METHOD AND SYSTEM FOR AUTOMATED EVENT MANAGEMENT

A method for providing an extensible architecture to facilitate automated event management is disclosed. The method includes receiving an indication that relates to an occurrence of a first event, the indication including event data; parsing the event data to generate event messages that correspond to the first event, each of the event messages relating to a structured data set that is accessible within a network environment; applying, by using the at least one event message, a rule and a corresponding trigger to accounts that are associated with the first event; initiating resolution actions for each of the accounts based on the rule and the corresponding trigger; and modifying a resolution indicator that is associated with each of the accounts based on results of the resolution actions.

BACKGROUND

1. Field of the Disclosure

This technology generally relates to methods and systems for managing events, and more particularly to methods and systems for providing an extensible architecture pattern that leverages data ingestion, data processing, and data resolution to facilitate automated event management.

2. Background Information

Many business entities provide services and products that are essential tools for many customers. Often, the usability of these essential tools may be drastically affected by occurrence of various customer life events. Historically, implementations of conventional event management techniques have resulted in varying degrees of success with respect to resource efficient identification and resolution of the events for the customers.

One drawback of the conventional event management techniques is that in many instances, disparate solutions for managing the events are individually implemented across a range of similar services and products. As a result, resources may not be efficiently utilized to identify and resolve events due to duplication of effort. Additionally, because of the disparate solutions, quality of event data across the range of similar services and products may not be consistently ensured.

Therefore, there is a need for an extensible architecture pattern that automatically leverages data ingestion, data processing, as well as data resolution to proactively and systemically manage events across various services and products.

SUMMARY

The present disclosure, through one or more of its various aspects, embodiments, and/or specific features or sub-components, provides, inter alia, various systems, servers, devices, methods, media, programs, and platforms for providing an extensible architecture pattern that leverages data ingestion, data processing, and data resolution to facilitate automated event management.

According to an aspect of the present disclosure, a method for providing an extensible architecture to facilitate automated event management is disclosed. The method is implemented by at least one processor. The method may include receiving at least one indication that relates to an occurrence of a first event, the at least one indication may include event data; parsing the event data to generate at least one event message that corresponds to the first event, each of the at least one event message may relate to a structured data set that is accessible within a network environment; applying, by using the at least one event message, at least one rule and a corresponding trigger to at least one account that is associated with the first event; initiating at least one resolution action for each of the at least one account based on the at least one rule and the corresponding trigger; and modifying at least one resolution indicator that is associated with each of the at least one account based on a result of the at least one resolution action.

In accordance with an exemplary embodiment, the method may further include identifying at least one service that is associated with each of the at least one account; determining at least one requirement for each of the at least one account based on the at least one resolution indicator, each of the at least one requirement may relate to a regulatory obligation; and initiating at least one service resolution action for each of the at least one service based on the corresponding at least one requirement.

In accordance with an exemplary embodiment, to receive the at least one indication, the method may further include generating a graphical user interface to receive event information, the graphical user interface may include at least one graphical element that is configured to receive an input from a user; displaying the graphical user interface via a user device; and receiving the at least one indication via the graphical user interface.

In accordance with an exemplary embodiment, the method may further include determining that additional event information is required based on the at least one indication and a corresponding event type; modifying the graphical user interface to request the additional event information; and displaying the modified graphical user interface via the user device.

In accordance with an exemplary embodiment, the method may further include aggregating raw data from a plurality of sources; parsing, by using at least one model, the raw data to automatically identify a second event; and generating a second indication that relates to the second event, the second indication may include second event data.

In accordance with an exemplary embodiment, the at least one model may include at least one from among a machine learning model, natural language processing model, a statistical model, a mathematical model, a process model, and a data model.

In accordance with an exemplary embodiment, to parse the event data, the method may further include aggregating authoritative information from a plurality of sources; verifying the event data based on a comparison with the corresponding authoritative information; and generating the at least one event message by using the verified event data.

