Wells Fargo Bank, N.a.

Nathan Coles

Ashish Bhoopen Kurani

Imran Haider

James Christopher Noe

Braden More

Frank Fehrenbach

Mattie L Morris

Chandra Subramanian

Palani Munuswamy

Matthew C Strader

George Atala

Guruprasadh Prasadh Ragothaman

Loftlon Worth

Debarchana Roy

Steve Perez

Dennis Emmanuel Montenegro

Darren M Goetz

Uma Meyyappan

Lofton Worth

A method includes obtaining, by a mobile client application of a user mobile device, context data associated with a user, predicting, by the mobile client application, an intended action of the user to be performed at a provider location based on the context data associated with the user, and switching, by the mobile client application, into a context-based application mode based on the intended action of the user.

Contextual mobile client application systems and methods

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.

Systems and methods for providing recommendations relating to enrollment and payment type

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.

Systems and methods for providing recommendations relating to customer state

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.

Systems and methods for determining customer state

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.

Systems and methods for providing early payment recommendations

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.

Systems and methods for accounts payable-based batch processing

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.

Systems and methods for accounts receivable-based batch processing

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.

Systems and methods for facilitating communications between computing systems

Systems, methods, and apparatuses for completing an action requested by a customer are described herein. A requested action is received from the customer. A customer task for completion of the requested action to be performed by the customer is identified. An interaction board is generated that is accessible by the customer and accessible an employee associated with a provider. The interaction board is displayable via a graphical user interface and includes the customer task. An indication is received from the customer that the customer task has been completed prior to a customer interaction. The interaction board is updated to indicate that the customer task has been completed prior to the customer interaction. Information associated with the requested action is received from a customer device during the customer interaction. The interaction board is updated to include the information received from the customer device during the customer interaction.

Systems and methods for an interactive customer interface utilizing customer device context

Systems, methods, and apparatuses for securely completing a dual custody activity are described herein. A security activity management system comprises a network, an employee device, a supervising employee device, and a provider computing system. The provider computing system is associated with a provider. The provider computing system comprises a processing circuit structured to identify a plurality of employees eligible for performing a task based employee rankings of the plurality of employees and transmit an indication of the plurality of employees eligible for performing the task to a supervising employee via an augmented reality to be displayed on the supervising employee device. The processing circuit is further structured to receive a selection indicating an employee that is associated with the employee device to perform the dual custody activity, authorize the employee to perform the task, and monitor the employee while the employee performs the task.

Systems and methods for facilitating secure dual custody activities

A provider computing system provides a mobile banking application to a user mobile device. The mobile banking application is configured to activate a contextual provider location mode when the user enters a provider location. The contextual provider location mode presents a plurality of modifications to both appearance and operation of the mobile banking application. Each modification is in response to an analysis performed by a context circuit of the mobile banking application. The modifications serve to facilitate the user's experience at the provider, enabling the user to perform their intended tasks in an easier more efficient manner. Additional data pertaining to the user's tasks and behavior are further categorized and transmitted back to the provider, enabling further accuracy and improvements during subsequent visits.

Growing community of inventors

El Cerrito, CA, United States of America

Nathan Coles