Patent Publication Number: US-2021166307-A1

Title: Risk assessment communication system

Description:
TECHNICAL FIELD 
     Aspects of this disclosure relate to computer networks, and more specifically, to communicating, over a network, financial information. 
     BACKGROUND 
     Supply chain finance involves business and financing processes that link participants in a supply chain in a manner that enables one or more of such participants to improve working capital efficiency. In some scenarios, a supply chain involves a reseller (sometimes referred to as a “buyer”) that purchases products from a vendor (sometimes referred to as a “product vendor,” “manufacturer,” or “supplier”). The reseller then resells the purchased products to end users. In some cases, the reseller may couple the resale of the products with a service. For instance, if the vendor is a manufacturer of complex computer networking products, the reseller may purchase those products from the vendor and then not only resell those networking products to end users, but also provide services to those end users relating to the installation of the networking products. A lender, bank, or other financial institution can play a role in a supply chain by providing short-term credit to one or more participants in the supply chain. 
     SUMMARY 
     This disclosure describes techniques that include collecting information used in determining the value of assets and/or collateral, and automation or near-automation of certain aspects of processing of requests to advance funds from a line of credit or other financial arrangement. Techniques in accordance with one or more aspects of the present disclosure may enable more accurate assessment of asset and collateral value, and may enable faster and more efficient and processing of financial transactions. As described in one or more examples, techniques described herein may involve receiving, by a computing system and from a computing device controlled by a borrower, a request to advance funds from a line of credit. In some examples, the computing system may access, over a network, financial information maintained by a borrower, including information about accounts receivables and aging information relating to such accounts receivables. Techniques described herein may further involve determining, based on the financial information maintained by the borrower, an updated borrowing base and/or available credit amount for the borrower. 
     In one example, this disclosure describes a method comprising maintaining, by a computing system and for each of a plurality of entities, access credentials; receiving, by the computing system and over a network, an advance request; identifying, by the computing system and based on the advance request, a requesting entity associated with the advance request and an advance amount associated with the advance request, wherein the requesting entity is one of the plurality of entities; accessing, by the computing system and over the network using the access credentials for the requesting entity, financial information maintained by the requesting entity, wherein the financial information includes accounts receivable information associated with the requesting entity and aging information associated with the accounts receivable information; determining, by the computing system and based on the financial information, a borrowing base for the requesting entity; determining, by the computing system and based on the borrowing base and the advance amount, a status for the advance request; and sending, by the computing system and over the network, information about the status for the advance request. 
     In another example, this disclosure describes a system comprising a storage device; and processing circuitry having access to the storage device and configured to: maintain, for each of a plurality of entities, access credentials, receive, over a network, an advance request, identify, based on the advance request, a requesting entity associated with the advance request and an advance amount associated with the advance request, wherein the requesting entity is one of the plurality of entities, access, over the network using the access credentials for the requesting entity, financial information maintained by the requesting entity, wherein the financial information includes accounts receivable information associated with the requesting entity and aging information associated with the accounts receivable information, determine, based on the financial information, a borrowing base for the requesting entity, determine, based on the borrowing base and the advance amount, a status for the advance request, and send, over the network, information about the status for the advance request. 
     In another example, this disclosure describes a computer-readable storage medium comprises instructions that, when executed, configure processing circuitry of a computing system to maintain, for each of a plurality of entities, access credentials; receive, over a network, an advance request; identify, based on the advance request, a requesting entity associated with the advance request and an advance amount associated with the advance request, wherein the requesting entity is one of the plurality of entities; access, over the network using the access credentials for the requesting entity, financial information maintained by the requesting entity, wherein the financial information includes accounts receivable information associated with the requesting entity and aging information associated with the accounts receivable information; determine, based on the financial information, a borrowing base for the requesting entity; determine, based on the borrowing base and the advance amount, a status for the advance request; and send, over the network, information about the status for the advance request. 
     The details of one or more examples of the disclosure are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the disclosure will be apparent from the description and drawings, and from the claims. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a conceptual diagram illustrating an example system within a supply chain finance ecosystem, in accordance with one or more aspects of the present disclosure. 
         FIG. 2  is a block diagram illustrating an example system within a supply chain finance ecosystem, in accordance with one or more aspects of the present disclosure. 
         FIG. 3A ,  FIG. 3B ,  FIG. 3C , and  FIG. 3D  are conceptual diagrams illustrating example user interfaces presented by a user interface device in accordance with one or more aspects of the present disclosure. 
         FIG. 4  is a flow diagram illustrating accounting operations performed by an example computing system lender computing system in accordance with one or more aspects of the present disclosure. 
         FIG. 5  is a flow diagram illustrating operations performed by an example computing system lender computing system in accordance with one or more aspects of the present disclosure. 
     
    
    
     DETAILED DESCRIPTION 
       FIG. 1  is a conceptual diagram illustrating an example system within a supply chain finance ecosystem, in accordance with one or more aspects of the present disclosure. For the purpose of providing background, the illustration in  FIG. 1  includes representations of a number entities, including one or more vendors  111 , one or more resellers  121 , and one or more end users  131 . Also shown in  FIG. 1  are one or more lenders  181  and one or more banks  191 . 
     System  100  of  FIG. 1  also includes one or more reseller computing systems  120 , one or more reseller mobile devices  122 , one or more accounting computing systems  160 , one or more lender computing systems  180 , one or more lender mobile devices  182 , and one or more banking computing systems  190 . Each of such devices are shown interconnected via network  105 . 
     In a supply chain, such as that illustrated in  FIG. 1 , one or more supply chain participants may seek to optimize cash flow and/or working capital. For instance, in the example illustrated in  FIG. 1 , vendor  111  is a manufacturer of products. Reseller  121  purchases products from vendor  111 , and resells those products (e.g., as inventory) to end users  131 . Reseller  121  may couple the sales to end users  131  with services associated with the inventory (e.g., reseller  121  may provide installation, support, and/or distribution functions to end users  131 ). Accordingly, reseller  121  generates revenue through sales of products and/or services to end users  131 . In some cases, reseller  121  purchases its inventory from vendor  111  before it can generate revenue through sales to end users  131 . 
     Reseller  121  may therefore seek to optimize cash flow by contracting with a financing partner, such as lender  181 . For instance, in the example of  FIG. 1 , lender  181  may provide financing (i.e., cash) to reseller  121  in the form of a line of credit secured by assets of reseller  121 . Those assets may include any assets held or owned by reseller  121 , and may include accounts receivables held by reseller  121 . Typically, such accounts receivables may, in some examples, be amounts owed to reseller  121  by one or more end users  131 . In some examples, reseller  121  and lender  181  contractually establish an initial maximum balance on the line of credit, based on collateral pledged by reseller  121 . According to such an arrangement, lender  181  permits reseller  121  to access funds, as needed, through the line of credit. Typically, reseller  121  can access funds from the line of credit at any time, as long as reseller  121  does not exceed the established maximum amount, and as long as reseller  121  meets any other requirements established by lender  181 . By partnering with lender  181  to obtain cash through a line of credit, reseller  121  may, for example, effectively lengthen payment terms to vendors  111  or otherwise optimize cash flow relating to, for example, purchases made from vendor  111  and sales made to end users  131 . 
     In the example of  FIG. 1 , bank  191  is a financial institution or bank at which reseller  121  and lender  181  maintain accounts. For simplicity in the example of  FIG. 1 , both reseller  121  and lender  181  maintain accounts at the same bank  191 , although in other examples, reseller  121  and lender  181  may, of course, maintain accounts at different financial institutions or banks. Also, in the example illustrated in  FIG. 1 , bank  191  is shown as an entity that is separate from lender  181 . In some examples, however, bank  191  and lender  181  may be the same entity, or lender  181  and bank  191  may have a parent-subsidiary relationship or other affiliation. Further, although only one vendor  111  and one reseller  121  are illustrated in  FIG. 1 , lender  181  may provide services to many resellers  121 , and each may have a business relationship with one or more vendors  111 . Accordingly, techniques described herein may be performed not only over a network that connects lender computing system  180  with reseller computing system  120 , but such techniques may also be performed over one or more networks that connect lender computing system  180  with multiple reseller computing systems  120 , multiple accounting computing systems  160 , multiple banking computing systems  190 , and/or multiple other devices. 
     Reseller  121  may draw cash from the line of credit it holds with lender  181  through funds transfers from an account owned by lender  181  at bank  191  to an account owned by reseller  121  at bank  191 . Conversely, reseller  121  may pay down the line of credit by making funds transfers from the account owned by reseller  121  to an account owned by lender  181 . Although reseller  121  and lender  181  may agree on an initial maximum balance on the line of credit, based on collateral pledged by reseller  121 , lender  181  may adjust this maximum balance in response to changes to a borrowing base associated with reseller  121 . In general, the borrowing base is the amount of collateral that reseller  121  uses to secure the value of the line of credit. In some examples, the borrowing base may occasionally, periodically, or continually change, since the collateral pledged by reseller  121  can change as assets held by reseller  121  change. For example, the values of accounts receivables owned by reseller  121  may increase and decrease over time. 