In accordance with an exemplary embodiment, the modifying of the at least one resolution indicator may include at least one from among a first action to add the at least one resolution indicator based on a context of the first event and a second action to remove the at least one resolution indicator based on the context of the first event.

In accordance with an exemplary embodiment, the structured data set may correspond to a predetermined data structure that is universally defined for usage by at least one component of the network environment.

According to an aspect of the present disclosure, a computing device configured to implement an execution of a method for providing an extensible architecture to facilitate automated event management is disclosed. The computing device including a processor; a memory; and a communication interface coupled to each of the processor and the memory, wherein the processor may be configured to receive at least one indication that relates to an occurrence of a first event, the at least one indication may include event data; parse the event data to generate at least one event message that corresponds to the first event, each of the at least one event message may relate to a structured data set that is accessible within a network environment; apply, by using the at least one event message, at least one rule and a corresponding trigger to at least one account that is associated with the first event; initiate at least one resolution action for each of the at least one account based on the at least one rule and the corresponding trigger; and modify at least one resolution indicator that is associated with each of the at least one account based on a result of the at least one resolution action.

In accordance with an exemplary embodiment, the processor may be further configured to identify at least one service that is associated with each of the at least one account; determine at least one requirement for each of the at least one account based on the at least one resolution indicator, each of the at least one requirement may relate to a regulatory obligation; and initiate at least one service resolution action for each of the at least one service based on the corresponding at least one requirement.

In accordance with an exemplary embodiment, to receive the at least one indication, the processor may be further configured to generate a graphical user interface to receive event information, the graphical user interface may include at least one graphical element that is configured to receive an input from a user; display the graphical user interface via a user device; and receive the at least one indication via the graphical user interface.

In accordance with an exemplary embodiment, the processor may be further configured to determine that additional event information is required based on the at least one indication and a corresponding event type; modify the graphical user interface to request the additional event information; and display the modified graphical user interface via the user device.

In accordance with an exemplary embodiment, the processor may be further configured to aggregate raw data from a plurality of sources; parse, by using at least one model, the raw data to automatically identify a second event; and generate a second indication that relates to the second event, the second indication including second event data.

In accordance with an exemplary embodiment, the at least one model may include at least one from among a machine learning model, natural language processing model, a statistical model, a mathematical model, a process model, and a data model.

In accordance with an exemplary embodiment, to parse the event data, the processor may be further configured to aggregate authoritative information from a plurality of sources; verify the event data based on a comparison with the corresponding authoritative information; and generate the at least one event message by using the verified event data.

In accordance with an exemplary embodiment, the modifying of the at least one resolution indicator may include at least one from among a first action to add the at least one resolution indicator based on a context of the first event and a second action to remove the at least one resolution indicator based on the context of the first event.

In accordance with an exemplary embodiment, the structured data set may correspond to a predetermined data structure that is universally defined for usage by at least one component of the network environment.

According to an aspect of the present disclosure, a non-transitory computer readable storage medium storing instructions for providing an extensible architecture to facilitate automated event management is disclosed. The storage medium including executable code which, when executed by a processor, may cause the processor to receive at least one indication that relates to an occurrence of a first event, the at least one indication may include event data; parse the event data to generate at least one event message that corresponds to the first event, each of the at least one event message may relate to a structured data set that is accessible within a network environment; apply, by using the at least one event message, at least one rule and a corresponding trigger to at least one account that is associated with the first event; initiate at least one resolution action for each of the at least one account based on the at least one rule and the corresponding trigger; and modify at least one resolution indicator that is associated with each of the at least one account based on a result of the at least one resolution action.

In accordance with an exemplary embodiment, when executed by the processor, the executable code may further cause the processor to identify at least one service that is associated with each of the at least one account; determine at least one requirement for each of the at least one account based on the at least one resolution indicator, each of the at least one requirement may relate to a regulatory obligation; and initiate at least one service resolution action for each of the at least one service based on the corresponding at least one requirement.

