Abstract: Systems and methods for providing recommendations relating to payment methods include establishing a connection between a first application executing on a first server and a second application executing on a second server where the first and second applications are linked to a first account holder. The first application may receive invoice data of a plurality of invoices from the second application. The first application may identify that at least one recipient is enrolled to accept a second payment type with one or more second account holders. The first application may identify a subset of invoices corresponding to the at least one recipient, compute a difference between a first value corresponding to usage of a first payment type and a second value corresponding to usage of the second payment type, and present a recommendation to enroll the first account holder with the second payment type based on the difference.

Abstract: Systems and methods for providing recommendations relating to payment methods include establishing a connection between a first application executing on a first server and a second application executing on a second server where the first and second applications are linked to a first account holder. The first application may receive invoice data of a plurality of invoices from the second application. The first application may identify that at least one recipient is enrolled to accept a second payment type with one or more second account holders. The first application may identify a subset of invoices corresponding to the at least one recipient, compute a difference between a first value corresponding to usage of a first payment type and a second value corresponding to usage of the second payment type, and present a recommendation to enroll the first account holder with the second payment type based on the difference.

Abstract: Systems and methods are described herein for generating data analytics and implementing payoff plans. Such systems and methods may use an institution computing system to retrieve, from an application programming interface (API), first data relating to an input of a first entity. The system retrieves second data relating to the input from one or more second APIs. After receiving the first data and the second data, the system identifies third data relating to a financing of the input of the first entity. Responsive to an update to the input, the system determines a payoff plan for the updated input by applying the first data, the second data, and the third data to one or more machine learning models. After the one or more machine learning models generates the payoff plan, the system causes implementation of the payoff plan automatically through a computing system of the first entity.

Abstract: A method includes authenticating, by a resource of a mobile device, a user for accessing the resource based on user credentials of the user, determining, according to a profile of the user, a set of allowable actions to be taken by the user, determining a list of accounts linked to the profile of the user, receiving an image of an identifier corresponding to a product, the image captured by a camera of the mobile device, extracting characters from the image corresponding to the identifier, initiating a request, to a server, including i) the identifier and ii) information corresponding to the list of accounts, receiving, responsive to the request, data corresponding to the product and displaying information relating to the data which corresponds to the product, including the set of allowable actions permitted to be performed.

Abstract: Systems and methods for receiving an enterprise resource dataset associated with a customer from an enterprise application associated with the customer, the enterprise resource dataset including a plurality of financial inputs captured on or before a first date, a plurality of customer recommendations, and a plurality of recommendation replies, receiving, from a first machine learning model, a predicted customer state including one or more predicted financial outputs corresponding with the predicted customer state at a second date subsequent to the first date, providing the plurality of financial inputs to a second machine learning model trained to predict a customer recommendations, determining, a customer recommendation corresponding to an action to be performed at a third date subsequent to the first date, wherein performing the action causes the first machine learning model to predict an updated customer state differing from the predicted customer state.

Abstract: Systems and methods for receiving an enterprise resource dataset includes a plurality of financial inputs captured associated with a customer from an enterprise application associated with the customer, providing the plurality of financial inputs to a machine learning model trained to predict a customer state using a plurality of training financial inputs and a plurality of training financial outputs, each of the plurality of training financial inputs corresponding to financial data and each of the plurality of training financial outputs corresponding with financial data, determining, responsive to providing the plurality of financial inputs to the machine learning model, a future customer state of the customer, including a predicted financial output, at a fourth date, and generating one or more financial recommendations based at least partially on the determined future customer state of the customer.

Abstract: Systems and methods for facilitating communication between computing systems may include a device which establishes a connection between a first application executing on a first server and a second application executing on a second server. The first application and the second application may be linked to a common account holder. The first application may transmit, to the second application, at least a portion of data associated with the common account holder and accessible via the first application. The first application may generate populated form fields for a form associated with the first application using data from the second application and the data received by the second application from the first application. The first application may generate a new account for the common account holder using the populated form fields received from the second application.

Abstract: Systems and methods for providing early payment recommendations may include one or more processors establish a connection between a first data source and a second data source, and maintain a machine-learning model trained to ingest data from the first and second data source. The processor(s) may detect a data entry for an invoice between an enterprise and a third party via the connection, extract a trade term from the invoice responsive to detecting the data entry, apply the trade term to the machine-learning model as a first input, and apply data of the account of the second data source to the machine-learning model as second input. The processor(s) may receive, from the machine-learning model, an output including a score for early-payment of the data entry according to the trade term and the data of the account, and transmit a notification for the invoice to a computing device of the enterprise.

Abstract: Systems and methods for receiving an enterprise resource dataset associated with the first entity, the enterprise resource dataset including an invoice data for the first entity, the invoice data including a first data entry including first value and a first maturity date and a second data entry including a second value and second maturity date, determining a predicted future account balance, determining based on the predicted future account balance, the first value, the second value, the first maturity date, the second maturity date, one or more financing options including a first finance option associated with the first data entry included in the invoice data, generating, a user interface display configured to be displayed within the enterprise application, the user interface display including the first finance option a selection of the first finance option, and initiating a first transfer to a second entity associated with the first data entry.

Abstract: Systems and methods for receiving, from an enterprise application associated with a first entity, a first data entry including first value and a first maturity date and a second data entry including a second value and second maturity date, determining, a predicted future account balance, determining, based on the predicted future account balance, the first value, the second value, the first maturity date, the second maturity date, one or more financing options including a first finance option associated with the first data entry included in the invoice data, generating, a user interface display including the first finance option, receive, from the enterprise application, a selection of the first finance option, in response to receiving the selection of the first finance option, initiating, a first transfer to the first entity corresponding with the first value before the first maturity date.

Abstract: Systems and methods for facilitating communication between computing systems may include a device which establishes a connection between a first application executing on a first server and a second application executing on a second server. The first application and the second application may be linked to a common account holder. The first application may transmit, to the second application, at least a portion of data associated with the common account holder and accessible via the first application. The first application may generate populated form fields for a form associated with the first application using data from the second application and the data received by the second application from the first application. The first application may generate a new account for the common account holder using the populated form fields received from the second application.