     In the example of  FIG. 1 , and in accordance with one or more aspects of the present disclosure, lender computing system  180  may authenticate a user operating reseller mobile device  122 . For example, reseller mobile device  122  detects input that it determines corresponds to authentication credentials from a user of reseller mobile device  122 . Reseller mobile device  122  outputs a signal over network  105 . Lender computing system  180  detects a signal over network  105 . Lender computing system  180  determines that the signal corresponds to authentication credentials for a user that is authorized to access funds from the line of credit. Lender computing system  180  outputs a signal over network  105 . Reseller mobile device  122  detects a signal and determines that the signal indicates that the user has been authenticated. In some examples, a wide variety of input types may be accepted by reseller mobile device  122  when authenticating a user. For example, reseller mobile device  122  may accept, for the purposes of authentication, input based on facial recognition, fingerprint identification, hand geometry biometrics, retina or iris scan information, voice or signature analysis, passcodes, passwords, information challenges, or any other input type now known or hereafter developed. 
     Lender computing system  180  may respond to a request to advance funds from the line of credit held by reseller  121 . For instance, in the example of  FIG. 1 , reseller mobile device  122  detects input that it determines corresponds to a request to withdraw cash as an advance from the line of credit held by reseller  121  with lender  181 . Reseller mobile device  122  outputs a signal over network  105 . Lender computing system  180  receives a signal that it determines corresponds to a request, from an authorized user associated with reseller  121 , to withdraw $800,000 from a line of credit held by reseller  121  with lender  181 . Lender computing system  180  further determines that the request is from an authorized user associated with reseller  121 , and that reseller  121  holds a $1,000,000 line of credit with lender  181 . Lender computing system  180  further determines that the current balance on that line of credit is $0, and that therefore, the available funds on the line of credit exceeds the requested advance amount. Lender computing system  180  therefore automatically authorizes the withdrawal, and outputs a signal over network  105 . 
     Banking computing system  190 , which is controlled by bank  191 , detects the signal output by lender computing system  180 . Banking computing system  190  determines that the signal corresponds to authorization to transfer $800,000 to an account owned by reseller  121  from an account owned by lender  181 . In the example of  FIG. 1 , banking computing system  190  also performs accounting functions relating to such a funds transfer. For example, banking computing system  190  adjusts accounting records to reflect the new balance of the line of credit held by reseller  121  with lender  181 . Specifically, if the line of credit was previously unused, the balance is adjusted from $0 to $800,000, leaving $200,000 still available. Correspondingly, banking computing system  190  increases, by $800,000, the balance of the account owned by reseller  121  that receives the advanced funds. In the example of  FIG. 1 , reseller  121  may use the funds to purchase inventory from vendor  111 . 
     Lender computing system  180  may provide information to a user of lender mobile device  182  about the funds transfer request initiated by reseller  121 . The user of lender mobile device  182  may be a relationship manager employed by lender  181 . For instance, in the example of  FIG. 1 , and in connection with authorizing the withdrawal, lender computing system  180  outputs a signal over network  105 . Lender mobile device  182  detects a signal over network  105  and determines that the signal corresponds to information about the request to advance funds by reseller  121 . Lender mobile device  182  generates data associated with a user interface and presents one or more user interfaces  183  at a display screen associated with lender mobile device  182 . In some examples, one or more of user interfaces  183  presents information indicating that funds were transferred from the line of credit held by reseller  121  with lender  181 . 
     Lender computing system  180  may confirm to a user of reseller mobile device  122  that funds were transferred. The user of reseller mobile device  122  may be an employee of reseller  121 . For instance, in the example of  FIG. 1 , and also in connection with authorizing the withdrawal, lender computing system  180  outputs a signal over network  105 . Reseller mobile device  122  detects a signal over network  105  and determines that the signal corresponds to information about the request to advance funds by reseller  121 . Reseller mobile device  122  generates data associated with a user interface and presents one or more user interfaces  123  at a display screen associated with reseller mobile device  122 , thereby informing a user of reseller mobile device  122  that funds were transferred from the line of credit held by reseller  121  with lender  181  to a cash account owned by reseller  121 . 
     Reseller  121  may, during the normal course of business operations, maintain accounting records. In some examples, such accounting records may include records of accounts receivables, accounts payables, information about banking activity and credits and debits posted to bank and credit accounts. In the example of  FIG. 1 , reseller computing system  120  maintains accounting records for reseller  121  relating to business operations performed by reseller  121 . For instance, in some examples, reseller computing system  120  detects input that it determines corresponds to information about business operations. Reseller computing system  120  determines, based on the information about business operations, accounting information. Reseller computing system  120  logs the accounting information in accounting records stored at reseller computing system  120  and/or updates accounting records stored at reseller computing system  120 . Alternatively, or in addition, reseller computing system  120  outputs, in response to the detected input, a signal over network  105 . Accounting computing system  160  detects a signal that it determines corresponds to accounting information associated with reseller  121 . Accounting computing system  160  logs the accounting information in accounting records stored at accounting computing system  160  and/or updates accounting records stored at accounting computing system  160 . 
     In some examples, accounting computing system  160  may act as a mirror of the accounting records maintained at reseller computing system  120 . In other examples, accounting computing system  160  may act as a primary store of some or all accounting records maintained by reseller  121 . In such an example, reseller  121  might not use reseller computing system  120  to maintain accounting records, but may instead use accounting computing system  160  or another remotely located system. 
     Also, in the example illustrated in  FIG. 1 , accounting computing system  160  is shown as implemented separately from lender computing system  180 . In other examples, however, accounting computing system  160  may be combined with lender computing system  180  or with one or more other systems illustrated in  FIG. 1 . Further, accounting computing system  160  may, in some examples, be operated or controlled by one or more of reseller  121 , lender  181 , and/or bank  191 . 
     Lender computing system  180  may respond to a request to advance further funds from the line of credit held by reseller  121 . For instance, in the example of  FIG. 1 , reseller mobile device  122  detects input that it determines corresponds to a request to advance additional cash from the line of credit reseller  121  holds with lender  181 . Reseller mobile device  122  outputs a signal over network  105 . Lender computing system  180  detects a signal over network  105  that it determines corresponds to a request, from an authorized user associated with reseller  121 , to withdraw an additional $300,000 from the $1,000,000 line of credit held by reseller  121  with lender  181 . Lender computing system  180  determines that the current balance on the line of credit is $800,000, and that the remaining available line of credit is $200,000. Lender computing system  180  therefore does not, in this example, automatically authorize the withdrawal, since the advance request exceeds the available cash by $100,000. 
     Lender computing system  180  may analyze financial records maintained by reseller  121  at accounting computing system  160  to determine whether collateral pledged by reseller  121  is nevertheless sufficient to enable the advance request to be granted. For instance, continuing with the example of  FIG. 1 , lender computing system  180  outputs a signal over network  105 . Accounting computing system  160  detects a signal and determines that the signal corresponds to a request for financial information sufficient to calculate a borrowing base for reseller  121 . Accounting computing system  160  further determines that the signal originates from lender computing system  180 , which accounting computing system  160  determines is authorized to access financial records associated with reseller  121  and maintained by reseller  121  at accounting computing system  160 . Accounting computing system  160  outputs information over network  105 . Lender computing system  180  detects a signal over network  105  and determines that the signal includes financial information associated with reseller  121 . Lender computing system  180  further determines that the financial information is sufficient to calculate a borrowing base. 
     Lender computing system  180  calculates, based on the financial information, an updated borrowing base for reseller  121 . In some examples, lender computing system  180  may determine that the value of the collateral pledged by reseller  121  has been increased because the value of the pledged assets have increased. For example, lender computing system  180  may determine that additional accounts receivables held by reseller  121  have been logged in accounting computing system  160 . Lender computing system  180  may also decrease the value of the collateral pledged based on other information logged in accounting computing system  160 , such as information about debts owed by reseller  121 , or about accounts receivables no longer held by reseller  121 . Accordingly, as a result of such adjustments, the borrowing base may increase or decrease relative to a previously-calculated borrowing base. 
     In the example of  FIG. 1 , lender computing system  180  determines that the updated borrowing base for reseller  121  is $1,150,000. Lender computing system  180  further determines that based on the updated borrowing base, the request to withdraw $300,000 will not exceed the current borrowing base associated with reseller  121 , since it will result in a line of credit balance of only $1,100,000. Accordingly, in such an example, lender computing system  180  outputs a signal over network  105 . Lender mobile device  182  detects a signal over network  105  and determines that the signal corresponds to information about the request to withdraw $300,000. Lender mobile device  182  generates data associated with a user interface and presents one or more user interfaces  183  at a display device associated with lender mobile device  182 . In some examples, one or more of user interfaces  183  include information about the request and the updated borrowing base calculation. One or more of user interfaces  183  may request approval to grant the request to advance funds. Lender mobile device  182  detects input that it determines corresponds to an approval to advance funds. Lender mobile device  182  outputs a signal over network  105 . Lender computing system  180  detects a signal over network  105  that it determines corresponds to an approval of the request to advance $300,000. In response, lender computing system  180  authorizes and/or enables the withdrawal, and outputs a signal over network  105 . Banking computing system  190  detects a signal that it determines corresponds to authorization to transfer $300,000 to an account owned by reseller  121  from an account owned by lender  181 . Banking computing system  190  causes the funds to be transferred from the line of credit maintained by reseller  121 , and performs accounting functions relating to the funds transfer, including adjusting the balance on the line of credit that reseller  121  maintains with lender  181  to $1,100,000, leaving $50,000 still available. 