DETAILED DESCRIPTION

As described herein, various embodiments provide optimized methods and systems for providing an extensible architecture pattern that leverages data ingestion, data processing, and data resolution to facilitate automated event management.

Referring toFIG.2, a schematic of an exemplary network environment200for implementing a method for providing an extensible architecture pattern that leverages data ingestion, data processing, and data resolution to facilitate automated event management is illustrated. In an exemplary embodiment, the method is executable on any networked computer platform, such as, for example, a personal computer (PC).

The method for providing an extensible architecture pattern that leverages data ingestion, data processing, and data resolution to facilitate automated event management may be implemented by an Automated Event Management and Analytics (AEMA) device202. The AEMA device202may be the same or similar to the computer system102as described with respect toFIG.1. The AEMA device202may store one or more applications that can include executable instructions that, when executed by the AEMA device202, cause the AEMA device202to perform actions, such as to transmit, receive, or otherwise process network messages, for example, and to perform other actions described and illustrated below with reference to the figures. The application(s) may be implemented as modules or components of other applications. Further, the application(s) can be implemented as operating system extensions, modules, plugins, or the like.

The communication network(s)210may be the same or similar to the network122as described with respect toFIG.1, although the AEMA device202, the server devices204(1)-204(n), and/or the client devices208(1)-208(n) may be coupled together via other topologies. Additionally, the network environment200may include other network devices such as one or more routers and/or switches, for example, which are well known in the art and thus will not be described herein. This technology provides a number of advantages including methods, non-transitory computer readable media, and AEMA devices that efficiently implement a method for providing an extensible architecture pattern that leverages data ingestion, data processing, and data resolution to facilitate automated event management.

The server devices204(1)-204(n) may be hardware or software or may represent a system with multiple servers in a pool, which may include internal or external networks. The server devices204(1)-204(n) hosts the databases206(1)-206(n) that are configured to store data that relates to indications, events, event data, event messages, structured data sets, rules, triggers, resolution actions, resolution indicators, services, requirements, regulatory obligations, and service resolution actions.

One or more of the devices depicted in the network environment200, such as the AEMA device202, the server devices204(1)-204(n), or the client devices208(1)-208(n), for example, may be configured to operate as virtual instances on the same physical machine. In other words, one or more of the AEMA device202, the server devices204(1)-204(n), or the client devices208(1)-208(n) may operate on the same physical device rather than as separate devices communicating through communication network(s)210. Additionally, there may be more or fewer AEMA devices202, server devices204(1)-204(n), or client devices208(1)-208(n) than illustrated inFIG.2.

The AEMA device202is described and shown inFIG.3as including an automated event management and analytics module302, although it may include other rules, policies, modules, databases, or applications, for example. As will be described below, the automated event management and analytics module302is configured to implement a method for providing an extensible architecture pattern that leverages data ingestion, data processing, and data resolution to facilitate automated event management.

An exemplary process300for implementing a mechanism for providing an extensible architecture pattern that leverages data ingestion, data processing, and data resolution to facilitate automated event management by utilizing the network environment ofFIG.2is shown as being executed inFIG.3. Specifically, a first client device208(1) and a second client device208(2) are illustrated as being in communication with AEMA device202. In this regard, the first client device208(1) and the second client device208(2) may be “clients” of the AEMA device202and are described herein as such. Nevertheless, it is to be known and understood that the first client device208(1) and/or the second client device208(2) need not necessarily be “clients” of the AEMA device202, or any entity described in association therewith herein. Any additional or alternative relationship may exist between either or both of the first client device208(1) and the second client device208(2) and the AEMA device202, or no relationship may exist.

Further, AEMA device202is illustrated as being able to access a business event messages repository206(1) and a customer accounts database206(2). The automated event management and analytics module302may be configured to access these databases for implementing a method for providing an extensible architecture pattern that leverages data ingestion, data processing, and data resolution to facilitate automated event management.

