participant based on the received financial data and the health data of the participant; identifying a healthcare expense prediction model to predict the future healthcare expenses of the participant; determining from the identified healthcare expense prediction model using the multi-dimensional feature vector of the participant, the predicted lifetime healthcare expenses of the participant; identifying lifetime non-healthcare expenses of the participant; performing a lookup in a database to identify a healthcare tax benefit account of the participant to provide funds towards the predicted lifetime healthcare expenses of the participant and a non-healthcare tax benefit account of the participant to provide funds towards lifetime non-healthcare expenses of the participant; determining, based on the predicted lifetime healthcare expenses of the participant, a first amount of funds to allocate per time period to the healthcare tax benefit account; determining, based on the lifetime non-healthcare expenses of the participant, a second amount of funds to allocate per time period to the non-healthcare tax benefit account; and providing, for presentation via an interactive user interface, the first amount of funds to allocate to the healthcare tax benefit account and the second amount of funds to allocate to the non-healthcare tax benefit account, the interactive user interface including a control object configured to i) receive an input to adjust the first amount, and ii) responsive to receiving the input to adjust the first amount, updating a total amount of funds projected to be allocated to the healthcare tax benefit account. 
     Referring now to  FIG.  15 A , a diagram of an interactive user interface  1500  is depicted. In some embodiments, the UI  1500  may be displayed at the client device  102  for interaction with a participant of an electronic benefits account. The interactive UI  1500  includes a navigation pane  1502 , an instructive prompt  1504 , an inquiry field  1506  (and  1510 ,  1514 , and  1518 ), a value field  1508  (and  1512 ,  1516 , and  1520 ) corresponding to the inquiry field  1506  (and  1510 ,  1514 , and  1518 , respectively), and a navigator  1522 . 
     In some embodiments, the interactive UI  1500  is a page (e.g., a web page) for entering information relevant to the PRAS  1408  for sending to the PRAS  1408 . The navigation pane  1502  includes a highlight indicator  1503  for indicating to a user the page that the UI currently displays. For example, the indicator  1503  indicates to a user that they are currently viewing a page for inputting “The Basics.” In addition, for further guidance, the UI  1500  includes the instructive prompt  1504  for further guiding the user as to what to do on this page. For example, the instructive prompt  1504  may welcome the user and guide the user by stating: “Let&#39;s start off with a couple of basic questions. Please answer the questions below.” 
     In some embodiments, the interactive UI  1500  may display one or more basic questions for the participant to answer. The questions may be general questions the answers to which will be transmitted to the PRAS  1408  and will enable the PRAS  1408  to perform its calculations. For example, inquiry field  1506  states: “How old are you?” In response to this question, the field  1508  has been filled with the number “32.” Inquiry field  1510  states: “At what age do you plan to retire?” In response to this question, the field  1512  has been filled with the number “60.” Inquiry field  1514  states: “Are you male or female?” In response to this question, an option of the field  1516  has been selected, the selection corresponding to “Male.” Inquiry field  1518  states: “What is your marital status?” In response to this question, an option of the field  1520  has been selected, the selection corresponding to “Married with Kid(s).” In some embodiments, the value fields  1508 ,  1512 ,  1516 , and  1520  may be a text box for entering in text by a participant. In other embodiments, the value field  1508  may provide a list of possible values that the participant may select (e.g., “male” or “female”). Once a participant has entered responses to the questions, the participant may interact with the navigator  1522  to continue to the next page, or to a previous page, as desired. 
     The PRAS  1408  can receive inputs corresponding to questions  1506 ,  1510 ,  1514 , and  1518  and can identify features for the participant and determine values for the features. For example, the PRAS  1408  can generate a first feature indicative of age, with values of young, middle-aged, and elderly. The PRAS  1408  can determine a first value of the first feature based on a first mapping that maps the input to the first feature value. For example, the input of 32 years ( 1508 ) can map to a first feature value of young. The PRAS  1408  can determine a second value for a second feature corresponding to retirement age (question  1510 ). The PRAS  1408  can include a second mapping different from the first mapping. For example, a second input  1512  of 60 years can map to a second value of young for the second feature because retiring at age 60 may be determined to be a young retirement age. The PRAS  1408  can determine a third value for a third feature corresponding to gender (question  1514 ). The PRAS  1408  can include a third mapping different from the first and second mappings. For example, a third input  1516  of “male” can map to a third value of male for the third feature. The PRAS  1408  can determine a fourth value for a fourth feature corresponding to marital status (question  1518 ). The PRAS  1408  can include a fourth mapping different from the first, second, and third mapping. For example, a fourth input  1520  of “married with kid(s)” can map to a fourth value of married with kid(s) for the fourth feature. In some embodiments, PRAS  1408  can combine two or more of the determined features to perform a fifth mapping different from the first, second, third, and fourth mappings to determine a fifth value for a fifth feature. For example, the first input  1506  and the fourth input  1518  can map to a fifth value of “young family.” 
     Referring now to  FIG.  15 B , a diagram of an interactive user interface  1520  is depicted. In some embodiments, the UI  1520  may be displayed at the client device  102  for interaction with a participant of an electronic benefits account. The interactive UI  1520  includes the navigation pane  1502 , an instructive prompt  1524 , an inquiry field  1525  (and  1527 ,  1529 ,  1531 ,  1533 ,  1535 , and  1537 ), a value field  1525  (and  1528 ,  1530 ,  1532 ,  1534 ,  1536 , and  1538 ) corresponding to the inquiry field  1524  (and  1527 ,  1529 ,  1531 ,  1533 ,  1535 , and  1537 , respectively), a control feature  1526 , and a navigator  1539 . 
     In some embodiments, the interactive UI  1520  is a page (e.g., a web page) for entering information relevant to the PRAS  1408  for sending to the PRAS  1408 . The navigation pane  1502  includes a highlight indicator  1522  for indicating to a user the page that the UI currently displays. For example, the indicator  1522  indicates to a user that they are currently viewing a page for inputting “Your Finances.” In addition, for further guidance, the UI  1520  includes the instructive prompt  1523  for further guiding the user as to what to do on this page. For example, the instructive prompt  1523  may guide the user by stating: “Next, we&#39;ll need to know some information about your finances. Please answer the questions below.” 
     In some embodiments, the interactive UI  1520  may display one or more questions for the participant to answer. The questions may be financial-related questions the answers to which will be transmitted to the PRAS  1408  and will enable the PRAS  1408  to perform its calculations. For example, inquiry field  1524  states: “How much do you typically spend on healthcare per year? Please don&#39;t include premiums.” In response to this question, the field  1525  has been filled with the value “$700.” The value entered into the value field may be increased or decrease, or otherwise controlled, by the control feature  1526 . The control feature  1526  is an interactive element embedded in the UI  1520  such that a user may interact with the control feature  1526  to control the value in the value field  1525 . 
     In addition, inquiry field  1527  states: “What is your annual household income?” In response to this question, the field  1528  has been filled with the value “$130,400.” Inquiry field  1529  states: “How much do you contribute to your HAS annually?” In response to this question, the field  1530  has been filled with the value “$1000.” Inquiry field  1531  states: “What percent of your income do you contribute to a 401k annually?” In response to this question, the field  1531  has been filled with the value “8%.” Inquiry field  1533  states: “How much does your employer match?” In response to this question, the field  1534  has been filled with the value “4%”. Inquiry field  1535  states: “How much have you saved for retirement?” In response to this question, the field  1536  has been filled with the value “$105,800.” Inquiry field  1537  states: “How much healthcare funds have you saved for retirement? (Health Savings Account).” In response to this question, the field  1538  has been filled with the value “$500.” In some embodiments, each, some, or none of the values in the respective value fields may include a slider for controlling a corresponding value. 
     The PRAS  1408  can receive inputs corresponding to questions  1524 ,  1527 ,  1529 ,  1531 ,  1533 ,  1535 , and  1537  and can identify features for the participant and determine values for the features. For example, the PRAS  1408  can generate a first feature indicative of healthcare expenditures, with values of high, medium, and low. The PRAS  1408  can determine a first value of the first feature based on a first mapping that maps the input to the first feature value. For example, the input of $700 ( 1525 ) can map to a first feature value of medium. The PRAS  1408  can determine a second value for a second feature corresponding to income (question  1527 ). The PRAS  1408  can include a second mapping different from the first mapping. For example, a second input  1528  of $130,400 can map to a second value of rich for the second feature because an annual income of over $120,000 may be considered rich by the PRAS  1408 . The PRAS  1408  can determine other feature values based on the inputs of  FIG.  15 B  to map certain feature values of features associated with the participant. In some embodiments, PRAS  1408  can combine two or more of the determined features to perform a third mapping different from the first and second mappings to determine a third value for a third feature. In some embodiments, as an example, the predictive expense models can use these features to predict that people with incomes in a certain range may have higher or lower healthcare expenses, and may extrapolate other deductions from other features of the participants. 