     Lender computing system  180  may confirm to a user of reseller mobile device  122  that funds were transferred. For instance, in the example of  FIG. 1 , lender computing system  180  outputs a signal over network  105 . Reseller mobile device  122  detects a signal over network  105  and determines that the signal corresponds to information about the latest request to advance funds. Reseller mobile device  122  generates data associated with a user interface and presents one or more user interfaces  123  at a display screen associated with reseller mobile device  122 . In some examples, one or more user interfaces present information confirming that funds were transferred from the line of credit held by reseller  121  with lender  181 . Further, in some examples, lender computing system  180  may send one or more other notifications to reseller mobile device  122  in connection with the request to advance funds. For instance, lender computing system  180  may send an earlier notification to reseller mobile device  122  confirming the advance request was received. Alternatively, or in addition, lender computing system  180  may send a notification when the advance request was authorized or approved by lender  181 . 
     In examples just described, some advance requests might be granted automatically, some might be granted after lender computing system  180  determines a new borrowing base, and/or some might be granted after approval by an agent of the lender. Alternate practices could also be followed. For instance, in some examples, lender computing system  180  might determine an updated borrowing base each time lender computing system  180  receives an advance request. In other examples, lender computing system  180  might determine an updated borrowing base each time financial records stored at accounting computing system  160  (or elsewhere) are updated. In still further examples, lender computing system  180  might determine a borrowing base occasionally, periodically, pursuant to a schedule, or continually. Lender computing system  180  might also determine a borrowing base based on the advance request itself or other circumstances. For instance, if granting the advance request will result in a line of credit balance that exceeds a certain dollar amount, or a certain percentage of the size of the line of credit, lender computing system  180  might determine an updated borrowing base in such examples. 
     Further, in some examples, lender computing system  180  might automatically determine whether to grant some or all advance requests based on an updated borrowing base for the requesting entity, without requiring confirmation from an agent of reseller  121 . In other examples, lender computing system  180  might request confirmation from an agent of reseller  121  before authorizing some or all advance requests. In still further examples, lender computing system  180  might request confirmation only for those advance requests that will result in a line of credit balance that exceeds a certain dollar amount, or a certain percentage of the size of the line of credit. 
       FIG. 1  illustrates one example implementation of system  100 . Other example or alternate implementations of system  100  may be appropriate in other instances. Such implementations may include a subset of the devices and/or components included in the example of  FIG. 1  and/or may include additional devices and/or components not shown in  FIG. 1 . 
     Accordingly, although one or more implementations of system  100  have been described with reference to  FIG. 1 , system  100  may be implemented in a number of different ways. For instance, one or more devices of system  100  that may be illustrated as separate devices may alternatively be implemented as a single device; one or more components of system  100  that may be illustrated as separate components may alternatively be implemented as a single component. Also, in some examples, one or more devices of system  100  that may be illustrated as a single device may alternatively be implemented as multiple devices; one or more components of system  100  that may be illustrated as a single component may alternatively be implemented as multiple components. Each of the multiple devices and/or components may be directly coupled via wired or wireless communication and/or remotely coupled via one or more networks. Also, one or more devices or components that may be illustrated in  FIG. 1  may alternatively be implemented as part of another device or component not shown in  FIG. 1 . 
     Further, certain operations, techniques, features, and/or functions may have been described herein as being performed by specific components, devices, and/or modules in  FIG. 1 . In other examples, such operations, techniques, features, and/or functions may be performed by different components, devices, or modules. Accordingly, some operations, techniques, features, and/or functions that may have been described herein as being attributed to one or more components, devices, or modules in  FIG. 1  may, in other examples, be attributed to other components, devices, and/or modules, even if not specifically described herein in such a manner. 
     In accordance with one or more aspects of this disclosure, one or more lender computing systems  180  may analyze information associated with one or more resellers  121 , such as information stored at accounting computing system  160 . It may be appropriate for one or more lender computing systems  180  to analyze such information only after receiving permission from the owner or user associated with such information. For example, in some examples described herein, before lender computing system  180  can collect or make use of information associated with reseller  121 , reseller  121  may be provided with an opportunity to control whether lender computing system  180  can collect or make use of information about the user (e.g., banking transactions, financial information, or other information), or to dictate whether and/or how lender computing system  180  can use such information. 
     Through techniques in accordance with one or more aspects of the present disclosure, such as calculating borrowing base information based on reseller financial information maintained by the reseller, lender computing system  180  may avoid having to perform periodic calculations based on data entered by a user. By not having to perform periodic calculations based on data entered by a user, lender computing system  180  may require less user input, and may generate more accurate and timely borrowing base determinations. Further, by not having to perform periodic calculations based on data entered by a user, lender computing system  180  and/or other systems may spend less computing cycles processing user input or correcting user input, and thereby consume less electrical power. Therefore, aspects of this disclosure may improve the function of at least some computing systems because calculating borrowing base information based on reseller financial information maintained by the reseller may have the effect of causing lender computing system  180  or other systems to consume less electrical power. 
     Further, through techniques in accordance with one or more aspects of the present disclosure, such as calculating borrowing base information based on reseller financial information maintained by the reseller, lender computing system  180  may operate on more accurate underlying data. By operating on more accurate underlying data, lender computing system  180  may make more accurate collateral assessments and more accurate borrowing base determinations. Therefore, aspects of this disclosure may improve the function of lender computing system  180  because calculating borrowing base information based on reseller financial information maintained by the reseller may have the effect of causing lender computing system  180  to make more accurate collateral assessments and more accurate borrowing base determinations. 
     Further, through techniques in accordance with one or more aspects of the present disclosure, such as calculating borrowing base information based on reseller financial information maintained by the reseller, lender computing system  180  may enable cash advance requests to be approved more quickly. By enabling advance requests to be approved more quickly, various aspects of system  100  may operate more efficiently because quick decisions on advance requests reduce or eliminate reseller and business uncertainty that accompanies delays in processing advance requests. Therefore, aspects of this disclosure may improve the function of at least some aspects of system  100  because calculating borrowing base information based on reseller financial information maintained by the reseller may have the effect of causing system  100  to operate more efficiently. 
       FIG. 2  is a block diagram illustrating an example system within a supply chain finance ecosystem, in accordance with one or more aspects of the present disclosure. System  200  of  FIG. 2  may be described as an example or alternate implementation of system  100  of  FIG. 1 . One or more aspects of  FIG. 2  may be described herein within the context of  FIG. 1 . 
     In the example of  FIG. 2 , system  200  includes one or more reseller computing systems  120 , one or more reseller mobile devices  122 , one or more accounting systems  260 , one or more lender computing systems  280 , one or more lender mobile devices  182 , and one or more banking computing systems  190 . Each of such devices are shown connected via network  105 . 
     Systems, devices, or components illustrated in  FIG. 2  may correspond to like-numbered systems, devices, or components illustrated in  FIG. 1 , and may be implemented in a manner consistent with the description provided in connection with  FIG. 1 . Also, lender computing system  280  of  FIG. 2  may correspond to lender computing system  180  of  FIG. 1 , and accounting system  260  of  FIG. 2  may correspond to accounting computing system  160  of  FIG. 1 . These systems may be implemented in a manner consistent with the description of the corresponding system provided in connection with  FIG. 1 , although in some examples such systems may involve alternate implementations with more, fewer, and/or different capabilities. For ease of illustration, and in at least some cases, one system of a given type is illustrated in  FIG. 2  (e.g., only one lender computing system  280  and only one accounting system  260  is illustrated in  FIG. 2 ), although techniques in accordance with one or more aspects of this disclosure may be performed with many more of such systems. 
     Network  105  may be the internet, or may include or represent any public or private communications network or other network. For instance, network  105  may be a cellular, Wi-Fi®, ZigBee, Bluetooth, Near-Field Communication (NFC), satellite, enterprise, service provider, and/or other type of network enabling transfer of transmitting data between computing systems, servers, and computing devices. One or more of client devices, server devices, or other devices may transmit and receive data, commands, control signals, and/or other information across network  105  using any suitable communication techniques. Network  105  may include one or more network hubs, network switches, network routers, satellite dishes, or any other network equipment. Such devices or components may be operatively inter-coupled, thereby providing for the exchange of information between computers, devices, or other components (e.g., between one or more client devices or systems and one or more server devices or systems). Each of the devices or systems illustrated in  FIG. 2  may be operatively coupled to network  105  using one or more network links. The links coupling such devices or systems to network  105  may be Ethernet, Asynchronous Transfer Mode (ATM) or other types of network connections, and such connections may be wireless and/or wired connections. One or more of the devices or systems illustrated in  FIG. 2  or otherwise on network  105  may be in a remote location relative to one or more other illustrated devices or systems. 