Upon being started, the automated event management and analytics module302executes a process for providing an extensible architecture pattern that leverages data ingestion, data processing, and data resolution to facilitate automated event management. An exemplary process for providing an extensible architecture pattern that leverages data ingestion, data processing, and data resolution to facilitate automated event management is generally indicated at flowchart400inFIG.4.

In the process400ofFIG.4, at step S402, indications that relate to an occurrence of an event may be received. The indication may include event data that details the event. In an exemplary embodiment, receiving of the indication may be part of a data ingestion process. The indication may relate to any piece of information that indicates and/or suggests that the event has occurred. For example, the indication may include event information that is received from an affected party.

In another exemplary embodiment, the event may relate to insignificant life events as well as significant life events. The event may include at least one from among a natural disaster event, a fraud event, a financial hardship event, an enlistment in the armed forces event, and an active duty event. The financial hardship event may further include at least one from among a destitute event and a bankruptcy event.

In another exemplary embodiment, to receive the indications, a graphical user interface may be generated to receive event information such as, for example, information that relates to a customer life event. The graphical user interface may relate to a form of user interface that enable interactions between users and electronic devices through various graphical icons and graphical devices. The graphical user interface may include graphical elements such as, for example, the graphical icons that are configured to receive an input from a user. For example, the graphical user interface may be utilized by a user to provide bankruptcy related information such as a confirmed bankruptcy status, an unconfirmed bankruptcy status, an in error bankruptcy status, a filing date, and case details. Similarly, the graphical user interface may be usable by another user to provide deceased related information such as a deceased status, a deceased date, and estate details.

Then, the graphical user interface may be displayed via a user device. The user device may include any computing device that is utilized by the user to interact with the graphical user interface such as, for example, a personal computing device or a mobile computing device. The graphical user interface may be automatically configured for optimized viewing based on the user device. For example, the graphical user interface may be automatically configured for viewing on a mobile device when the mobile device is detected as the user device. Thus, the indications may be received from the user via the graphical user interface.

In another exemplary embodiment, the graphical user interface may be designed to accommodate the receiving of additional information as needed based on the type of customer life event. To facilitate this accommodation, additional event information may be determined to be required based on the received indications and a corresponding event type. The event type may be automatically determined for each of the indications based on information extracted from the indications. For example, information extracted from the indication may provide that the life event relates to a financial-type event such as a bankruptcy.

Then, the graphical user interface may be modified to request the additional event information. The graphical user interface may be modified to update the graphical elements to include instructions for the user to provide the additional event information. For example, when the user indicates that the life event relates to a financial-type event, the graphical elements may be modified to provide instructions requesting additional case information related to final disposition of assets. The modified graphical user interface may be displayed via the user device consistent with present disclosures.

In another exemplary embodiment, to receive the indications, raw data may be aggregated from a plurality of sources. The raw data may correspond to authoritative information that may indicate a life event for various users. The authoritative information may be received from public sources such as, for example, government agencies as well as from private sources such as, for example, third-party data aggregators. For example, the authoritative information may include disaster proclamation data from a government agency for a geographical location.

Then, the raw data may be parsed to automatically identify a life event for affected users. For example, obituary data may be parsed to automatically identify deceased users. A model such as, for example, a machine learning model may be usable to facilitate automated identification of the life event. For example, machine learning and pattern recognition may be usable to identify a life event such as a marriage life event from name change information released by a government agency. The indication that is received by the extensible architecture may be automatically generated based on the identified life event consistent with present disclosures. The indication may include life event data such as, for example, the identified life event, the source information, and model information such as a confidence score.

In another exemplary embodiment, the model may include at least one from among a natural language processing model, a machine learning model, a statistical model, a mathematical model, a process model, and a data model. The model may also include stochastic models such as, for example, a Markov model that is used to model randomly changing systems. In stochastic models, the future states of a system may be assumed to depend only on the current state of the system.