     In some embodiments, the value field  1528  may be a text box for entering in text by a participant or a slider controller. In other embodiments, the value field  1528  may provide a list of possible values that the participant may select. Once a participant has entered responses to the questions, the participant may interact with the navigator  1532  to continue to the next page, or to the previous page (e.g., “The Basics” page), as desired. In various embodiments, the information entered into the interactive UI  1520  may correspond to the financial data that is sent to the PRAS  1408 , for use by the forecast engine  1412 . 
     Referring now to  FIG.  15 C , a diagram of an interactive user interface  1540  is depicted. In some embodiments, the UI  1540  may be displayed at the client device  102  for interaction with a participant of an electronic benefits account. The interactive UI  1540  includes the navigation pane  1502 , an instructive prompt  1544 , an inquiry field  1546 , and a value field  1548  corresponding to the inquiry field  1546 . 
     In some embodiments, the interactive UI  1540  is a page (e.g., a web page) for entering information relevant to the PRAS  1408  for sending to the PRAS  1408 . The navigation pane  1502  includes a highlight indicator  1542  for indicating to a user the page that the UI currently displays. For example, the indicator  1542  indicates to a user that they are currently viewing a page for inputting “About You.” In addition, for further guidance, the UI  1540  includes the instructive prompt  1544  for further guiding the user as to what to do on this page. For example, the instructive prompt  1544  may guide the user by stating: “It&#39;s the last step! Tell us a little about your health and preferences. Please answer the questions below.” 
     In some embodiments, the interactive UI  1540  may display one or more questions for the participant to answer. The questions may be health-related questions the answers to which will be transmitted to the PRAS  1408  and will enable the PRAS  1408  to perform its calculations. In some embodiments, the inputs to these queries enable the PRAS  1408  to identify features corresponding to the participant and generate values for the features. Accordingly, the values of the features corresponding to the participant can be input into the expense prediction model generated by the machine learning engine  1416  to determine an output for the participant corresponding to predicted expenses of the participant. 
     Inquiry field  1546  states: “Which of the following best describes your health insurance buying?” In response to this question, the field  1548  has been selected corresponding to the value “I don&#39;t want to pay too much when I see the doctor and get prescriptions.” In some embodiments, the value field  1548  may be a text box for entering in text by a participant or a slider controller. In other embodiments, the value field  1548  may provide a list of possible values that the participant may select. Once a participant has entered or selected responses to the questions, the participant may interact with the navigator  1550  to continue to the next page (e.g., to calculate the results), or revert to the previous page (e.g., “Your Finances” page), as desired. 
     In various embodiments, the information entered into the interactive UI  1540  may correspond to the health data that is sent to the PRAS  1408 , for use by the forecast engine  1412 . In response to selecting the “Calculate” feature in the navigator  1550 , the client  102  may send the entered information to the PRAS  1408 , including the information entered in the UIs  1500 ,  1520 , and  1540 . Accordingly, by clicking the “Calculate” button, the client device  102  can transmit the personal, financial, and health data of the participant so that the forecast engine  1412  may perform operations on the entered data. 
     Referring now to  FIG.  15 D , a diagram of an interactive user interface  1560  is depicted. In some embodiments, the UI  1560  may be displayed at the client device  102  for interaction with a participant of an electronic benefits account. The interactive UI  1560  includes the navigation pane  1502 , a results field  1564 , an overview field  1566 , a healthcare analysis field  1568 , a financial analysis field  1570 , and a graphical result  1572 . 
     In some embodiments, after the financial, personal, and health data is entered in UIs  1500 ,  1520 , and  1540  and are submitted to the PRAS  1408 , the forecast engine  1412  may perform a resource allocation process on the received data. Upon completing the resource allocation process with respect to the received participant data, the PRAS  1408  may send the results of the operations of the forecast engine  1412  to the client device  102  for displaying the results via the interactive UI  1560 . 
     In some embodiments, the interactive UI  1560  is a page (e.g., a web page) for viewing information received from the PRAS  1408 . The navigation pane  1502  includes a highlight indicator  1562  for indicating to a user the page that the UI currently displays. For example, the indicator  1562  indicates to a user that they are currently viewing the “Results” page. Accordingly, the interactive UI  1560  may display the results determined, based on the entered personal, health, and financial data, by the forecast engine  1412 . 
     The results UI  1560  may include a results field  1566 . The results field  1566  includes a non-healthcare account result field  1564   a  and a healthcare account results field  1564   b . Each of the results fields  1564   a  and  1564   b  may indicate a total amount of savings that a participant should save in each account over the participant&#39;s lifetime, as determined by the forecast engine  1412 . In some embodiments, the results fields  1564   a  and  1564   b  may also indicate the amount that the participant will save during the participant&#39;s lifetime. This piece of information may be based on the participant&#39;s current contribution habits, current balances in the accounts, gross income, expected income raises, or the like. This information may be accessed by the PRAS  1408  from the database  1414  or from the administrator device  1118  associated with the participant&#39;s account. In some embodiments, the results field  1506  may also indicate whether the participant is saving enough or not with respect to each of the non-healthcare account ( 1564   a ) and the healthcare account ( 1564   b ). 
     In some embodiments, the overview field  1566  includes a plurality of parameter fields  1566   a  and a plurality of corresponding value fields  1566   b . The overview field  1566  can include basic information pertaining to the participant. The values  1566   b  of the overview field  1566  may be populated based on the participant&#39;s responses to questions in the previous UI pages. In some embodiments, the values  1566   b  of the overview field  1566  may be populated based on information contained in the participant&#39;s profile stored in the administrator device  1118  or the PRAS  1408 . For example, the overview field  1566  may include such parameters as age, gender, annual income, or the like. 
     In some embodiments, the healthcare analysis field  1568  includes a plurality of prompts  1568   a , a plurality of values  1568   b  corresponding to the prompts  1568   a , and a control feature  1568   c . The plurality of prompt  1568   a  indicate various financial attributes associated with the participant&#39;s health savings account, such as, but not limited to, amount needed to save in the healthcare account each year for retirement, amount the participant is currently contributing to the healthcare account, how much the participant should be contributing, or the like. The values  1568   b  correspond to the prompts  1568   a  (e.g., the participant needs to save $4,773 in the health benefits account each year for retirement). 
     In addition, the healthcare analysis field  1568  may include a control feature  1568   c , which may be a slider, or any other feature suitable for adjusting a value of the value fields  1568   b . In some embodiments, the control feature  1568   c  may increase or decrease a value corresponding to the prompt of how much the participant is currently contributing to the health benefits account. As such, a participant may adjust this value, as desired. In response to adjusting the value via the control feature  1568   c , one or more values displayed in the UI  1560  may also change. For example, in response to increasing the value associated with the control feature  1568   c  (e.g., the value of amount currently contributed to HSA), the value associated with the prompt “By the time you retire your HSA might grow to this much” may increase, since the value associated with current yearly contributions increased. This change in the UI  1560  may occur in real-time or responsive to an adjustment to the control feature  1568   c . The adjusted value may be sent to the PRAS  1408  in real-time as updated financial data or health data of the participant, and the PRAS  1408  may calculate the updated values of the UI  1560  in response to the new data and send the updated results to the client device  102  in real-time. Other input features from previous features can also be adjusted to generate an updated value at the UI  1560 . For example, a participant can change the answer to the question “Members of my family can describe the diet we have as . . . ” displayed in  FIG.  15 C , and depending on the adjusted input responsive to the question, the PRAS  1408  may update the values at the UI  1560 . 
     As such, the present solution provides an interactive report to a participant that can reduce the number of requests and processing required because the PRAS  1408  can adjust a single field to update the prediction of expenses. Because the PRAS  1408  includes predictive models trained with data from a plurality of participants over time, the PRAS  1408  can efficiently identify the change in the feature and identify a new predictive model to determine a new prediction. Also, the system can update the healthcare prediction if the change in feature is a healthcare-related feature. Thus, the PRAS  1408  reduces data communications, bandwidth, and processing because it can focus on updating the healthcare expense and savings and efficiently allocate resources for healthcare expenses without re-processing non-healthcare expense. This is especially beneficial for mobile devices where battery and data usage is an issue. In addition, battery life may be saved because the present system updates or renders the screen because with only one field. The system also saves time as a user does not need to re-enter all other inputs, and only need change one input for a new result. 
     Similar to the health analysis field, the UI  1560  may include the financial analysis field  1570  including a plurality of prompts  1570   a , a plurality of values  1570   b  corresponding to the prompts  1570   a , and a control feature  1570   c . The plurality of prompt  1570   a  indicate various financial attributes associated with the participant&#39;s non-healthcare savings account, such as, but not limited to, amount needed to save in the non-healthcare account each year for retirement, amount the participant is currently contributing to the non-healthcare account, how much the participant should be contributing, or the like. The values  1570   b  correspond to the prompts  1570   a . The financial analysis field  1570  may also include the a control feature  1570   c  for adjusting one or more of the values in the value field  1570   b . For example, the control feature  1570   c  may adjust a value corresponding to an amount saved annually in the non-healthcare savings account. Similar to the function of control feature  1568   c , the control feature  1570   c  may cause one or more of the values of the UI  1560  to update based on the changed value. 