     Lender computing system  280  may be implemented as any suitable computing system, such as one or more server computers, workstations, mainframes, appliances, cloud computing systems, virtual machines, containers, and/or other computing systems that may be capable of performing operations and/or functions described in accordance with one or more aspects of the present disclosure. In some examples, lender computing system  280  represents a cloud computing system, server farm, and/or server cluster (or portion thereof) that provides services to client devices and other devices or systems. In other examples, lender computing system  280  may represent or be implemented through one or more virtualized compute instances (e.g., virtual machines, containers) of a data center, cloud computing system, server farm, and/or server cluster. 
     In the example of  FIG. 2 , lender computing system  280  may include power source  281 , one or more processors  283 , one or more input devices  286 , one or more output devices  287 , and one or more storage devices  290 . Storage devices  290  may include authentication module  293 , notification module  294 , analysis module  296 , and data store  297 . One or more of the devices, modules, storage areas, or other components of lender computing system  280  may be interconnected to enable inter-component communications (physically, communicatively, and/or operatively). In some examples, such connectivity may be provided by through communication channels (e.g., communication channels  282 ), a system bus, a network connection, an inter-process communication data structure, or any other method for communicating data. 
     Power source  281  may provide power to one or more components of lender computing system  280 . Power source  281  may receive power from the primary alternating current (AC) power supply in a building, home, or other location. In other examples, power source  281  may be a battery or a device that supplies direct current (DC). In still further examples, lender computing system  280  and/or power source  281  may receive power from another source. One or more of the devices or components illustrated within lender computing system  280  may be connected to power source  281 , and/or may receive power from power source  281 . Power source  281  may have intelligent power management or consumption capabilities, and such features may be controlled, accessed, or adjusted by one or more modules of lender computing system  280  and/or by one or more processors  283  to intelligently consume, allocate, supply, or otherwise manage power. 
     One or more processors  283  of lender computing system  280  may implement functionality and/or execute instructions associated with lender computing system  280  or associated with one or more modules illustrated herein and/or described below. One or more processors  283  may be, may be part of, and/or may include processing circuitry that performs operations in accordance with one or more aspects of the present disclosure. Examples of processors  283  include microprocessors, application processors, display controllers, auxiliary processors, one or more sensor hubs, and any other hardware configured to function as a processor, a processing unit, or a processing device. Lender computing system  280  may use one or more processors  283  to perform operations in accordance with one or more aspects of the present disclosure using software, hardware, firmware, or a mixture of hardware, software, and firmware residing in and/or executing at lender computing system  280 . 
     One or more communication units  285  of lender computing system  280  may communicate with devices external to lender computing system  280  by transmitting and/or receiving data, and may operate, in some respects, as both an input device and an output device. In some examples, communication unit  285  may communicate with other devices over a network. In other examples, communication units  285  may send and/or receive radio signals on a radio network such as a cellular radio network. In other examples, communication units  285  of lender computing system  280  may transmit and/or receive satellite signals on a satellite network such as a Global Positioning System (GPS) network. Examples of communication units  285  include a network interface card (e.g. such as an Ethernet card), an optical transceiver, a radio frequency transceiver, a GPS receiver, or any other type of device that can send and/or receive information. Other examples of communication units  285  may include devices capable of communicating over Bluetooth®, GPS, NFC, ZigBee, and cellular networks (e.g., 3G, 4G, 5G), and Wi-Fi® radios found in mobile devices as well as Universal Serial Bus (USB) controllers and the like. Such communications may adhere to, implement, or abide by appropriate protocols, including Transmission Control Protocol/Internet Protocol (TCP/IP), Ethernet, Bluetooth, NFC, or other technologies or protocols. 
     One or more input devices  286  may represent any input devices of lender computing system  280  not otherwise separately described herein. One or more input devices  286  may generate, receive, and/or process input from any type of device capable of detecting input from a human or machine. For example, one or more input devices  286  may generate, receive, and/or process input in the form of electrical, physical, audio, image, and/or visual input (e.g., peripheral device, keyboard, microphone, camera). 
     One or more output devices  287  may represent any output devices of lender computing system  280  not otherwise separately described herein. One or more output devices  287  may generate, receive, and/or process input from any type of device capable of detecting input from a human or machine. For example, one or more output devices  287  may generate, receive, and/or process output in the form of electrical and/or physical output (peripheral device, actuator). Some devices may serve as both input and output devices. For example, a communication device may both send and receive data to and from other systems or devices over a network. 
     One or more storage devices  290  within lender computing system  280  may store information for processing during operation of lender computing system  280 . Storage devices  290  may store program instructions and/or data associated with one or more of the modules described in accordance with one or more aspects of this disclosure. One or more processors  283  and one or more storage devices  290  may provide an operating environment or platform for such modules, which may be implemented as software, but may in some examples include any combination of hardware, firmware, and software. One or more processors  283  may execute instructions and one or more storage devices  290  may store instructions and/or data of one or more modules. The combination of processors  283  and storage devices  290  may retrieve, store, and/or execute the instructions and/or data of one or more applications, modules, or software. Processors  283  and/or storage devices  290  may also be operably coupled to one or more other software and/or hardware components, including, but not limited to, one or more of the components of lender computing system  280  and/or one or more devices or systems illustrated as being connected to lender computing system  280 . 
     In some examples, one or more storage devices  290  are temporary memories, meaning that a primary purpose of the one or more storage devices is not long-term storage. Storage devices  290  of lender computing system  280  may be configured for short-term storage of information as volatile memory and therefore not retain stored contents if deactivated. Examples of volatile memories include random access memories (RAM), dynamic random access memories (DRAM), static random access memories (SRAM), and other forms of volatile memories known in the art. Storage devices  290 , in some examples, also include one or more computer-readable storage media. Storage devices  290  may be configured to store larger amounts of information than volatile memory. Storage devices  290  may further be configured for long-term storage of information as non-volatile memory space and retain information after activate/off cycles. Examples of non-volatile memories include magnetic hard disks, optical discs, floppy disks, Flash memories, or forms of electrically programmable memories (EPROM) or electrically erasable and programmable (EEPROM) memories. 
     Authentication module  293  may perform functions relating to authenticating a user of a client computing device, often one that is operated by a user associated with reseller  121 . Authentication module  293  may perform analyze authentication credentials received by communication unit  285  over network  105 , and compare the authentication credentials to a list or hashed list of credentials associated with authorized users. In doing so, authentication module  293  may access data store  297 . Although authentication module  293  may be described in connection with  FIG. 2  as primarily performing authentication services, authentication module  293  may alternatively, or in addition, operations relating to identifying users and/or entities associated with users. 
     Notification module  294  may perform functions relating to communicating with computing devices to provide information about the status of a request to advance funds, to prompt a relationship manager associated with lender  181  to approve or otherwise act on a request to advance funds, to provide information about cross-selling or upselling opportunities (e.g., to a relationship manager associated with reseller  121 ), or to provide other information. Notification module  294  may receive information from one or more other modules, including analysis module  296 . Although notification module  294  may be described in connection with  FIG. 2  as primarily providing information to mobile devices, notification module  294  may alternatively, or in addition, provide information to other computing devices or systems. 
     Analysis module  296  may perform functions relating to performing borrowing base calculations and/or identifying potential cross-selling and/or upselling opportunities. Analysis module  296  may request, from accounting system  260 , financial information that can be used to determine a borrowing base for one or more resellers  121 . Analysis module  296  may analyze financial information received from accounting system  260  and determine a value of the collateral pledged by one or more resellers  121  by evaluating, for example, accounts receivables information and aging information relating to the accounts receivables information. Analysis module  296  may also access other information sources, which may include information stored locally or remotely relative to lender computing system  280 . Analysis module  296  may analyze financial information received from accounting system  260  and identify, based on banking records or other records, cross-selling and upselling information relating to one or more resellers  121 . Analysis module  296  may output information to, or receive information from, one or more other modules (e.g., notification module  294 ). 
     Data store  297  may represent any suitable data structure or storage medium for storing information relating to records of financial transactions associated with one or more resellers  121  and/or other entities, and information relating to cross-selling and/or upselling opportunities or potential opportunities involving one or more resellers  121  and/or other entities. Data store  297  may further include access credentials for one or more of multiple resellers  121 . Such access credentials may enable lender computing system  280  to access, at accounting system  260 , financial information about each of resellers  121 . The information stored in data store  297  may be searchable and/or categorized such that one or more modules within lender computing system  280  may provide an input requesting information from data store  297 , and in response to the input, receive information stored within data store  297 . Data store  297  may be primarily maintained by analysis module  296 . Data store  297  may store financial information for one or more resellers  121 . Such financial information may include information retrieved from accounting system  260  over network  105 . Data store  297  may provide other modules with access to the data stored within data store  297 , and/or may analyze the data stored within data store  297  and output such information on behalf of other modules of lender computing system  280 . 