In another exemplary embodiment, machine learning and pattern recognition may include supervised learning algorithms such as, for example, k-medoids analysis, regression analysis, decision tree analysis, random forest analysis, k-nearest neighbors analysis, logistic regression analysis, etc. In another exemplary embodiment, machine learning analytical techniques may include unsupervised learning algorithms such as, for example, Apriori analysis, K-means clustering analysis, etc. In another exemplary embodiment, machine learning analytical techniques may include reinforcement learning algorithms such as, for example, Markov Decision Process analysis, etc.

In another exemplary embodiment, the model may be based on a machine learning algorithm. The machine learning algorithm may include at least one from among a process and a set of rules to be followed by a computer in calculations and other problem-solving operations such as, for example, a linear regression algorithm, a logistic regression algorithm, a decision tree algorithm, and/or a Naive Bayes algorithm.

In another exemplary embodiment, the model may include training models such as, for example, a machine learning model which is generated to be further trained on additional data. Once the training model has been sufficiently trained, the training model may be deployed onto various connected systems to be utilized. In another exemplary embodiment, the training model may be sufficiently trained when model assessment methods such as, for example, a holdout method, a K-fold-cross-validation method, and a bootstrap method determine that at least one of the training model's least squares error rate, true positive rate, true negative rate, false positive rate, and false negative rates are within predetermined ranges.

In another exemplary embodiment, the training model may be operable, i.e., actively utilized by an organization, while continuing to be trained using new data. In another exemplary embodiment, the models may be generated using at least one from among an artificial neural network technique, a decision tree technique, a support vector machines technique, a Bayesian network technique, and a genetic algorithms technique.

In another exemplary embodiment, the natural language processing model may correspond to a plurality of natural language processing techniques. The natural language processing techniques may include at least one from among a sentiment analysis technique, a named entity recognition technique, a summarization technique, a topic modeling technique, a text classification technique, a keyword extraction technique, and a lemmatization and stemming technique. As will be appreciated by a person of ordinary skill in the art, natural language processing may relate to computer processing and analyzing of large quantities of natural language data.

At step S404, the event data may be parsed to generate event messages that correspond to the event. Each of the event messages may relate to a structured data set that is accessible within a network environment. In an exemplary embodiment, the structured data set may correspond to a predetermined data structure that is universally defined for usage by components of the network environment. The predetermined data structure may govern the organization of various data such as, for example, bankruptcy status data and bankruptcy filing data. In another exemplary embodiment, the event messages may include business event messages that are sharable in the network environment. For example, the business event messages may be accessible to all lines of business in an enterprise network environment.

In another exemplary embodiment, parsing of the event data to generate the event messages may be part of a data ingestion process. To facilitate the parsing of the event data, authoritative information may be aggregated from a plurality of sources. The authoritative information may be received from public sources such as, for example, government agencies as well as from private sources such as, for example, third-party data aggregators. For example, the authoritative information may include bankruptcy court information for various participants in bankruptcy proceedings. The authoritative information may include user information that may be trusted as being accurate or true.

Then, the event data may be verified based on a comparison with the corresponding authoritative information. The event data may be verified to confirm the accuracy of the provided information. Consistent with present disclosures, the comparison may be accomplished on an exact match basis and a partial match basis according to a predetermine guideline. Confirmation from an administrator may be required prior to final verification. For example, an administrator may provide final verification approval when a data item such as a name in a bankruptcy filing does not exactly match the corresponding name in the event data. The event message may be generated by using the verified event data.

At step S406, rules and corresponding triggers may be applied to accounts that are associated with the event. The rules and the corresponding triggers may be applied by using the event messages. In an exemplary embodiment, applying of the rules and corresponding triggers may be part of a data processing step. To facilitate the applying of the rules and corresponding triggers, accounts that are associated with the event may first be identified. The accounts may be identified based on an identifier such as, for example, a name and/or an account number of an event participant. The identification may be accomplished by computing components that are subscribed to the business event messages that detail the life events.