     The UI  1560  may further include a graphical result  1572 , which may display the results of the UI  1560  in graphical form. The graphical result  1572  may include an x-axis corresponding to the participant&#39;s age in year and a y-axis corresponding to amounts of money. Accordingly, the graphical result  1572  indicates the amount of savings over time in accordance with the results determined and shown in the UI  1560 . In particular, the graphical result  1572  displays the amount saved in the participant&#39;s HSA account over time as represented by line  1572   c , and the amount saved in the participant&#39;s 401k account over time as represented by line  1572   e . The graphical result  1572  may also indicate target savings in each of the accounts, as illustrated by lines  1572   d  and  1572   f . In other embodiments, other forms of data representation my be depicted in the UI  1560 , such as, but not limited to, a pie chart, a bar chart, or the like. 
     Referring now to  FIG.  16   , a flow diagram depicting an embodiment of a method  1600  of allocating resources using an information technology infrastructure is shown. The method can be performed by one or more component or module of system  1400 , the PRAS  1408 , or one or more component or module depicted in  FIGS.  1 A- 1 D . In brief overview, at step  1605 , a server of a predictive resource allocating system receives financial data indicating a financial snapshot of a participant of a client device and health data of the participant to predict lifetime healthcare expenses of the participant. At step  1610 , the server generates a multi-dimensional feature vector of the participant based on the received financial data and the health data of the participant. At step  1615 , the server identifies a healthcare expense prediction model to predict the future healthcare expenses of the participant, the healthcare expense prediction model generated by the server using financial data and health data of a plurality of participants. At step  1620 , the server determines from the identified healthcare expense prediction model using the multi-dimensional feature vector of the participant, the predicted lifetime healthcare expenses of the participant. At step  1625 , the server identifies lifetime non-healthcare expenses of the participant. At step  1630 , the server performs a lookup in a database to identify a healthcare tax benefit account of the participant to provide funds towards the predicted lifetime healthcare expenses of the participant and a non-healthcare tax benefit account of the participant to provide funds towards lifetime non-healthcare expenses of the participant. At step  1635 , the server determines based on the predicted lifetime healthcare expenses of the participant, a first amount of funds to allocate per time period to the healthcare tax benefit account. At step  1640 , the server determines based on the lifetime non-healthcare expenses of the participant, a second amount of funds to allocate per time period to the non-healthcare tax benefit account. At step  1645 , the server provides, for presentation via an interactive user interface, the first amount of funds to allocate to the healthcare tax benefit account and the second amount of funds to allocate to the non-healthcare tax benefit account, the interactive user interface including a control object configured to i) receive an input to adjust the first amount, and ii) responsive to receiving the input to adjust the first amount, updating a total amount of funds projected to be allocated to the healthcare tax benefit account. 
     Still referring to  FIG.  16   , and in further detail, at step  1605 , a server of a predictive resource allocating system receives financial data indicating a financial snapshot of a participant of a client device and health data of the participant to predict lifetime healthcare expenses of the participant. The server can include one or more processors. The server can include a communications interface for receiving the data. One or more data packets carrying data indicating the request can be received. In some aspects, step  1605  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  1605  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  1605  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     The data can be received via a computer network using a networking protocol. The data can be generated by a client device of a participant. The data packets can include header information and payload information. The header information can include, e.g., TCP header information that can facilitate the routing and transmission of the data packet. The payload information can include data related to, describing, defining, associated with or otherwise about the financial and health data. The one or more data packets can include data identifying the client device or participant sending the data. The client device can generate or obtain information that allows the server to conduct the resource allocation, encapsulate or process the information using a protocol to generate data packets, and transmit the data packets in a secure manner over a network to the server for further processing. The server can initiate a resource allocation process responsive to receiving the one or more data packets. 
     At step  1610 , the server generates a multi-dimensional feature vector of the participant based on the received financial data and the health data of the participant. In some aspects, step  1610  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  1610  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  1610  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     The server can parse the received data and organize the data in the multi-dimensional vector. The server can perform the generating of the vector responsive to receiving the health and financial data. In some embodiments, the server parses the one or more data packets to identify the participant profile, and performs a lookup in an administrator profile database maintained by the server using the identifier to retrieve the participant&#39;s information. The server may generate the multi-dimensional feature vector comprising a first feature indicating demographic information, a second feature indicating a healthcare spend amount, a third feature indicating a health savings account contribution amount, and a fourth feature indicating a health preference. 
     At step  1615 , the server identifies a healthcare expense prediction model to predict the future healthcare expenses of the participant, the healthcare expense prediction model generated by the server using financial data and health data of a plurality of participants. In some aspects, step  1615  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  1615  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  1615  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     The server can access the database to access or identify a relevant predictive model. The server can perform the identifying responsive to the generating of the multi-dimensional vector. The server can perform a similarity analysis between the received financial and health data and each of the stored healthcare expense prediction model, and identify the model that is the most similar to the received financial and health data. The healthcare expense prediction models may be refined and updated as more data of various participants across various administrators is received by the server. The server may include a machine learning engine executed by the server configured to train the healthcare expense prediction model with the financial data and the health data of the plurality of participants. The serve can input the multi-dimensional feature vector into the healthcare expense prediction model to output the predicted lifetime healthcare expenses of the participant, the predicted lifetime healthcare expenses of the participant based on data associated with similar participants used to generate the healthcare expense prediction model. 
     At step  1620 , the server determines from the identified healthcare expense prediction model using the multi-dimensional feature vector of the participant, the predicted lifetime healthcare expenses of the participant. The server can perform the determining responsive to the identifying of the healthcare expense prediction model. The healthcare expenses may include doctor visits, medicine, surgeries, or the like. In some aspects, step  1620  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  1620  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  1620  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     At step  1625 , the server identifies lifetime non-healthcare expenses of the participant. The identifying may be performed responsive to the determining the predicted lifetime healthcare expenses. The non-healthcare expenses may include day-to-day expense, such as, groceries, bills, insurance, or the like. In some aspects, step  1625  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  1625  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  1625  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     At step  1630 , the server performs a lookup in a database to identify a healthcare tax benefit account of the participant to provide funds towards the predicted lifetime healthcare expenses of the participant and a non-healthcare tax benefit account of the participant to provide funds towards lifetime non-healthcare expenses of the participant. The performing may be performed responsive to the identifying of the non-healthcare expenses. The benefit accounts may be those that the participant is enrolled in. The participant&#39;s account information may be accessed from the database of the server or may be accessed remotely, for example, at an administrator of the participant&#39;s accounts. In some aspects, step  1630  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  1630  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  1630  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     At step  1635 , the server determines based on the predicted lifetime healthcare expenses of the participant, a first amount of funds to allocate per time period to the healthcare tax benefit account. In some aspects, step  1635  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  1635  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  1635  is implemented to make or cause more effective and efficient use of computing and networking resources. The first amount may be an amount the participant should contribute to the participant&#39;s healthcare account on a yearly basis to cover the predicted healthcare expenses of the participant. The healthcare tax benefit account may be an HSA account. The server can determine the first amount of funds to allocate per time period to the healthcare tax benefit account using a first feature indicating demographic information, a second feature indicating a healthcare spend amount, a third feature indicating a health savings account contribution amount, and a fourth feature indicating a health preference. 
     At step  1640 , the server determines based on the lifetime non-healthcare expenses of the participant, a second amount of funds to allocate per time period to the non-healthcare tax benefit account. The second amount may be an amount the participant should contribute to the participant&#39;s non-healthcare account on a yearly basis to cover the predicted non-healthcare expenses of the participant. The non-healthcare tax benefit account may be a 401k account. In some aspects, step  1640  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  1640  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  1640  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     The server can determine the second amount of funds to allocate per time period to the non-healthcare tax benefit account using a first feature indicating demographic information, a second feature indicating a non-healthcare spend amount, and a third feature indicating a non-health retirement account contribution amount. The server can determine a first allocation priority associated with the healthcare tax benefit account, and determine a second allocation priority associated with the non-healthcare tax benefit account, the second allocation priority less than the first allocation priority. The server can determine the first amount of funds to allocate to the healthcare tax benefit account based on the first allocation priority, the second allocation priority, and the healthcare expense prediction model. 
     At step  1645 , the server provides, for presentation via an interactive user interface, the first amount of funds to allocate to the healthcare tax benefit account and the second amount of funds to allocate to the non-healthcare tax benefit account, the interactive user interface including a control object configured to i) receive an input to adjust the first amount, and ii) responsive to receiving the input to adjust the first amount, updating a total amount of funds projected to be allocated to the healthcare tax benefit account. In some aspects, step  1645  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  1645  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  1645  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     The server can send the data to be presented via the communications interface of the server. The data sent by the communications interface may be received at the client device of the participant. The interactive user interface displayed to the participant may be adjusted using control features embedded in the UI to adjust input values and to adjust the results based on the adjusted values. The result values may be adjusted in real time in response to the adjusted input values. The server may generate the interactive user interface with an electronic survey comprising one or more input elements, the interactive user interface configured to receive the financial data and the health data. The server may generate the interactive user interface with a countdown timer set to a predetermined time interval. The server may initiate the countdown timer responsive to enabling the interactive user interface to receive the financial data and the health data. The server may disable input via the interactive user interface responsive to expiration of the countdown timer. 
