The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Apr. 18, 2023

Filed:

Jun. 01, 2020
Applicant:

Bank of America Corporation, Charlotte, NC (US);

Inventors:

Christine Malabad, Charlotte, NC (US);

Jeffrey R. Goertz, Liberty, MO (US);

Letishia R. Hunt, Charlotte, NC (US);

Clement Chellaraj, Charlotte, NC (US);

Eric Dryer, Charlotte, NC (US);

Clarence E. Lee, Charlotte, NC (US);

Charles Christopher Harbinson, Mooresville, NC (US);

Verlon S. Watson, Charlotte, NC (US);

Assignee:

Bank of America Corporation, Charlotte, NC (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 5/00 (2006.01); G06N 5/043 (2023.01); G06N 20/00 (2019.01); G06Q 40/02 (2023.01); G06Q 20/10 (2012.01); G06Q 10/10 (2023.01); G06Q 10/0631 (2023.01); G06Q 20/04 (2012.01);
U.S. Cl.
CPC ...
G06N 5/043 (2013.01); G06N 20/00 (2019.01); G06Q 10/06316 (2013.01); G06Q 10/10 (2013.01); G06Q 20/1085 (2013.01); G06Q 40/02 (2013.01); G06Q 20/042 (2013.01);
Abstract

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.


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