Then, rules and corresponding triggers that relate to the life events may be identified. The rules may be predetermined based on the type of life events according to guidelines such as, for example, business guidelines and regulatory guidelines. The corresponding triggers may relate to instructions that causes a necessary action to occur. For example, the rules may indicate that existing debts are forgiven as a result of a bankruptcy and a corresponding trigger may include instructions for actions to clear the existing debts from various ledgers. Consistent with present disclosures, the life event specific business rules may be applied to facilitate the triggering of required account treatment actions.

At step S408, resolution actions for each of the accounts may be initiated based on the associated rules and the corresponding triggers. In an exemplary embodiment, initiation of the resolution actions may be part of a treatment process. The life event specific business rules may be applied to facilitate the triggering of required account treatment actions such as, for example, the resolution actions. The resolution actions may include at least one from among a charge-off action and a write-off action to forgive debt based on the initiated actions.

In another exemplary embodiment, the resolution actions may be automatically initiated based on the associated rules and the corresponding triggers. The resolution actions may be automatically initiated without additional user input. For example, for certain life events, the resolution actions may be configured to automatically initiate. In another exemplary embodiment, the resolution actions may require additional administrative confirmation prior to initiation. The resolution actions may automatically request confirmation from a responsible administrator prior to modification of any accounts. For example, for certain life events, the resolution actions may be configured to automatically request confirmation prior to any ledger write-offs.

At step S410, resolution indicators that are associated with each of the accounts may be modified based on a result of the resolution action. In an exemplary embodiment, modifying resolution indicators may be part of a treatment process. The modifying of the resolution indicators may include at least one from a first action to add the resolution indicators based on a context of the event as well as a second action to remove the resolution indicators based on the context of the event. The resolution indicators may be added or removed from the accounts based on the customer level life event. The resolution indicators may be modified in context with the life event.

In another exemplary embodiment, services that are associated with each of the accounts may be identified. The services may relate to products which are required to comply with conditions that are associated with the accounts. For example, the products may relate to automated payment services for an account that must be stopped based on conditions that are associated with the account. The services may include at least one from among an automated payment service, a collections service, a marketing service, a specialist experience service related to personalizing administrative views across a platform, a customer experience service related to personalizing customer views across a platform, and a credit reporting service.

Then, requirements for each of the accounts may be determined based on the resolution indicator. Each of the requirements may relate to a regulatory obligation that must be satisfied based on a condition of the accounts. For example, a resolution indicator such as a deceased indicator may be usable to provide a condition of the account. The regulatory obligations may be automatically aggregated and maintained to facilitate identification of the requirements. For example, a management system for regulatory obligations may continuously update a repository of requirements when necessary to facilitate identification of the requirements.

Service resolution actions may then be initiated for each of the services based on the corresponding requirement. The service resolution actions may relate to actions that are usable to bring the services into compliance with the requirements. For example, an automated payment service may be required to stop according to a regulatory obligation when the account has a deceased indicator signifying that the account owner is deceased. When the resolution indicators indicate bankruptcy or decease, the service resolution actions may include at least one from among a stop payment action, a stop communications action, a marketing stop action, a labeling of accounts for specialist action, a hiding of accounts for customers action, and a credit bureau reporting action.

FIG.5is a system context diagram500of an exemplary process for implementing a method for providing an extensible architecture pattern that leverages data ingestion, data processing, and data resolution to facilitate automated event management. InFIG.5, an extensible solution is provided to facilitate automated management of customer life events. The architecture pattern may facilitate the automated management in an ingestion stage, a processing stage, and a treatment stage.

As illustrated inFIG.5, a customer may provide event information via a graphical user interface to report a life event. Management systems such as, for example, a deceased management system and a bankruptcy management system may notify a loan management system and mark an eligibility status in an eligibility handling system. The loan management system may determine impacts to a servicing experience system and a customer experience system.