     In some aspects, the methods of the present solutions implements a combination of steps in an innovative, non-conventional and/or non-routine manner. In some aspects, the method  1600  of the present solution combines the steps of  FIG.  16    in an innovative, non-conventional and/or non-routine combination to implement the improved functionality, performance and operation of the present solution. In some aspects, the method of the present solution combines the steps of  FIG.  16    in in an innovative, non-conventional and/or non-routine manner to more efficiently and effectively use computing and networking resources. In some aspects, the method of the present solution provides innovative, non-conventional and/or non-routine ordered combination of steps. 
     G. Reducing Resource Consumption 
     The systems and methods of the present solution are directed to the technical problems and challenges of implementing the functionality of reducing resource consumption via information technology in an electronic transaction based technology and platform. Existing electronic transaction based technologies and platforms do not effectively and efficiently make use of the computing and network resources deployed for electronic transaction based technologies and platforms to include such functionality. Without implementing such functionality, existing electronic transaction based technologies and platforms have the problems of excessive server-client requests and responses, processing delays, increase bandwidth usage, or increased or inefficient resource consumption. 
     The systems and methods of the present solution are directed to the improvement of the performance and operation of the electronic transaction based technology and platform and computing and networking resource used by such electronic transaction based technology and platform. In some aspects, the present solution improves and enhances the implemented functionality of the electronic transaction based technology and platform implemented on, integrated with and inherently tied to the processor, memory, network and computing resources of one or more computing devices. In some aspects, the present solution more effectively performs the functionality of the electronic transaction based technology and platform thereby making and causing more effective use of the computing and networking resources to achieve the improved functionality of the present solution. The same computing and network resources used by such electronic transaction based technology and platform will provide increased and improved functionality with implementation of the present solution. 
     In some aspects, the present solution more efficiently uses the computing and networking resources to implement the improved functionality of the electronic transaction based technology and platform. For example, systems and methods of the present solution are directed to reducing resource consumption via information technology infrastructure. The present solution can determine resource consumption trends and configure an engine to generate a notification based on an event correlation coefficient. 
     Administrators, such as companies or health insurance providers, can establish electronic benefits accounts such as flexible spending accounts or healthcare tax benefit accounts (e.g., health savings accounts) for participants such as employees, subscribers, or customers. These electronic benefits accounts can provide a tax advantage for the participants. Administrators that establish or provide electronic tax benefits accounts for various participants of those accounts can utilize backend information technology infrastructure to process, analyze, monitor or manage the electronic tax benefits accounts. The tax benefit management information technology infrastructure can be configured with processing rules that are applied to electronic transactions. Electronic transactions can include allocating funds to the tax benefit account, withdrawing funds from the tax benefit account, making a purchase with funds from the tax benefit account, modifying a profile of the tax benefit account, or submitting a claim. The management information technology infrastructure can apply one or more rules to each type of transaction to determine an event. As the types of transactions and rules increase in number and complexity, the types and events can also increase in number and complexity, thereby consuming an increasing amount of resources of the information technology infrastructure. For example, events such as a card denial increases the number of transaction attempts, communications with the server, account resets, profile corruption, or resources consumed by a point-of-sale device initiating the transaction. 
     Systems and methods of the present solution can reduce resource consumption of tax benefit information technology infrastructure. For example, a system of the present solution can reduce resource consumption by determining a resource consumption trend. The resource consumption trend can refer to a trend of events such as card denials. The system can then select a recommendation based on the event trend. The system can select the recommendation from a plurality of recommendations by determine or computing an event correlation coefficient between the trend and the recommendation. The event correlation coefficient can refer to a level of correlation between the event or event trend and the recommendation. For example, card transactions may be denied because the cards were being used to make non-qualifying purchases. A highly correlated recommendation may be to provide participants with information on the types of qualifying and non-qualifying purchases so they can avoid attempting to conduct a transaction for a non-qualifying item using funds allocated in an electronic tax benefit account. 
     Upon identifying a recommendation based on the event correlation coefficient, the system can generate a notification. To generate the notification, the system can select a notification template corresponding to the identified recommendation. The system can configure a notification engine with the notification template, and the notification engine can generate a notification. In some cases, the notification engine can automatically generate campaigns based on the trends. The system can provide proactive, client customized communications via email and text messages to participants based on events processed by the system, such as claim paid, card denied, password changed, or deposit received. The system provides a trend based proactive communication plan using data with the administrator, employer or participant data sets. Marketing campaigns can be automatically triggered based on the need identified in the trended data to communicate through various media to educate, promote or advance programs to reduce costs, increase revenue, and/or drive consumer, employer and administrator satisfaction. By automatically identifying transaction event trends and generating notifications based on the trends, the present solution can reduce resource consumption by causing an increase in resource efficient electronic transactions and a decrease in resource intensive electronic transactions. By shifting the types of transactions from resource intensive to resource light, the present solution can improve the functioning of both the tax benefit information technology infrastructure as well as the functioning of associated point of sale devices and computing devices by reducing the number of processing errors or transaction attempts. 
     For example, the system can identify an increase in card denials. The system can identify additional features associated with the card denial and select a trend model that matches the event. The trend model can be further associated with recommendations or transaction modifications that are configured to reduce the type of event. For example, to reduce an increase in card denials, the system can generate a notification that includes processing instructions for the card (e.g., a type of electronic configuration to use for electronic transactions with the card). In another example, the system can generate a notification based on a denial code associated with the event. 
     Referring now to  FIG.  17   , a block diagram depicting an embodiment of a system  1700  that includes a resource consumption reduction system is shown. In brief overview, and in some embodiments, the system  1700  includes a resource consumption reduction system (“RCRS”)  1708 . The RCRS  1708  can include one or more servers  106   a - n . In some embodiments, the RCRS  1708  can include the MPTS  120  depicted in  FIG.  2   , the MPTS  408  depicted in  FIG.  4   , the TEPS  708  depicted in  FIG.  7   , the AMRGS  1108  depicted in  FIG.  11   , the PRAS  1408  depicted in  FIG.  14   , or one or more components or modules depicted in  FIG.  2 ,  4 ,  7 ,  11   , or  14 , and can perform the functions of the MPTS  120 , MPTS  408 , TEPS  708 , the AMRGS  1108 , or the PRAS  1408 . The RCRS  1708  can receive or transmit data via a network  104  with computing devices participant computing device  1702   a - n , administrator devices  1160   a - n , heterogeneous funding sources  702   a - n , POS terminals  202   a - n , or a claims processor  220 . The participant computing devices  1702   a - n  can include one or more component or functionality of client computing devices  102   a - n.    
     In some embodiments, the RCRS  1708  includes a communications interface  1710  designed and constructed to receive and transmit data packets for tax benefit electronic transactions. The RCRS  1708  can include a forecast engine  1712  designed and constructed to use the received data packets to identify a corresponding transaction trend model. The RCRS  1708  can include a notification engine  1714  designed and constructed to select a resource consumption reduction recommendation corresponding to the identified transaction trend model, generate a notification for the recommendation, and provide the notification to the communications interface  1710  for transmission to a participant computing device  1702   a . The RCRS  1708  can include a database  1718  stored in storage device or memory accessible to the RCRS  1708 . The database  1708  can include, store, or maintain event information, trend models, templates, or recommendations. The database  1708  can communicate or interface with one or more of the communications interface  1710 , forecast engine  1712 , notification engine  1714  and healthcare management platform  1716 . 
     Still referring to  FIG.  17   , and in further detail, the communications interface  1710  can include the communications interface  210  depicted in  FIG.  2   , the communications interface  410  depicted in  FIG.  4   , the communications interface  710  depicted in  FIG.  7   , the communications interface  1110  depicted in  FIG.  11   , or the communications interface  1410  depicted in  FIG.  14   , or one or more components or modules depicted in  FIG.  2 ,  4 ,  7 ,  11   , or  14  and can perform the functions of the communications interfaces  210 ,  410 ,  710 ,  1110 , or  1410 . The communications interface  1710  is configured with one or more communications ports, application programming interfaces, network protocols (e.g., TCP/IP), authentication protocols, or security protocols (e.g., SSL). The communications interface  1710  can receive data associated with tax benefit electronic transactions for one or more participant devices  1702   a - n . In some aspects, the communications interface  1710  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, the communications interface  1710  is implemented to make or cause more effective and efficient use of computing and networking resources. For example, the communications interface  1710  can cause more effective and efficient use of computing and network resources by reducing the number of processing cycles, memory or network bandwidth used to determine resource allocations to reduce resource consumption. The communications interface  1710  can provide a reduction in resource consumption by integrating with a forecast engine  1712 , notification engine  1714 , healthcare management platform  1716 , database  1718 , participant computing devices  1702   a - n , admin devices  1160   a - n , claims processor  220 , POS terminals  202   a - n , or heterogeneous electronic funding sources  702   a - n  to allocate resources or reduce resource consumption. 
