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:
Jul. 08, 2025

Filed:

Nov. 10, 2022
Applicant:

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

Inventors:

Vinesh Patel, London, GB;

Michael Young, Davidson, NC (US);

Assignee:

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

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06K 19/07 (2006.01); H04L 41/046 (2022.01); H04L 43/04 (2022.01); H04L 67/303 (2022.01); H04W 4/50 (2018.01); H04W 4/80 (2018.01);
U.S. Cl.
CPC ...
H04W 4/50 (2018.02); G06K 19/0719 (2013.01); H04L 41/046 (2013.01); H04L 43/04 (2013.01); H04L 67/303 (2013.01); H04W 4/80 (2018.02);
Abstract

Apparatus, methods and systems for voice surveillance using enhanced metadata and geotagging capabilities are provided. Systems may monitor communications being transmitted from, and being received at, entity devices. The communications may be monitored for anomalies. The anomalies may be identified as communications outside of a regular pattern of communications. Various factors may be used to identify the anomalous communications. The factors may include a number of communications per predetermined time period, a geolocation of the communication, identification of a second communicative party of the communication and any other suitable factors. Stakeholders may be alerted regarding any anomalous communications. Additionally, once the communications have been labeled as anomalous or non-anomalous, the labeled communications may be used to create and/or update a set of labeled training data. The created and/or updated set of labeled training data may be used in an artificial intelligence engine that labels communications as anomalous or non-anomalous.


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