The loan management system may also change account states in an account management system. The account management system may generate account related communications to notify the appropriate management systems. The account management system may also determine effects to impacted systems such as, for example, customer management systems, payment systems, collection systems, analytics and reporting systems, as well as credit reporting systems.

FIG.6is a container diagram600of an exemplary process for implementing a method for providing an extensible architecture pattern that leverages data ingestion, data processing, and data resolution to facilitate automated event management. InFIG.6, an extensible solution is provided to facilitate automated management of customer life events. The architecture pattern may facilitate the automated management in an ingestion stage, a processing stage, and a treatment stage.

As illustrated inFIG.6, a customer may provide event information via a graphical user interface to report a life event. Notification systems such as, for example, centralized bankruptcy notification systems and centralized deceased notification systems may notify a customer management system, a loan management system, and an eligibility handling system. The loan management system may interact with an account management system to facilitate actions such as, for example, charge off actions and/or write-off actions. The eligibility handling system may send communications to the customer regarding an eligibility status.

The account management system may also share accounts tagged with life event to a credit reporting system. The account management system may update account statuses in a customer management system. The account management system may similarly update account statuses and indicators in a payment management system, a servicing experience system, as well as an analytics and reporting system.

FIG.7is a component diagram700of an exemplary process for implementing a method for providing an extensible architecture pattern that leverages data ingestion, data processing, and data resolution to facilitate automated event management. InFIG.7, an extensible solution is provided to facilitate automated management of customer life events. The architecture pattern may facilitate the automated management in an ingestion stage, a processing stage, and a treatment stage.

As illustrated inFIG.7, a customer life event management system may subscribe to a life event handler application for customer life event notifications. The life event handler application may include event subscriber components, customer life event rules components, repository components, and external service integrator components. The repository components may be usable to store life event account details in a database. The event subscriber component may manage subscriptions from the customer life event management system. The external service integrator component may interact with a customer management system to obtain existing accounts of the customer as well as interact with an account management system to update account statuses and indicators.

In another exemplary embodiment, the application may include at least one from among a monolithic application and a microservice application. The monolithic application may describe a single-tiered software application where the user interface and data access code are combined into a single program from a single platform. The monolithic application may be self-contained and independent from other computing applications.

In another exemplary embodiment, a microservice application may include a unique service and a unique process that communicates with other services and processes over a network to fulfill a goal. The microservice application may be independently deployable and organized around business capabilities. In another exemplary embodiment, the microservices may relate to a software development architecture such as, for example, an event-driven architecture made up of event producers and event consumers in a loosely coupled choreography. The event producer may detect or sense an event such as, for example, a significant occurrence or change in state for system hardware or software and represent the event as a message. The event message may then be transmitted to the event consumer via event channels for processing.

In another exemplary embodiment, the event-driven architecture may include a distributed data streaming platform such as, for example, an APACHE KAFKA platform for the publishing, subscribing, storing, and processing of event streams in real time. As will be appreciated by a person of ordinary skill in the art, each microservice in a microservice choreography may perform corresponding actions independently and may not require any external instructions.

In another exemplary embodiment, microservices may relate to a software development architecture such as, for example, a service-oriented architecture which arranges a complex application as a collection of coupled modular services. The modular services may include small, independently versioned, and scalable customer-focused services with specific business goals. The services may communicate with other services over standard protocols with well-defined interfaces. In another exemplary embodiment, the microservices may utilize technology-agnostic communication protocols such as, for example, a Hypertext Transfer Protocol (HTTP) to communicate over a network and may be implemented by using different programming languages, databases, hardware environments, and software environments.

Accordingly, with this technology, an optimized process for providing an extensible architecture pattern that leverages data ingestion, data processing, and data resolution to facilitate automated event management is disclosed.