     The communications interface  1710  can receive one or more data packets including data indicating a healthcare transaction event corresponding to a participant of a plurality of participants of a healthcare management platform. The communications interface  1710  can receive the data packets via network  104  from one or more devices. In some cases, the communications interface  1710  receives data packets indicative of an electronic transaction, and then the RCRS  1708  processes the data packets to determine, generate or identify the healthcare transaction event. In some cases, the communications interface  1710  receives the data packets from a healthcare management platform or one or more system or depicted or described in  FIGS.  1 - 16   . 
     In some embodiments, the RCRS  1708  can receive data packets from a device of an administrator remote from the server and use these data packets to generate or train a trend model. The data packets used to train the trend model can be referred to as previously received data packets because they may be received prior to the current transaction event that triggers the generation of a notification. For example, the RCRS  1708  can cause an administrator interface (e.g., an interface including a graphical user interface including text input, fields, drop down menus, a batch upload mechanism, or a file browser) to be rendered on the device of the administrator. The administrator can input a file or data indicative of the transaction via the administrator interface, and the administrator interface can convert the file or data into data packets suitable for transmission over network  104  to communications interface  1710 . Conversion of the data into a suitable for transmission form can include converting the data into network packets such as TCP/IP packets or encapsulating the packets using a security protocol or encryption protocol. 
     For example, the communications interface  1710  can receive data packets that indicate a claim payment, a card denial, a password change, or a received deposit. The data packets can include network data packets such as TCP/IP data packets. The data packets can be encrypted with a data encryption technique. The data packets can be sent via a secure communication channel established with another server or computing device. The data packets can include a header and payload data. 
     A claim payment can refer to a payment by an insurance provider based on terms of an insurance policy. For example, the claims processor  220  can process a request for a claim payment and then generate an event indicating a claim payment to an electronic account of the participant. The claims processor  220  can transmit the indication to the RCRS  1708 . 
     A card denial can refer to a denial to withdraw or use funds from an electronic tax benefit account. The term card can also include other types of transaction mechanisms, including, e.g., wireless mobile device-based payment mechanisms such as NFC or Bluetooth enabled payment techniques, or inputting an identifier of the electronic tax benefit account into an interface. The denial can refer to a denial to allocate funds towards the transaction. The denial can be associated with a denial code that indicates a reason for the denial. The denial code can indicate, for example, a lack of sufficient funds in the account, incorrect processing parameter or configuration (e.g., transaction cannot be processed as a debit transaction or a credit transaction; incorrect pin number), the transaction includes non-qualifying items, the transaction is occurring at a non-qualifying merchant, or the card has expired. 
     A received deposit can refer to allocating funds to an electronic tax benefit account of the participant. For example, funds can be allocated to the electronic tax benefit account from one or more heterogeneous electronic funding sources  702   a - n  using one or more allocation techniques, such as direct deposit, pay roll, wire transfer, or ACH. The RCRS  1708  can process the deposit or the RCRS  1708  can receive an indication of the deposit. 
     The RCRS  1708  can include a forecast engine  1712  designed and constructed to select a healthcare trend model used to identify healthcare related recommendations to provide to participants of the healthcare management platform. In some aspects, the forecast engine  1712  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, the forecast engine  1712  is implemented to make or cause more effective and efficient use of computing and networking resources. For example, the forecast engine  1712  can cause more effective and efficient use of computing and network resources by reducing the number of processing cycles, memory or network bandwidth used to determine resource allocations to reduce resource consumption. The forecast engine  1712  can provide a reduction in resource consumption by integrating with the communications interface  1710 , notification engine  1714 , healthcare management platform  1716 , database  1718 , participant computing devices  1702   a - n , admin devices  1160   a - n , claims processor  220 , POS terminals  202   a - n , or heterogeneous electronic funding sources  702   a - n  to allocate resources or reduce resource consumption. 
     In some embodiments, the forecast engine  1712  can include one or more component or functionality of forecast engine  1412 . In some embodiments, the forecast engine  1712  can train one or more healthcare trend models using previously received data packets that indicate healthcare transaction events corresponding to participants of the healthcare management platform. To train the healthcare trend model, the forecast engine  1712  can obtain electronic tax benefit account transaction information, and electronic tax benefit account transaction event information associated with profiles or participants. The forecast engine  1712  can maintain historical transaction and event data and monitor transactions occurring in real-time or data received from one or more component of the system  1700  in real-time. The forecast engine  1712  can be configured with one or more trend detection techniques to identify an increase or spike in a type of event, or to identify a decrease or lull in a type of an event. The forecast engine  1712  can identify or determine additional characteristics associated with the increase or decrease in types of events, such as the rate of increase or decrease, features associated with the events (e.g., geographic area associated with the increase or decrease, type of transaction, transaction method, type of merchant, time of day, or portion of month or year). 
     In some embodiments, the forecast engine  1712  can be configured with a trend detection technique that uses historical transaction and event data to generate a baseline model. The baseline model can indicate a baseline threshold, for example, a number of card denials for a type of transaction during a time interval. The forecast engine  1712  can monitor transactions occurring in real-time, or transaction data received via communications interface  1710 . The forecast engine  1712  can generate a metric for the transactions and compare the metric with the baseline threshold of the trend model. If the metric meets or exceeds the baseline threshold, the RCRS  1708  can determine that there is an increase or spike in the type of event. If the metric falls below the baseline threshold, the RCRS  1708  can determine that there is decrease or lull in the type of event. 
     In some embodiments, the forecast engine  1712  can categorize healthcare transaction events into a first category selected from a plurality of categories. For example, the categories of health care transaction events can include denial, claim payment, deposit, password change, stolen card number, disputed transaction, or insufficient funds. The forecast engine  1712  may generate a separate healthcare trend model for each category, where each healthcare trend model includes a baseline model or baseline threshold. In some cases, each healthcare trend model can further includes sub-models for sub-categories for features such as geographic area, temporal values (e.g., time of day, time of year), or demographic indicators. For a given transaction, the forecast engine can determine one or more features, and then select a healthcare trend model matching the determined features. If the RCRS  1708  identify only one feature, such as event type, then the RCRS  1708  can select the broadest healthcare trend model matching the identified feature. If the RCRS  1708  can identify multiple features associated with the event, such as type of event, geographic area, and time of year (e.g., 4 th  quarter), then the RCRS  1708  can select a healthcare trend model that matches this combination of features. For example, if the event is a denial that occurred in Boston, Mass. during the fourth quarter of the year, the forecast engine  1708  can select a healthcare trend model that includes a baseline model for historical denials that occurred in Boston, Mass. during a fourth quarter. 
     In some embodiments, the RCRS  1708  can generate vectors in a multidimensional graph for features associated with an event and trends to select the trend having a minimum vector distance to the event. For example, the RCRS  1708  can generate a first vector based on the healthcare transaction event and one or more healthcare transaction events of the participants. The vector can include features of the event and historical events such as geographic area, type of event, or time of day. The RCRS  1708  can identify a second vector for each of a plurality of healthcare transaction trend models. The second vectors can each be based on feature values corresponding to the healthcare transaction trend models. The RCRS  1708  can determine distance between the first vector and each of the second vectors. The distance can refer to a vector or a magnitude of the distance. For example, the RCRS  1708  can determine a distance vector between an endpoint of the first vector and an end point of the second vector, and then determine the distance as a magnitude of the distance vector. The RCRS  1708  can identify a minimum distance vector from the determined distance vector for each of the plurality of healthcare transaction events, and select the healthcare trend model corresponding to the minimum distance vector. 
     In some embodiments, the forecast engine  1712  can be configured with one or more of a smoothing filter, a significant change detection algorithm, a threshold selector or a dynamic threshold. The smoothing filter can be configured to smooth a data set to create an approximating function that indicates patterns in the data, while leaving out noise or other fine-scale structures. For example, the forecast engine  1712  can use a smoothing filter such as a moving average to determine a baseline curve that fits a data set including a type of event over a time interval. The moving average can capture trends in the event data by creating a series of averages of different subsets of the full data set. The forecast engine  1712  can determine an event trend above a threshold and, responsive to determining the event trend above the threshold, trigger the notification engine  1714  to initiate. 
     In some embodiments, the forecast engine  1712  can determine whether a recommendation is correlated with a reduction in a number of events or a desired event trend. The forecast engine  1712  can correlate a reduction in events with one or more features of transactions to determine which features resulted in the reduction. The forecast engine  1712  can correlate a reduction in events with one or more recommendations or notification that were previously transmitted to participants to determine whether features associated with the recommendation or notification are correlated with the desired event trend. 