     Accounting system  260  may be implemented as any suitable computing system, such as one or more server computers, workstations, mainframes, appliances, cloud computing systems, and/or other computing systems that may be capable of performing operations and/or functions described in accordance with one or more aspects of the present disclosure. In some examples, accounting system  260  represents a cloud computing system, server farm, and/or server cluster (or portion thereof) that provides services to client devices and other devices or systems. In other examples, accounting system  260  may represent or be implemented through one or more virtualized compute instances (e.g., virtual machines, containers) of a data center, cloud computing system, server farm, and/or server cluster. In some examples, accounting system  260  may be implemented as a cloud-based accounting and/or recordkeeping system, such as QuickBooks Online, which is a service provided by Intuit Inc., of Mountain View, Calif. 
     In the example of  FIG. 2 , accounting system  260  may include power source  261 , one or more processors  263 , one or more communication units  265 , one or more input devices  266 , one or more output devices  267 , and one or more storage devices  270 . Storage devices  270  may include accounting module  276  and data store  277 . One or more of the devices, modules, storage areas, or other components of accounting system  260  may be interconnected to enable inter-component communications (physically, communicatively, and/or operatively). In some examples, such connectivity may be provided by through communication channels (e.g., power sources  261 ), a system bus, a network connection, an inter-process communication data structure, or any other method for communicating data. 
     Power source  261  may provide power to one or more components of accounting system  260 . One or more processors  263  of accounting system  260  may implement functionality and/or execute instructions associated with accounting system  260  or associated with one or more modules illustrated herein and/or described below. One or more communication units  265  of accounting system  260  may communicate with devices external to accounting system  260  by transmitting and/or receiving data over a network or otherwise. One or more input devices  266  may represent any input devices of accounting system  260 . One or more output devices  267  may represent any output devices of accounting system  260 . One or more storage devices  270  within computing system  260  may store program instructions and/or data associated with one or more of the modules of storage devices  270 , in accordance with one or more aspects of this disclosure. One or more processors  263  and one or more storage devices  270  may provide an operating environment or platform for such modules. Power source  261 , processors  263 , communication units  265 , input devices  266 , output devices  267 , and/or storage devices  270  may be implemented in a manner similar to or consistent with like-named components described herein, such as those described connection with lender computing system  280 . 
     Accounting module  276  may perform functions relating to maintaining accounting records for one or more resellers  121 . Accounting module  276  may receive, over network  105 , information about business operations or transactions from one or more resellers  121 . Accounting module  276  may analyze such information and determine appropriate accounting entries to be made to accounting records maintained by accounting module  276  for one or more resellers  121 . Accounting module  276  may log, in data store  277 , information about business operations performed by one or more resellers  121  or other entities. Accounting module  276  may periodically, occasionally, or continually access, over network  105 , information about banking activity associated with bank accounts owned or controlled by one or more resellers  121 . Accounting module  276  may determine whether a computing system (e.g., lender computing system  280 ) is authorized to access financial records associated with reseller  121  and maintained by reseller  121  at accounting system  260 . Although accounting module  276  may be described in connection with  FIG. 2  as primarily performing accounting operations, accounting module  276  may alternatively, or in addition, perform operations including analysis of data received from one or more resellers  121  or other entities. 
     Data store  277  may represent any suitable data structure or storage medium for storing accounting records and/or other financial information for one or more resellers  121 . The information stored in data store  277  may be searchable and/or categorized such that one or more modules within accounting system  260  may provide an input requesting information from data store  277 , and in response to the input, receive information stored within data store  277 . Data store  277  may be primarily maintained by accounting module  276 . Data store  277  may provide other modules with access to the data stored within data store  277 , and/or may analyze the data stored within data store  277  and output such information on behalf of other modules of accounting system  260 . 
     In the example of  FIG. 2 , and in accordance with one or more aspects of the present disclosure, reseller  121  may, during the normal course of business operations, maintain accounting records at accounting system  260 . For instance, in the example of  FIG. 2 , reseller computing system  120  detects input that it determines corresponds to information about a newly acquired claim for payment that reseller  121  holds against one or more end users  131 . In response to such input, reseller computing system  120  outputs a signal over network  105 . Communication unit  265  of accounting system  260  detects a signal over network  105 . Communication unit  265  outputs to accounting module  276  information about the signal. Accounting module  276  determines that the signal corresponds to information about the claim for payment that reseller  121  holds against one or more end users  131 . Accounting module  276  outputs to data store  277  information about the claim. Data store  277  stores and/or logs information about the claim as an accounts receivable asset associated with reseller  121 . 
     Reseller  121  may, during business operations, update the accounting records at accounting system  260 . For instance, in the example of  FIG. 2 , reseller computing system  120  detects input that it determines corresponds to information about a payment received for an accounts receivable. In response to the input, reseller computing system  120  outputs a signal over network  105 . Communication unit  265  detects a signal over network  105  and outputs to accounting module  276  information about the signal. Accounting module  276  determines that the signal corresponds to information about payment received by reseller  121  (or by a bank account owned by reseller  121 ) that corresponds to an accounts receivable accounting entry. Accounting module  276  outputs to data store  277  information about the payment. Data store  277  stores and/or logs information about the payment. 
     Other accounting records associated with reseller  121  may be maintained and/or updated at accounting system  260 . For instance, in the example of  FIG. 2 , reseller computing system  120  detects input that it determines corresponds to information about a claim for payment that a third party holds against reseller  121 . In response to the input, reseller computing system  120  outputs a signal over network  105 . Communication unit  265  of accounting system  260  detects a signal over network  105  and outputs to accounting module  276  information about the signal. Accounting module  276  determines that the signal corresponds to information about an accounts payable associated with reseller  121 . Accounting module  276  outputs information to data store  277 , and data store  277  stores and/or logs information about the accounts payable. 
     In another example, reseller computing system  120  may communicate to accounting system  260 , over network  105 , information about banking activity associated with one or more bank accounts owned by reseller  121 . Banking activity may include types of charges incurred, checks written, names of creditors, names of debtors, amounts paid or received. In such an example, accounting module  276  of accounting system  260  may store and/or log such information within data store  277 . Alternatively, or in addition, accounting module  276  of accounting system  260  may periodically, occasionally, or continually access, over network  105 , information about banking activity associated with one or more bank accounts owned by reseller  121 . For instance, accounting module  276  of accounting system  260  may access banking computing system  190  over network  105 . Accounting module  276  may store and/or log information about banking activity in data store  277 . 
     Accounting system  260  may be implemented in a variety of ways. For instance, in some examples, accounting system  260  may serve as a primary accounting system for reseller  121 . In other examples, accounting system  260  may act as a full or partial mirror of another accounting system used by reseller  121 . In still other examples, accounting system  260  may serve as an accounting system for only certain aspects of the business operated by reseller  121 . In still other examples, accounting system  260  may be integrated into one or more systems or components of  FIG. 2 , such as banking computing system  190  or lender computing system  280 . 
     Lender computing system  280  may authenticate a user that is authorized to access funds, on behalf of reseller  121 , from the line of credit held by reseller  121  with lender  181 . For instance, in the example of  FIG. 2 , reseller mobile device  122  detects input that it determines corresponds to authentication credentials from a user of reseller mobile device  122 . Reseller mobile device  122  outputs a signal over network  105 . Communication unit  285  of lender computing system  280  detects a signal over network  105  and outputs information about the signal to authentication module  293 . Authentication module  293  determines that the signal corresponds to authentication credentials for a user that is authorized to access funds from the line of credit held by reseller  121  with lender  181 . Authentication module  293  compares the credentials to credentials or hashed credentials stored within data store  297 . Authentication module  293  causes communication unit  285  to output a signal over network  105 . Reseller mobile device  122  detects a signal and determines that the signal indicates that the user has been authenticated. 
     Lender computing system  280  may collect information to calculate a borrowing base for reseller  121 . For instance, in the example of  FIG. 2 , communication unit  285  of lender computing system  280  detects a signal over network  105 . Communication unit  285  outputs an indication of the signal to analysis module  296 . Analysis module  296  determines that the signal corresponds to a request, from an authorized user associated with reseller  121 , to advance funds from a line of credit held by reseller  121  with lender  181 . In response, analysis module  296  causes communication unit  285  to output a signal over network  105  that includes access credentials for accessing information about reseller  121  at accounting system  260 . Communication unit  265  of accounting system  260  detects a signal and outputs to accounting module  276  information about the signal. Accounting module  276  determines that the signal includes access credentials. Accounting module  276  further determines that the signal originates from lender computing system  280 , which accounting module  276  also determines is authorized to access financial records associated with reseller  121  and maintained by reseller  121  at accounting system  260 . Accounting module  276  further determines that the signal corresponds to a request for financial information about reseller  121 . Accounting module  276  accesses data store  277  and causes communication unit  265  to output information over network  105 . Communication unit  285  detects a signal over network  105  and outputs to analysis module  296  information about the signal. Analysis module  296  determines that the signal includes information that can be used to perform a borrowing base calculation. 
