Bank of America Corporation

Letishia Renee Hunt

Charles Christopher Harbinson

Eric Dryer

Adam Nathaniel Desautels

Verlon S Watson

Jeffrey R Goertz

Verlon Safold Watson, Iii

Timothy Alan Mincey

Clarence E Lee

Coty Tyler Cherrix

Brendan P Murphy

Barry Hall

Brigitte Marie Doughty

Lucy M Lahera

Collin Jarel Cacho Lenon

Kyaw Htet Kyi

Clement Chellaraj

Christine Malabad

Aspects of the disclosure relate to performing enhanced exception processing using cognitive automation tools. In some embodiments, a computing platform may receive interaction data identifying one or more actions performed by one or more users in resolving a plurality of exception items associated with an exception queue. Subsequently, the computing platform may train, using a learning engine, a machine learning model to resolve a first exception and a second exception of one or more exceptions based on the interaction data. Based on training the machine learning model, the computing platform may generate one or more configuration commands directing a processing module to implement the machine learning model to process additional exception items associated with the exception queue. The computing platform then may send the one or more configuration commands to the processing module.

Performing enhanced exception processing using cognitive automation tools

A system is provided for file capture and in-line error correction. The system comprises: a controller configured to capture and process a file during a file capture sequence comprising one or more capture events, the controller being configured to: capture a file using a file capture device associated with a user device, wherein capturing the file comprises receiving a file image and a user input data field associated with the file; identify, using an in-line file analysis module, an error with a capture event during the file capture sequence, wherein the error is a discrepancy identified between the user input data field and an image-derived data field; correct the error in the file before the file capture sequence is completed and the file is exported; and export the file, wherein the file capture sequence is completed.

File capture and processing system with in-line error detection

Aspects of the disclosure relate to performing enhanced deposit item processing using cognitive automation tools. In some embodiments, a computing platform may receive, from a deposit item input support server, image data associated with a deposit item. Subsequently, the computing platform may apply a machine learning classification model to the image data associated with the deposit item. In doing so, the computing platform may produce one or more predicted values for one or more fields of the deposit item and one or more confidence scores for the one or more predicted values. Based on these predicted values and confidence scores, the computing platform may generate and send one or more commands directing the deposit item input support server to accept or reject the deposit item, which in turn may cause the deposit item input support server to accept or reject the deposit item.

Performing enhanced deposit item processing using cognitive automation tools

A system includes a template database storing, for each of a plurality of predefined root causes, a corresponding correspondence template and response form template. Each root cause corresponds to a cause of an exception associated with an ATM. An automatic reconciliation tool determines a exception has occurred associated with a ATM. A set of exception parameters are determined associated with the exception. A party is determined at the service provider with which to correspond in or order to resolve the exception. A root cause of the exception is determined. A correspondence template and a response form template are identified for the determined root cause and used to generate correspondence which includes a description of the exception, instructions for actions to take, and a link configured to provide access to a response form. The response form includes fields for providing a response parameter.

Automatic exception reconciliation

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Charlotte, NC, United States of America

Letishia Renee Hunt