     For example, the forecast engine  1712  can receive data indicating that a type of notification was sent to participants. The forecast engine  1712  can monitor event trends before and after the notification was transmitted to participants to identify a change in the trend. If the forecast engine  1712  determines that the notification resulted in a reduction of resource consumption of the RCRS  1708  (e.g., fewer computing resources were used to process denials), then the forecast engine  1712  can link the notification with the reduction of the event. If the forecast engine  1712  at a later time identifies an increase in the type of event, the RCRS  1708  can automatically determine the type of event and corresponding features, identify the type of recommendation correlated with a reduction of the event, and transmit the notification. Types of recommendations can include informational, warning, alert, advertisement, descriptive, customized, or general. 
     The forecast engine  1712  can use a machine learning engine or technique to correlate notifications including recommendations with a change in an event trend. For example, the forecast engine  1712  can be configured with one or more techniques of the machine learning engine  1416 . The forecast engine  1712  can generate a feature indicative of the notification and use the trend data as signals that are dependent on the features. The forecast engine  1712  can be configured with a regression analysis technique that uses a statistical process to estimate the relationship between a feature (e.g., type of recommendation; time of day notification was sent out; geographic area notification was sent; communication medium of notification such as text, email, print, direct mail, television or radio advertisement) and an event trend signal (e.g., increase or decrease in number of events, increase or decrease in number of events in one or more geographic areas or across a demographic). The feature (e.g., type of recommendation) can be a predictor or independent variable, and the signal (e.g., event trend) can be a dependent variable or a criterion variable that can change as the features are varied. In some cases, the forecast engine  1712  can estimate, determine or predict a conditional expectation of the dependent variable given the independent variables (e.g., an average value of the dependent variable when the independent variables are fixed; or other parameter or metric of the conditional distribution of the dependent variable or signal given the independent variable or feature). The predicted signal (e.g., event trend) can be a function of the independent variables and can be referred to as a regression function. The forecast engine  1712  can further identify, determine or characterize a variation of the dependent variable around the regression function which can be described by a probability distribution. The forecast engine  1712  can use the probability distribution to generate a correlation coefficient or confidence score in the predicted signal value, or use the probability distribution as the correlation coefficient or confidence score. For a given feature or feature combination, the forecast engine  1712  can identify the event trend corresponding to the highest confidence score to the recommendation, and select this recommendation to generate and transmit a new notification. 
     The RCRS  1708  can include a notification engine  1714  designed and constructed to identify a notification template based on an event or event trend, and transmit the notification to one or more participants. In some aspects, the notification engine  1714  is implemented to make or cause more effective and efficient use of computing and networking resources. For example, the notification engine  1714  can cause more effective and efficient use of computing and network resources by reducing the number of processing cycles, memory or network bandwidth used to determine resource allocations to reduce resource consumption. The notification engine  1714  can provide a reduction in resource consumption by integrating with the communications interface  1710 , forecast engine  1712 , healthcare management platform  1716 , database  1718 , participant computing devices  1702   a - n , admin devices  1160   a - n , claims processor  220 , POS terminals  202   a - n , or heterogeneous electronic funding sources  702   a - n  to allocate resources or reduce resource consumption. 
     The notification template can include or identify text, fields, images, multimedia, data format, or a communication medium. In some cases, the notification template includes predetermined text in a predetermined format. The notification template can include fields that can be customized to a type of event, time of day, geographic area, or other feature associated with an event or participant. The notification engine  1714  can determine, identify or select a notification template using one or more techniques. For example, the notification engine  1714  can select the notification template from a predetermined recommendation data structure that assigns recommendations to event trends. In another example, the notification engine  1714  can select a random notification template. In yet another example, the notification engine  1714  can determine a notification template for a recommendation that satisfies a correlation coefficient with a corresponding trend model. 
     The notification engine  1714  can perform a lookup in the recommendation data structure stored in database  1718  using an identifier of the selected healthcare trend model to identify a healthcare related recommendation. In some cases, the notification engine  1714  can identify multiple healthcare related recommendations linked with the selected healthcare trend model. The RCRS  1708  can determine a correlation coefficient between each of the plurality of healthcare related recommendations and the selected healthcare trend model. The RCRS  1708  can rank the healthcare related recommendations based on the correlation coefficient. For example, a recommendation with a high correlation coefficient can be ranked higher than a low correlation coefficient because a high correlation coefficient can indicate a high level of correlation. Correlation coefficient can be a numeric value in the range of 0 to 1, 1 to 10, 1 to 100, a percentage or any other indicator of a level of correlation. The RCRS  1708  can select a highest ranking healthcare related recommendation of the plurality of healthcare related recommendations. 
     The RCRS  1708  can determine the correlation coefficient between recommendations, notification templates, and event trends. For example, a first type of recommendation can be highly correlated with a reduction in event trend if the first type of recommendation resulted in a reduction in the number of events below a threshold amount during a predetermined time interval (e.g., 5% reduction within 2 weeks). A higher reduction percentage and shorter time interval can indicate a higher correlation coefficient. If a recommendation does not affect the event trend, then it may correspond to a low correlation coefficient. 
     Similar to recommendations, notification templates can be correlated with event trends. For example, the same recommendation can be made using one or more notification templates. A notification template can refer to a communication medium for the notification, font, text size, image, format, color, multimedia, time of day notification, or day of week of notification. The RCRS  1708  can cycle through various notification templates or recommendations to identify notification templates or recommendations that are highly correlated with a desired event trend. The RCRS  1708  can use a machine learning technique to determine the notification template or recommendation that is highly correlated with an event trend or change in event trend. 
     In some cases, the notification engine  1714  can select a notification template from a predetermined recommendation data structure stored in database  1718 . For example, the RCRS  1708  can receive a configuration file from a user that maps event trends to notification templates or recommendations. When the RCRS  1708  identifies an event trend, the RCRS  1708  can select the corresponding notification template and recommendation, generate the notification, and transmit the notification. 
     In some embodiments, the notification engine  1714  can select a default notification template that is not correlated or tied to the event trend. For example, the RCRS  1708  can determine that a particular event is not correlated to a recommendation or notification template. For example, there may be an absence of a notification template for an event trend. The RCRS  1708  can then select a default notification template for the event trend and update the recommendation data structure in database  1718  to include the selected default notification template. The RCRS  1708  can monitor the event trend responsive to transmitting the default notification to determine whether the notification causes a reduction in resource consumption. In the event the selected default notification did not cause an improvement in the event trend or reduction in resource consumption, the RCRS  1708  can select a different notification template. The RCRS  1708  can continue to cycle through different notification templates or recommendations until the RCRS  1708  identifies a notification template and recommendation that causes a reduction in resource consumption or event trend that satisfies a threshold. 
     Upon identifying a recommendation, the RCRS  1708  can retrieve a notification template from a notification template data structure that maps to the healthcare related recommendation. The RCRS  1708  can use the notification template to generate a notification corresponding to the highest ranking healthcare related recommendation. For example, the RCRS  1708  can populate one or more fields in the notification template with recommendation information. The RCRS  1708  can populate one or more fields in the notification template with data customized for a participant. The notification engine  1714  can generate a request to deliver the notification corresponding to the highest ranking healthcare related recommendation at a destination address of a computing device  1702   a  of the participant. The RCRS  1708  can transmit the notification to the computing device  1702   a  via a communication channel established between the server and the computing device. For example, the communication interface  1710  can establish a communication channel between the computing device and the server using a TCP/IP protocol. In some cases, establishing a communication channel can include transmitting a text message such as a SMS message over a network provided by a cellular service provider and network  104 . In some cases, establishing a communication channel can include transmitting an electronic mail message via an email service provider and data network  104 . 
     In one example, the healthcare transaction event can include a denial of a transaction. A denial of the transaction can refer to a participant swiping card linked to the participant&#39;s electronic tax benefit account at a POS terminal  202   a . The RCRS  1708  can receive data packets from the POS terminal  202   a  indicating the denial of the transaction. In some cases, the RCRS  1708  can receive data packets indicating the transaction from the POS  202   a , and the RCRS  1708  can determine to deny the transaction. In some cases, a healthcare management platform  1716  processes the transaction, determines to deny the transaction, and transmits the data packets indicating denial to the RCRS  1708 . For example, the RCRS  1708  can include the healthcare management platform  1716 . The healthcare management platform  1716  can include one or more component or functionality depicted in  FIGS.  1 A- 16   . 
     The RCRS  1708  can determine that there has been an increase in transaction denials above a threshold that may cause or result in an unsatisfactory increase in resource consumption of the information technology infrastructure. The RCRS  1708  can select a denial recommendation that is correlated with the denial event. The denial recommendation can be correlated with a reduction in the event rend. For example, the RCRS  1708  can determine, based on historical trend data and a machine learning technique, that the denial recommendation reduces denial events by 5% over two weeks. The denial recommendation can include instructions on how to properly process a transaction such as a recommended processing configuration. For example, a card transaction can be processed as a debit card transaction or a credit card transaction. In some cases, a POS terminal  202  at a merchant may be configured to only process credit card transactions. Thus, an attempt at a debit card transaction can result in a denial of the transaction. To reduce the spike in denial events, the RCRS  1708  can generate a recommendation that instructs participants to configure the transaction as a credit card transaction. In some cases, the recommendation may identify types of merchants that only process transactions as credit transactions. 