     Analysis module  296  calculates, based on the financial information received from accounting system  260  as well as further information, an updated borrowing base for reseller  121 . In some examples, analysis module  296  calculates a borrowing base for reseller  121  based on information about inventory, accounts receivables, accounts payables, and aging information for accounts receivables and payables. Such information may be derived from sales journals, collections journals, debit and/or credit memo journals. For instance, in some examples, analysis module  296  may access data store  297  and analyze historical information about reseller  121 , information about previous advances requested by reseller  121 , and information current balances associated with one or more lines of credit held by reseller  121  with lender  181 . 
     Analysis module  296  may calculate the borrowing base by totaling the values of all pledged collateral, accounts receivables, and other designated assets, and then applying certain adjustments. For instance, analysis module  296  may determine that the value of the collateral pledged by reseller  121  has been increased because the value of the pledged assets have increased based on certain new accounts receivables held by reseller  121  and logged in data store  277  of accounting system  260 . Analysis module  296  may also decrease the value of the collateral pledged based on other information logged in data store  277  of accounting system  260 , such as information about accounts payables, debts owed by reseller  121 , or about accounts receivables no longer held by reseller  121 . For instance, reseller  121  may have an accounts receivable for a third party, but may also have an accounts payable for that same third party. In such a situation, the value that the accounts receivable increases the borrowing base might be decreased or offset by the value of the accounts payable for that same third party. 
     Further, some accounts receivables, accounts payables, and/or other assets might be disqualified or determined to be ineligible for inclusion in the borrowing base calculation. For instance, accounts receivables that are more than a certain age (e.g., 90 days) might be declared ineligible. Also, one or more assets, such as an accounts receivable, might be declared ineligible for inclusion in a borrowing base calculation for other reasons, such as receivables characterized as cross-aged, or those associated with individuals, affiliate companies, government entities, foreign companies, and/or other identified entities. Further, some assets might be declared ineligible or reduced in value based on other circumstances that might weaken the claim associated with the asset (e.g., an accounts receivable claim) or that might otherwise weaken the lender&#39;s ability to convert the underlying asset into cash. 
     In some examples, the borrowing base is that amount that a lender might consider likely to be able to liquidate easily if necessary. Accordingly, although some borrowing base calculations might include assets such as equipment, real estate, other hard assets, and/or inventory, other borrowing base calculations might not include one or more of such items. In some examples, a borrowing base might only include assets that would be relatively easy to convert into cash. Such assets would include bank accounts and accounts receivables, for example. Further, the total value of the assets might, in some examples, be discounted or margined by a percentage, thereby further reducing the borrowing base. As a result of the various adjustments described above, a borrowing base may increase or decrease over time. 
     In some examples, analysis module  296  may calculate a borrowing base each time a request to advance funds is received. In other examples, analysis module  296  may calculate a borrowing base occasionally or periodically (e.g., hourly, daily, weekly). In still other examples, analysis module  296  may calculate a borrowing base only when a request to advance funds would result in outstanding credit that exceeds the maximum current amount, or exceeds a given percentage of the maximum credit amount. For example, analysis module  296  may calculate a borrowing base each time a request to advance funds will result in a balance on the line of credit that exceeds a fixed percentage (e.g., 80%, 90%) of the maximum credit amount. In still other examples, analysis module  296  might determine an updated a borrowing base at other times, or in response to other circumstances. 
     Modules illustrated in  FIG. 2  (e.g., accounting module  276 , authentication module  293 , analysis module  296 , notification module  294 ) and/or illustrated or described elsewhere in this disclosure may perform operations described using software, hardware, firmware, or a mixture of hardware, software, and firmware residing in and/or executing at one or more computing devices. For example, a computing device may execute one or more of such modules with multiple processors or multiple devices. A computing device may execute one or more of such modules as a virtual machine executing on underlying hardware. One or more of such modules may execute as one or more services of an operating system or computing platform. One or more of such modules may execute as one or more executable programs at an application layer of a computing platform. In other examples, functionality provided by a module could be implemented by a dedicated hardware device. 
     Although certain modules, data stores, components, programs, executables, data items, functional units, and/or other items included within one or more storage devices may be illustrated separately, one or more of such items could be combined and operate as a single module, component, program, executable, data item, or functional unit. For example, one or more modules or data stores may be combined or partially combined so that they operate or provide functionality as a single module. Further, one or more modules may interact with and/or operate in conjunction with one another so that, for example, one module acts as a service or an extension of another module. Also, each module, data store, component, program, executable, data item, functional unit, or other item illustrated within a storage device may include multiple components, sub-components, modules, sub-modules, data stores, and/or other components or modules or data stores not illustrated. 
     Further, each module, data store, component, program, executable, data item, functional unit, or other item illustrated within a storage device may be implemented in various ways. For example, each module, data store, component, program, executable, data item, functional unit, or other item illustrated within a storage device may be implemented as a downloadable or pre-installed application or “app.” In other examples, each module, data store, component, program, executable, data item, functional unit, or other item illustrated within a storage device may be implemented as part of an operating system executed on a computing device. 
       FIG. 2  illustrates one example implementation of system  200 . Other example or alternate implementations of system  200  may be appropriate in other instances. Such implementations may include a subset of the devices and/or components included in the example of  FIG. 2  and/or may include additional devices and/or components not shown in  FIG. 2 . Accordingly, although one or more implementations of system  200  have been described with reference to  FIG. 2 , system  200  may be implemented in a number of different ways. 
     For instance, one or more devices of system  200  that are illustrated as separate devices may be implemented as a single device; one or more components of system  200  that are illustrated as separate components may be implemented as a single component. Also, in some examples, one or more devices of system  200  that are illustrated as a single device may be implemented as multiple devices; one or more components of system  200  that are illustrated as a single component may be implemented as multiple components. Each of the multiple devices and/or components may be directly coupled via wired or wireless communication and/or remotely coupled via one or more networks. Also, one or more devices or components illustrated in  FIG. 2  may also be implemented as part of another device or component not shown in  FIG. 2 . In this and other ways, some of the functions described herein may be performed via distributed processing by two or more devices. 
     Further, certain operations, techniques, features, and/or functions have been described herein as being performed by specific components, devices, and/or modules in  FIG. 2 . In other examples, such operations, techniques, features, and/or functions may be performed by different components, devices, or modules. Accordingly, some operations, techniques, features, and/or functions described herein as being attributed to one or more components, devices, or modules in  FIG. 2  may, in other examples, be attributed to other components, devices, and/or modules, even if not specifically described herein in such a manner. 
       FIG. 3A ,  FIG. 3B ,  FIG. 3C , and  FIG. 3D  are conceptual diagrams illustrating example user interfaces presented by a user interface device in accordance with one or more aspects of the present disclosure. The user interfaces illustrated in  FIG. 3A  and  FIG. 3D  may correspond to a user interface presented by lender mobile device  182  of  FIG. 1 . The user interfaces illustrated in  FIG. 3B  and  FIG. 3C  may correspond to a user interface presented by reseller mobile device  122  of  FIG. 1 . 
     Although the user interfaces illustrated in  FIG. 3A  through  FIG. 3D  are shown as graphical user interfaces, other types of interfaces may be presented by lender mobile device  182  and/or reseller mobile device  122 , including a text-based user interface, a console or command-based user interface, a voice prompt user interface, or any other appropriate user interface. One or more aspects of the user interfaces illustrated in  FIG. 3A  through  FIG. 3D  may be described herein within the context of system  200  of  FIG. 2 . 
       FIG. 3A  illustrates an example user interface that may be presented by a computing device as a result of receiving information about a request for an advance from a line of credit. For instance, with reference to an example that can be described in the context of  FIG. 2 , analysis module  296  determines that reseller  121  has requested an advance. Analysis module  296  outputs to notification module  294  information about the advance. Notification module  294  causes communication unit  285  to output a signal over network  105 . Lender mobile device  182  detects a signal over network  105  and determines that the signal includes information sufficient to present a user interface. Lender mobile device  182  generates data associated with a user interface and presents user interface  383 A at display  185  of lender mobile device  182  as illustrated in  FIG. 3A . 
     In  FIG. 3A , user interface  383 A includes a message (i.e., an email) about a requested advance by reseller  121  (i.e., “ABC Reseller”), and includes information about the request, the reseller&#39;s balance, and current borrowing base. In some examples, the current borrowing base may have been recently calculated by lender computing system  280 , and as such may be a near or seemingly-near real time representation of the borrowing base for ABC Reseller. User interface  383 A further prompts the user to approve the request (button  385 ), defer deciding the request (e.g., allow further time for research or consideration, button  386 ), or deny the request (button  387 ). 
