Bank of America Corporation

Verizon Patent and Licensing Inc.

Belinda Franklin-Barr

Patrick Lewis

Daniel M Jacobson

John Rivera

Aspects of the disclosure relate to machine learning based analysis of electronic communications. A computing platform may monitor receipt of a potentially unacceptable electronic communication by a user. Then, the computing platform may extract one or more attributes of the potentially unacceptable electronic communication. The computing platform may then perform, based on the one or more attributes, textual analysis of the potentially unacceptable electronic communication. Subsequently, the computing platform may retrieve one or more rules applicable to the potentially unacceptable electronic communication. Then, the computing platform may determine, based on the textual analysis and the one or more rules, and based on a repository of previously identified unacceptable content, whether the potentially unacceptable electronic communication is unacceptable. Subsequently, the computing platform may trigger, based on a determination that the potentially unacceptable electronic communication is unacceptable, one or more actions associated with the unacceptable electronic communication.

Machine learning based analysis of electronic communications

A system may include a database configured to selectively store and retrieve data. The system may further include a call record parser configured to receive a plurality of call records, each call record being associated with a respective call, parse the plurality of call records to identify periods of resource usage and types of resource usage for the associated calls, create parsed data based on the identified periods of resource usage and the types of resource usage, and store the parsed data in the database indexed according to the type of the identified resource and including the start and end times for the identified periods of usage.

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Colorado Springs, CO, United States of America

Belinda Franklin-Barr