     In some cases, the RCRS  1708  can determine the denial event based on a denial reason or code, and select a denial recommendation corresponding to the denial reason or code. Denial reasons can include incorrect processing configuration (e.g., credit verses debit card), insufficient funds, non-qualifying purchase, or invalid card. If the denial reason maps to insufficient funds, and there is an increased trend of denials due to this reason, the RCRS  1708  can generate a denial recommendation that recommends a resource allocation amount. For example, the RCRS  1708  can indicate to maintain a minimum balance of funds in the tax benefit electronic account to avoid denials. 
     In some embodiments, the denial event trend can be a trend of partial denials of transactions. For example, a transaction can be denied because the transaction includes both qualifying and non-qualifying items. In some embodiments, a partial denial can refer to the entire transaction being denied because the transaction includes both qualifying and non-qualifying items. In some embodiments, a partial denial can refer to only the non-qualifying items being denied. The RCRS  1708  can select a denial recommendation that includes an ordered list of qualifying items and non-qualifying items responsive to determining that the denial healthcare transaction event resulted from a transaction including one or more qualifying items and one or more non-qualifying items. The RCRS  1708  can retrieve the ordered list from the recommendation data structure stored in database  1718 . Qualifying items can include, e.g., prescription medications or doctor co-payments. Non-qualifying items can include chips or soda. 
     In some embodiments, the notification engine  1714  can identify participant computing devices to transmit the notification to using a targeting criteria. Targeting criteria can include, for example, location, type of computing device, or type of event or transaction associated with the participant computing device  1702 . For example, if a set of multiple participant computing devices as associated with the event and the event trend that triggered the generation of the notification, the RCRS  1708  can automatically generate a marketing campaign to send the notification with the recommendation to the corresponding participant devices. The server can, in some embodiments, customize the notification for each participant computing device  1702   a - n  by using different notification templates based on device type (e.g., screen size or communication medium). The notification engine  1714  can automatically update the marketing campaign by monitoring event trends and triggering the generation of new notifications with new recommendations responsive to the determined event trend that falls outside threshold. 
     In some aspects, the system of the present solutions implements a combination of one or more of the communications interface  1710 , forecast engine  1712 , notification engine  1714 , database  1718 , or healthcare management platform  1716  in an innovative, non-conventional and/or non-routine manner. In some aspects, the system of the present solutions integrates the communications interface  1710 , forecast engine  1712 , notification engine  1714 , database  1718 , or healthcare management platform  1716  in an innovative, non-conventional and/or non-routine manner to implement the improved functionality, performance and operation of the present solution. In some aspects, the system of the present solutions integrates the communications interface  1710 , forecast engine  1712 , notification engine  1714 , database  1718 , or healthcare management platform  1716  in an innovative, non-conventional and/or non-routine manner to more efficiently and effectively use computing and networking resources. The communications interface  1710 , forecast engine  1712 , notification engine  1714 , database  1718 , or healthcare management platform  1716  are integrated in an innovative, nonconventional manner to mitigate, reduce, prevent, or resolve the technical problems of excessive resource consumption. The communications interface  1710 , forecast engine  1712 , notification engine  1714 , database  1718 , or healthcare management platform  1716  integrated in the innovative, non-conventional manner address at least these technical problems by receiving one or more data packets including data indicating a healthcare transaction event corresponding to a participant of a plurality of participants of a healthcare management platform; selecting a healthcare trend model to provide healthcare related recommendations to the plurality of participants of the healthcare management platform maintained by the server, the healthcare trend model trained by the server using previously received data packets including data indicating healthcare transaction events corresponding to the plurality of participants of the healthcare management platform; performing a lookup in a recommendation data structure using an identifier of the selected healthcare trend model to identify a plurality of healthcare related recommendations linked with the selected healthcare trend model; determining a correlation coefficient between each of the plurality of healthcare related recommendations and the selected healthcare trend model; selecting, based on a rank of each correlation coefficient, a highest ranking healthcare related recommendation of the plurality of healthcare related recommendations; retrieving, responsive to the selection of the highest ranking healthcare related recommendation, a notification template from a notification template data structure that maps to the highest ranking healthcare related recommendation; generating, using the notification template, a notification corresponding to the highest ranking healthcare related recommendation; generating a request to deliver the notification corresponding to the highest ranking healthcare related recommendation at a destination address of a computing device of the participant; and transmitting, to the computing device via a communication channel established between the server and the computing device, responsive to the request, the notification to the computing device of the participant. 
     Referring now to  FIG.  18   , a flow diagram depicting an embodiment of a method  1800  of reducing resource consumption via information technology infrastructure is shown. The method can be performed by one or more component or module of system  1700 , the RCRS  1708 , or one or more component or module depicted in  FIGS.  1 A- 1 D . In brief overview, and in some embodiments, the method  1800  includes a server receiving data packets indicating a healthcare transaction event of a participant at step  1805 . At step  1810 , the server selects a healthcare trend model to provide a healthcare related recommendation. At  1815 , the server performs a lookup to identify healthcare related recommendations. At  1820 , the server determines correlation coefficients for the recommendations. At  1825 , the server selects a highest ranking healthcare related recommendation and retrieves a corresponding notification template. At  1830 , the server generates a notification corresponding to the highest ranking healthcare related recommendation. At  1835 , the server generates a request to deliver the notification and transmit the notification. 
     In further detail, the server receives data packets indicating a healthcare transaction event of a participant at step  1805 . In some aspects, step  1805  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  1805  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  1805  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     The server can receive the data packets via a communications interface. The data packets can indicate a transaction event such as a denial, password change, claim deposit, or detected fraudulent card use. The server can parse the payload data of the data packets to identify the event. For example, the server can parse one or more received data packets and determine a type of event. In some cases, the data packets can include an event data structure that defines or describes the transaction event. The event data structure provided via the data packets can include one or more of an event type (e.g., denial, password change, claim payment), participant identifier (e.g., a unique identifier, an alphanumeric identifier), a tax benefit account identifier, time stamp, geographic area or location, or merchant identifier. In some cases, the communications interface  1710  can perform pre-processing on the data packets and then route or forward the pre-processed data packets to a component or module of the RCRS  1708 . For example, the communications interface  1710  can de-encapsulate or decrypt the data packets and forward them to one or more of the forecast engine, notification engine, or healthcare management platform. In some cases, the communications interface  1710  can store the data of the data packets in database  1718 . The communication interface  1710  may create an event data structure from the data packets and store the event data structure in the database  1718 . The communication interface  1710  may provide a pointer or identifier of the stored event data structure to one or more component or module of the RCRS  1708 . 
     At step  1810 , the server selects a healthcare trend model to provide a healthcare related recommendation. The healthcare trend model can be trained by the server using previously received data packets including data indicating healthcare transaction events corresponding to the plurality of participants of the healthcare management platform. In some aspects, step  1810  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  1810  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  1810  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     The trend model can include a baseline trend for an event. The server can update the trend model as the server receives data packets indicating tax benefit account transaction events. The server can monitor the continuously updated trend model to determine whether the trend of events is exceeding a maximum threshold (e.g., a first threshold) or falling below a minimum threshold (e.g., a second threshold). The server can poll the trend model for an update regarding the current trend relative to the first and second thresholds. The trend model can be configured to provide a binary value responsive to a polling request or query. For example, the trend model can be configured with one or more scripts, API&#39;s, or libraries. The trend model can be configured to compare a current trend value with the first and second threshold and respond to the polling request or query with an indication as to whether the current trend satisfies the desired range by falling within the first and second thresholds, or does not satisfy the desired range by fallout outside the first and second thresholds. If the current trend falls below the threshold or exceeds the threshold, the trend model may further indicate, in the response, that the current trend is below the minimum threshold, or above the maximum threshold. 
     The server can train the trend model by computing a moving average over a time period. The server can determine a moving average of a value associated with the trend, such as a number of denials, rate of denials, amount of denial, number of password changes, or amount of payment deposits. The trend model can include a unique identifier. The unique identifier can include an alpha numeric identifier or one or more of strings, characters, or symbols. Thus, in some cases, training the trend model can include determining a moving average to set a baseline trend. In some cases, training the trend model can further include computing or determining a dynamic first and second threshold (or dynamic maximum and minimum thresholds). The server can determine a dynamic threshold as a function of a baseline trend. For example, the threshold can be a function of a statistical value of the baseline trend, such as a standard deviation, variance, percentage, or logarithm or exponential function. For example, the threshold range can be plus or minus one or more standard deviations from the baseline trend or average. 