       FIG. 3B  illustrates an example user interface that may be presented by a computing device as a result of receiving information about an approval of an advance request. For instance, with reference  FIG. 2  and  FIG. 3A , lender mobile device  182  detects input that lender mobile device  182  determines corresponds to a selection of button  385  of  FIG. 3A . In response, lender mobile device  182  outputs a signal over network  105 . Communication unit  285  of lender computing system  280  detects a signal over network  105 . Communication unit  285  outputs information about the signal to notification module  294 . Notification module  294  determines that the signal corresponds to approval of the advance request. Notification module  294  causes communication unit  285  to output a signal over network  105 . Reseller mobile device  122  detects a signal over network  105  and determines that the signal includes information sufficient to present a user interface. Reseller mobile device  122  generates data associated with a user interface and presents user interface  323 B at display  125  of reseller mobile device  122  as illustrated in  FIG. 3B . 
     In  FIG. 3A , user interface  323 B includes a message indicating that lender  181  (i.e., “XYZ Financing”) has approved the request to advance funds. In some examples, user interface  323 B may include information underlying the decision to approve the request, including the current balance on the line of credit, the maximum available balance, the current borrowing base, and/or other information. 
       FIG. 3C  illustrates another example user interface that may be presented by a computing device as a result of receiving information about an approval of an advance request. For instance, with reference  FIG. 2 , analysis module  296  of lender computing system  280  determines that the requested funds have been transferred to a bank account owned by reseller  121 . Analysis module  296  outputs to notification module  294  information about the transfer. Notification module  294  causes communication unit  285  to output a signal over network  105 . Reseller mobile device  122  detects a signal over network  105  and determines that the signal includes information sufficient to present a user interface. Reseller mobile device  122  generates data associated with a user interface and presents user interface  323 C at display  125  of reseller mobile device  122  as illustrated in  FIG. 3C . In  FIG. 3C , user interface  383 C includes a message indicating that the requested funds have been transferred into a bank account owned by reseller  121  (i.e., ABC Reseller). 
     In some examples, similar procedures might provide ongoing status about the line of credit balance or balances for other accounts, and also might provide suggestions relating to such accounts. For example, notification module  294  might cause a notification to be sent to mobile device  122  when the balance on the line of credit exceeds a certain amount or a certain percentage (e.g., 90%) of maximum. In response, mobile device  122  may present the notification to a user in the form of a user interface similar to the examples illustrated herein. 
       FIG. 3D  illustrates an example user interface that may be presented by a computing device as a result of analyzing information stored within accounting system  260 . For instance, with reference to an example that can be described in the context of  FIG. 2 , analysis module  296  causes communication unit  285  to output a signal over network  105 . Communication unit  265  of accounting system  260  detects a signal over network  105  and outputs to accounting module  276  information about the signal. Accounting module  276  determines that the signal corresponds to a request, from an authorized requestor, for information about banking activities of reseller  121 . Accounting module  276  causes communication unit  265  to output a signal over network  105 . Communication unit  285  of lender computing system  280  detects a signal and outputs to analysis module  296  information about the signal. Analysis module  296  determines that the signal includes information about the banking activities of reseller  121 . Analysis module  296  further determines, based on the information about the banking activities, that reseller  121  has significant foreign account debtors. Analysis module  296  further determines that businesses with significant foreign account debtors are good candidates for foreign exchange services that lender  181  may offer. In response, analysis module  296  causes communication unit  285  to output a signal over network  105 . Lender mobile device  182  detects a signal over network  105  and determines that the signal includes information sufficient to present a user interface. Lender mobile device  182  generates data associated with a user interface and presents user interface  383 D at display  185  of lender mobile device  182  as illustrated in  FIG. 3D . 
     In  FIG. 3D , user interface  383 D includes a message about a possible cross-selling opportunity available to lender  181  (i.e., XYZ Financing). Lender mobile device  182  may present, in response to detecting selection of button  388 , further information about the cross-selling opportunity. Lender mobile device  182  may alternatively present, in response to detecting selection of button  389 , a proposed email inquiring about offering foreign exchange services. Further, lender mobile device  182  may dismiss the notification about the opportunity in response to detecting selection of button  390 . 
     In the example illustrated in connection with  FIG. 3D , analysis module  296  identified the cross-selling opportunity based on financial information about reseller  121  retrieved from accounting system  260 . Lender computing system  180  may have access credentials enabling access to such information, and/or may have access to such information for other purposes (e.g., calculating a current borrowing base). The information available from accounting computing system  160  might be effectively used by analysis module  296  to identify cross-selling and/or upselling opportunities. Notification module  294  may provide nonfictions about such opportunities by, for example, sending a communication to lender mobile device  182 . 
     In general, notification module  294  of lender computing system  280  may send at least two types of notifications and/or messages: (1) notifications about financing status events (sent to both a user of lender mobile device  182  and to a user of reseller mobile device  122 ) and (2) messages identifying business opportunities in the form of cross-selling and upselling opportunities (sent to a user of lender mobile device  182  or to a device operated by another associated with lender  181 ). For example, notification module  294  may generate and send various notifications, including information about the status of financing requests, approvals, borrowing base calculations, and line of credit usage. The frequency of and type of those notifications could be initially configured by the user of lender mobile device  182  (e.g., a relationship manager employed by lender  181 ) and by a user of reseller mobile device  122  (e.g., an employee of reseller  121 ). Thereafter, notification module  294  may learn which items the recipient wants to continue receiving, based on how the recipient interacts with messages of different types. For example, if messages are not often read, or are deleted, notifications of a similar type might not be sent in the future. On the other hand, messages that the recipient tends to act on, could be given a higher priority, and perhaps flagged in some way to ensure the recipient sees those messages. 
     Notification module  294  may generate and send notifications and/or messages about cross-selling opportunities based on its access to the reseller&#39;s financial information at accounting computing system  160 . For example, notification module  294  and/or analysis module  296  may identify, based on the financial information, bank service fees charged by competing banks, and determine situations where lender  181  is able to offer a competitive service to reduce such fees. Notification module  294  may send a message to a device operated by a relationship manager employed by lender  181 . The message may identify the opportunity to sell the identified competitive service. In another example, notification module  294  and/or analysis module  296  might identify situations in which reseller  121  has foreign subsidiaries, and might therefore generate a message intended for the relationship manager at lender  181  describing how foreign exchange services could beneficial to that reseller. In another example, notification module  294  and/or analysis module  296  might identify situations in which a reseller has a significant term loan, and may generate a message describing how interest rate hedging services could be helpful to that reseller. 
     Further, notification module  294  may generate and send notifications and/or messages about upselling opportunities based on its access to the reseller&#39;s financial information at accounting computing system  160 . For instance, notification module  294  and/or analysis module  296  may identify, based on the financial information, situations where reseller  121  is working with a vendor (e.g., another vendor  111 ) that has a reseller financing program being sponsored by lender  181 , and where that reseller is not participating in that other vendor&#39;s program. Notification module  294  may cause a message to be sent to the relationship manager at lender  181  identifying the opportunity to offer to reseller  121  participation in the program. In another example, notification module  294  and/or analysis module  296  may, based on analysis of the reseller&#39;s financial data, identify instances where lender  181  is missing out on potential business, such as where a reseller bought inventory from a vendor on “open account” (meaning through a direct purchase from the vendor, without a financing partner such as lender  181 ). Analysis of the reseller&#39;s financial data, enabled through availability of financial information at accounting computing system  160 , provides visibility into such missed potential business, and the system could send messages to a manager employed by lender  181  that highlight new opportunities based on information determined about previously missed business opportunities. 
       FIG. 4  is a flow diagram illustrating accounting operations performed by an example computing system lender computing system in accordance with one or more aspects of the present disclosure.  FIG. 4  illustrates operations corresponding to what might be referred to as “zero balance accounting.” Such accounting practices may be used systems described herein, such as system  100  of  FIG. 1  and system  200  of  FIG. 2 . 
       FIG. 4  is described below within the context of lender computing system  180  of  FIG. 1 . In other examples, operations described in  FIG. 4  may be performed by one or more other components, modules, systems, or devices. Further, in other examples, operations described in connection with  FIG. 4  may be merged, performed in a difference sequence, or omitted. 
     In the example of  FIG. 4 , reseller  121  is assumed to have at least two accounts, a cash bank account, and a line of credit extended to reseller  121  by lender  181 . During the course of business operations, when cash is needed by reseller  121 , cash is drawn from the line of credit. When cash is available in the bank account, that cash is used to pay down the line of credit. In some examples, once the line of credit has been paid off (i.e., the line of credit has no outstanding balance), any excess cash in the bank account held by reseller  121  might be invested in a treasury or other account. The result is that the line of credit is used in an efficient manner, and any excess cash can be invested productively. 
