Wells Fargo Bank, N.a.

Other

James Christopher Noe

Ashish Bhoopen Kurani

Imran Haider

Nathan Coles

Braden More

Frank Fehrenbach

Chandra Subramanian

Mattie L Morris

Matthew C Strader

Palani Munuswamy

Guruprasadh Prasadh Ragothaman

George Atala

Loftlon Worth

Daniel David

Albert Hwu

Shane Duncan Eaton

Derek D Mohr

Ken C Kiernan

Todd Douglas Simmel

Jacob T Orth

Theresa Ann Clements

Michelle E Ziolkowski

Ranganathan Kanchi

Robert D McKeirnan, Jr

Dinesh Arora

Udaya Isampalli

Joseph Borgia

Christopher George Klapheke

Jesse Owens

Greg J Hansen

Kiran Rapolu

Lofton Worth

Point of sale (POS) devices, systems, and methods disclosed herein enable payments by merchants to non-customers, such as to employees of the merchant. A point of sale system of the merchant determines an amount of a payment to be made by the merchant to the employee. The point of sale system transmits payment instructions for executing the payment to a payment system provider computing system. The funds are made available in a bank account of the employee instantly or near instantly.

Instant network cash transfer at point of sale

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, methods, and other embodiments associated with cash pooling. According to one embodiment, a system includes an account logic configured to receive at least one change selected by a user and make the at least one change to a pool. The pool includes a plurality of accounts. The system further includes a settlement logic configured to calculate a balance for one or more accounts in the pool. The settlement logic is further configured to identify at least one settlement options for the one or more accounts based at least in part on the balance.

Systems and methods associated with cash pooling

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 access rights may include a first computing system that receives a request to link an enterprise account of the first computing system to a second computing system. The first computing system may authenticate a user, receive a selection of one or more access rights, and one or more accounts of the enterprise account, via an application interface of the second computing system, and generate an access token for transmission to a computing device of the user, where the access token identifies the one or more access rights and the one or more accounts. The first computing system may transmit the access token to the computing device, to provide the computing device access to the one or more accounts according to the one or more access rights, of the first computing system, via the second computing system.

Systems and methods for providing access rights of an enterprise account to an enterprise resource

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

A remote deposit capture system for distributed processing of check presentation can sense, or be instructed to differentiate, between deposit document types, including checks, cash withdrawals, and casino markets. Thereby, automated recognition and correction features can be selectively applied to an imaged deposit document. Thereby deposit documents that tend to use identical transaction codes, such as the same routing/transit numbers in magnetic ink character recognition (MICR) code line data, can be effectively processed without a high failure rate due to duplicate detection. Yet the advantages of duplicate detection are still leveraged against other deposit types. Alternatively or in addition, duplicate detection can be selected to not depend upon uniqueness of MICR code line data.

Remote deposit capture for the gaming industry

Growing community of inventors

Charlotte, NC, United States of America

James Christopher Noe