     At  1815 , the server performs a lookup to identify tax benefit account related recommendations. In some aspects, step  1815  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  1815  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  1815  is implemented to make or cause more effective and efficient use of computing and networking resources. The server can perform the lookup in a recommendation data structure using an identifier of the selected trend model. The server can perform the lookup to identify one or more tax benefit account related recommendations linked with the selected trend model. 
     In some cases, the server may determine that there are no recommendations linked to the trend model. For example, recommendations may not have been previously transmitted for the event type of the trend model. For situations in which recommendations are not linked to the trend model in the recommendation data structure, the server can select a random one or more recommendations from a pool of available recommendations. In some cases, the server can retrieve a default recommendation. In these cases, the server can be configured to cycle through one or more recommendations to obtain data on how the recommendation might affect the event trend. If the recommendation has no or minimal impact on the event trend (e.g., decreases or increases the event trend by less than 2%, 1%, 0.5%, 0.3%, or some other deminimis amount), then the server can determine that the recommendation has a zero or low correlation coefficient with respect to affecting the event trend. By cycling through different recommendations based on a time interval and monitoring the recommendation&#39;s effect on the event trend, the server can determine a correlation coefficient between the recommendation and the event trend. The server can link the event trend to the recommendation and store the link along with the correlation coefficient in the recommendation data structure for future use. 
     At  1820 , the server determines correlation coefficients for the one or more recommendations. The server can determine the correlation coefficient between each of the plurality of healthcare related recommendations and the selected healthcare trend model. In some cases, the correlation coefficient between a recommendation and an event trend model can be stored in a recommendation data structure. In some aspects, step  1820  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  1820  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  1820  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     In some cases, the server can input the recommendation (or features of the recommendation) and features of the event trend into a machine learning model for the trend that is trained by the server. The output of the machine learning model can include a correlation coefficient that indicates a level of correlation between the recommendation and the event trend or an increase or decrease in the event trend. This correlation coefficient can indicate a likelihood that the recommendation can affect the event trend. 
     For example, providing a notification with a recommendation to change an account password (or other security recommendation) can be correlated with a decrease in fraudulent transaction reported to the RCRS. A decrease in fraudulent transactions reduces resource consumption and processing of the system. 
     At  1825 , the server selects a highest ranking healthcare related recommendation and retrieves a corresponding notification template. In some cases, a recommendation is linked to a notification template that is predetermined to most effectively convey the recommendation. For example, the recommendation data structure can map recommendations to notification templates stored in the notification template data structure. In some cases, the server may determine an additional correlation coefficient between each of a plurality of notification templates and the selected recommendation to identify a highest ranking notification template. In some aspects, step  1825  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  1825  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  1825  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     In some embodiments, the server can be configured to select a notification template for a recommendation using one or more criteria. For example, if recommendation includes text and an image, the server can select a notification template that includes a field for text and an image slot. The server can further select the notification template that includes sufficient space for the recommendation, such as sufficient space for a certain number of characters. In some embodiments, the recommendation can include criteria specifying a communication medium. In some embodiments, the server can determine that a type of communication medium is correlated with a desired event trend adjustment. For example, sending a list of qualifying and non-qualifying items may be more effective in improving an event trend if the list is sent via email as opposed to physical mail or text message. Thus, in some embodiments, the server can select a notification template based on criteria of a recommendation or based on the notification template being correlated with an desired trend adjustment. The server can determine the correlation coefficient between the notification template and event trend adjustment using a machine learning technique. 
     At  1830 , the server generates a notification corresponding to the highest ranking healthcare related recommendation. For example, the server can configure a notification engine with the notification template to cause the notification engine to generate a notification corresponding to the highest ranking healthcare related recommendation. The notification engine can be configured to populate the selected notification template with the recommendation data. The notification engine can be further configured to customize the notification with participant data, temporal data, event type data, or geographic data. In some aspects, step  1830  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  1830  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  1830  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     Configuring the notification engine to generate a notification can include providing the notification template to the notification engine. For example, the notification template can include a data file, a script, or HTML fields. In some embodiments, providing the notification template can include inputting or providing an identifier corresponding to the notification template to the notification engine. For example, the server can generate a function call where the function input includes an identifier for the notification template. The identifier can include an alphanumeric identifier. The identifier can include a path to a data file comprising the notification template. 
     In some embodiments, generating the notification for the recommendation using the notification template can include populating one or more fields of the notification template, calling a scripting function, or assembling one or objects identified by the template or the recommendation. For example, the recommendation can include a data file with instructions that include text or bitmap to be printed or rendered on a display. Example notifications can include a text message to one or more participants that states, for example: “Remember: only use your card for qualifying purchases such as prescription medications and do not conduct a transaction that includes both qualifying and non-qualifying items”; “Check your balance before you swipe by clicking here”; or “Merchant &lt;X&gt; is only configured for credit transactions, so do not use your tax benefit card in debit mode”, where &lt;X&gt; can include a merchant name such as a local pharmacy. The server can determine the local pharmacy based on location information received from the mobile device. For example, the server can receive latitude and longitude information from the participant&#39;s mobile computing device and map this location information to merchant location information by performing a lookup in a merchant location database. 
     At  1835 , the notification engine generates a request to deliver the notification and transmit the notification. In some aspects, step  1835  comprises an innovative, non-conventional or non-routine way to operate or perform the functionality of the present solution. In some aspects, step  1835  is implemented to address the technical problems and challenges of prior systems not deploying the present solution. In some aspects, step  1835  is implemented to make or cause more effective and efficient use of computing and networking resources. 
     The notification engine can generate the request to deliver the notification to a destination address of a computing device of the participant. The destination address can correspond to a phone number, email address, physical address, username, identifier of an application, or other identifier of communication medium of the participant computing device. 
     In some embodiments, the notification engine can store the generated or assembled notification in database. The notification engine can generate a request to deliver the notification. The request can include an identifier, pointer, or file path of the notification stored in the database. The server can, responsive to the generated request, retrieve the stored notification and transmit the notification. The request can include instructions regarding when to transmit the notification, a time interval for repeating transmission of the notification, and to which computing device to transmit the notification. The notification engine can identify participant computing devices to receive the notification using a targeting criteria such as location, type of computing device, or type of event or transaction associated with the computing device. For example, if a set of multiple participant computing devices as associated with the event and the event trend that triggered the generation of the notification, the RCRS can automatically generate a marketing campaign to send the notification with the recommendation to the corresponding participant devices. The server can, in some embodiments, customize the notification for each devices by using different notification templates based on device type (e.g., screen size or communication medium). 
     In some aspects, the methods of the present solutions implements a combination of steps in an innovative, non-conventional and/or non-routine manner. In some aspects, the method  1800  of the present solution combines the steps of  FIG.  18    in an innovative, non-conventional and/or non-routine combination to implement the improved functionality, performance and operation of the present solution. In some aspects, the method of the present solution combines the steps of  FIG.  18    in in an innovative, non-conventional and/or non-routine manner to more efficiently and effectively use computing and networking resources. In some aspects, the method of the present solution provides innovative, non-conventional and/or non-routine ordered combination of steps. 
     It should be understood that the systems described above can provide multiple ones of any or each of those components and these components can be provided on either a standalone machine or, in some embodiments, on multiple machines in a distributed system. The systems and methods described above can be implemented as a method, apparatus or article of manufacture using programming or engineering techniques to produce software, firmware, hardware, or any combination thereof. In addition, the systems and methods described above can be provided as one or more computer-readable programs embodied on or in one or more articles of manufacture. The term “article of manufacture” as used herein is intended to encompass code or logic accessible from and embedded in one or more computer-readable devices, firmware, programmable logic, memory devices (e.g., EEPROMs, ROMs, PROMs, RAMs, SRAMs, etc.), hardware (e.g., integrated circuit chip, Field Programmable Gate Array (FPGA), Application Specific Integrated Circuit (ASIC), etc.), electronic devices, a computer readable non-volatile storage unit (e.g., CD-ROM, floppy disk, hard disk drive, etc.). The article of manufacture can be accessible from a file server providing access to the computer-readable programs via a network transmission line, wireless transmission media, signals propagating through space, radio waves, infrared signals, etc. The article of manufacture can be a flash memory card or a magnetic tape. The article of manufacture includes hardware logic as well as software or programmable code embedded in a computer readable medium that is executed by a processor. In general, the computer-readable programs can be implemented in any programming language, such as LISP, PERL, C, C++, C#, PROLOG, or in any byte code language such as JAVA. The software programs can be stored on or in one or more articles of manufacture as object code. 
     References to “or” may be construed as inclusive so that any terms described using “or” may indicate any of a single, more than one, and all of the described terms. 
     While various embodiments of the methods and systems have been described, these embodiments are exemplary and in no way limit the scope of the described methods or systems. Those having skill in the relevant art can effect changes to form and details of the described methods and systems without departing from the broadest scope of the described methods and systems. Thus, the scope of the methods and systems described herein should not be limited by any of the exemplary embodiments and should be defined in accordance with the accompanying claims and their equivalents.