     If lender computing system  180  has access to current financial information for reseller  121 , lender computing system  180  may be able to determine an accurate and current borrowing base for reseller  121 . And therefore, lender computing system  180  may be able to make an accurate determination of a maximum line of credit that lender  181  may be willing to extend to reseller  121  at any given time. With that information, lender computing system  180  can effectively implement zero balance accounting, and may do so automatically.  FIG. 4  is described below within the context of lender computing system  180  of  FIG. 1 . Systems described herein may advantageously practice one or more aspects of the process illustrated in  FIG. 4 . In other examples, operations described in  FIG. 4  may be performed by one or more other components, modules, systems, or devices. Further, in other examples, operations described in connection with  FIG. 4  may be merged, performed in a difference sequence, or omitted. 
     In the example of  FIG. 4 , and in accordance with one or more aspects of the present disclosure, banking computing system  190  and/or lender computing system  180  may process one or more transactions during the normal course of business operations ( 401 ). Such transactions may affect (e.g., increase or decrease) the balance associated with a cash account held by reseller  121 . Lender computing system  180  may determine a cash account balance held by reseller  121  ( 402 ). For instance, in the example of  FIG. 2 , lender computing system  180  requests, from banking computing system  190  over network  105 , information about the balance in the bank account held by reseller  121 . Banking computing system  190  responds with information about the balance. 
     Lender computing system  180  may determine that the cash account balance is greater than zero ( 403 ). Lender computing system  180  evaluates the information about the balance, and if lender computing system  180  determines that the balance is greater than zero, lender computing system  180  may use the available cash to pay down any balance on the line of credit held by reseller  121  ( 404 ). To do so, lender computing system  180  may request, from banking computing system  190  over network  105 , information about the balance on the line of credit. Lender computing system  180  may receive information about the line of credit and cause banking computing system  190  to use the excess cash to pay down the line of credit using any available cash, until the balance on the line of credit is zero. 
     Lender computing system  180  may determine that the cash account balance is less than zero ( 405 ). If lender computing system  180  determines that the balance on the bank account held by reseller  121  is less than zero, lender computing system  180  may draw from the line of credit as needed unit the cash account balance is restored to zero ( 406 ). For instance, lender computing system  180  may cause banking computing system  190  to transfer funds from the line of credit held by reseller  121  until the cash account balance for reseller  121  has been restored to zero ( 407 ). 
       FIG. 5  is a flow diagram illustrating operations performed by an example computing system lender computing system in accordance with one or more aspects of the present disclosure.  FIG. 5  is described below within the context of lender computing system  180  of  FIG. 2 . In other examples, operations described in  FIG. 5  may be performed by one or more other components, modules, systems, or devices. Further, in other examples, operations described in connection with  FIG. 5  may be merged, performed in a difference sequence, or omitted. 
     In the example of  FIG. 5 , and in accordance with one or more aspects of the present disclosure, lender computing system  180  may maintain available credit amounts for one or more resellers  121  ( 501 ). For instance, in some examples, lender  181  may extend lines of credit to one or more resellers  121 . For each reseller  121 , lender computing system  180  may maintain an available credit amount, based on previous cash advances extended to each of reseller  121  and based on payments received from each reseller  121 . Lender computing system  180  may also maintain other information about each of resellers  121 , such as access credentials enabling lender computing system  180  to access financial information about each of resellers  121 . Such financial information may be up-to-date or near-real time financial information, and may include information sufficient to determine a borrowing base for each of resellers  121 . 
     Lender computing system  180  may receive a request for an advance ( 502 ). For instance, lender computing system  180  may receive, over network  105 , a signal that it determines corresponds to a request to advance cash. Lender computing system  180  may identify the requesting entity and the advance amount ( 503 ). Lender computing system  180  determine, based on the signal received over network  105 , which of the resellers  121  originated the request to advance cash. Lender computing system  180  may further determine, based on the signal received, an advance amount, which may be an amount of cash that the requesting reseller  121  seeks to have advanced. 
     Lender computing system  180  may determine whether the advance amount is greater than the available credit for the requesting entity ( 504 ). In some examples, lender computing system  180  may grant the request if the advance amount is less than the available credit ( 505 ). If the request amount is greater than the available credit, then lender computing system  180  may access financial information for the requesting entity ( 506 ). For instance, lender computing system  180  may request, over network  105 , financial information about reseller  121  that reseller  121  maintains at accounting computing system  160 . Accounting computing system  160  may respond to the request by sending, over network  105 , financial information about reseller  121 . Lender computing system  180  may receive, over network  105 , the financial information from accounting computing system  160 . 
     Lender computing system  180  may adjust the available credit ( 507 ). Lender computing system  180  may perform a borrowing base calculation taking into account current financial information about reseller  121 . Lender computing system  180  may determine a borrowing base for reseller  121  based on recent accounts receivables for reseller  121 , aging information associated with those accounts receivables, any offsetting accounts payables, and other information. 
     Lender computing system  180  may grant the request if the advance amount is not greater than the adjusted available credit ( 508 ). For instance, lender computing system  180  may determine that the borrowing base has increased for reseller  121 , and that the advance amount is not greater than the adjusted available credit ( 505 ). Lender computing system  180  deny the request if the advance amount is greater than the adjusted available credit ( 509 ). In some examples, lender computing system  180  may offer to advance a lesser amount, rather than denying the request. Such a lesser amount may, in some examples, be an amount equal to or approximately equal to the remaining adjusted available credit for reseller  121 . 
     For processes, apparatuses, and other examples or illustrations described herein, including in any flowcharts or flow diagrams, certain operations, acts, steps, or events included in any of the techniques described herein can be performed in a different sequence, may be added, merged, or left out altogether (e.g., not all described acts or events are necessary for the practice of the techniques). Moreover, in certain examples, operations, acts, steps, or events may be performed concurrently, e.g., through multi-threaded processing, interrupt processing, or multiple processors, rather than sequentially. Further certain operations, acts, steps, or events may be performed automatically even if not specifically identified as being performed automatically. Also, certain operations, acts, steps, or events described as being performed automatically may be alternatively not performed automatically, but rather, such operations, acts, steps, or events may be, in some examples, performed in response to input or another event. 
     The detailed description set forth above is intended as a description of various configurations and is not intended to represent the only configurations in which the concepts described herein may be practiced. The detailed description includes specific details for the purpose of providing a thorough understanding of the various concepts. However, these concepts may be practiced without these specific details. In some instances, well-known structures and components are shown in block diagram form in the referenced figures in order to avoid obscuring such concepts. 
     In accordance with one or more aspects of this disclosure, the term “or” may be interrupted as “and/or” where context does not dictate otherwise. Additionally, while phrases such as “one or more” or “at least one” or the like may have been used in some instances but not others; those instances where such language was not used may be interpreted to have such a meaning implied where context does not dictate otherwise. 
     In one or more examples, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored, as one or more instructions or code, on and/or transmitted over a computer-readable medium and executed by a hardware-based processing unit. Computer-readable media may include computer-readable storage media, which corresponds to a tangible medium such as data storage media, or communication media including any medium that facilitates transfer of a computer program from one place to another (e.g., pursuant to a communication protocol). In this manner, computer-readable media generally may correspond to (1) tangible computer-readable storage media, which is non-transitory or (2) a communication medium such as a signal or carrier wave. Data storage media may be any available media that can be accessed by one or more computers or one or more processors to retrieve instructions, code and/or data structures for implementation of the techniques described in this disclosure. A computer program product may include a computer-readable medium. 
     By way of example, and not limitation, such computer-readable storage media can include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage, or other magnetic storage devices, flash memory, or any other medium that can be used to store desired program code in the form of instructions or data structures and that can be accessed by a computer. Also, any connection is properly termed a computer-readable medium. For example, if instructions are transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. It should be understood, however, that computer-readable storage media and data storage media do not include connections, carrier waves, signals, or other transient media, but are instead directed to non-transient, tangible storage media. Disk and disc, as used, includes compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-ray disc, where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media. 
     Instructions may be executed by one or more processors, such as one or more digital signal processors (DSPs), general purpose microprocessors, application specific integrated circuits (ASICs), field programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuitry. Accordingly, the terms “processor” or “processing circuitry” as used herein may each refer to any of the foregoing structure or any other structure suitable for implementation of the techniques described. In addition, in some examples, the functionality described may be provided within dedicated hardware and/or software modules. Also, the techniques could be fully implemented in one or more circuits or logic elements. 
     The techniques of this disclosure may be implemented in a wide variety of devices or apparatuses, including a wireless handset, a mobile or non-mobile computing device, a wearable or non-wearable computing device, an integrated circuit (IC) or a set of ICs (e.g., a chip set). Various components, modules, or units are described in this disclosure to emphasize functional aspects of devices configured to perform the disclosed techniques, but do not necessarily require realization by different hardware units. Rather, as described above, various units may be combined in a hardware unit or provided by a collection of interoperating hardware units, including one or more processors as described above, in conjunction with suitable software and/or firmware.