Bank of America Corporation

Jason Daniel Latta

Nelipher Moyo

Jisoo Lee

William P Jacobson

Morgan Stewart Allen

Clifford Todd Barnett

Anurag Amatya

John A Curl

Kenton C Smith

David Stuart Rietz

Ruben C Berumen

Richard T Mattingly

A computing platform may receive, from a web server, entity identification information in different formats, and normalize the entity identification information. After normalizing the information, the computing platform may receive a plurality of interaction records each associated with an interaction between a system and a client of the system. The computing platform may compare the normalized entity identification information with the interaction records of the interactions between the system and the clients of the system. After determining that the entity identification information matches client information for one of the interaction records, the computing platform may send an alert to a control server. The alert may cause the control server to take one or more actions with respect to the client. For example, future attempts by the client to access one or more services offered by the system may be blocked for access by the client.

Controlling interactions and generating alerts based on iterative fuzzy searches of a database and comparisons of multiple variables

Aspects of the disclosure relate to implementing and using a data processing system with a machine learning engine to provide automated collaboration assistance functions. A computing platform may receive, from a teleconference hosting computer system, a content stream associated with a teleconference. Responsive to receiving the content stream associated with the teleconference, the computing platform may generate, based on a machine learning dataset, real-time transcript data comprising a real-time textual transcript of the teleconference. The computing platform may receive a request for a summary of the teleconference. Responsive to receiving the request for the summary of the teleconference, the computing platform may generate, based on the real-time transcript data comprising the real-time textual transcript of the teleconference, a summary report of the teleconference. Based on generating the summary report of the teleconference, the computing platform may send the summary report of the teleconference to one or more recipient devices.

Data processing system with machine learning engine to provide automated collaboration assistance functions

Systems for predicting features to be accessed by a user and generating a customized user interface are provided. In some examples, a computing platform may receive a request to access a system. In some examples, a content data stream may be received including data associated with the identity of the user, current date and time information, and the like. Data may be extracted from the content stream and analyzed, based on one or more machine learning datasets (generated internally or received from an external source), to predict a likely function or feature the user may access. In some examples, access to other features may be disabled. Responsive to identifying the likely feature, the system may enable access to the predicted feature and may generate a customized user interface including the predicted feature. The customized and dynamic user interface may include and place the predicted feature in a predetermined location on the user interface, in a size and/or format other than standard.

Data processing system with machine learning engine to provide dynamic interface functions

Aspects of the disclosure relate to implementing and using a data processing system with a machine learning engine to provide automated collaboration assistance functions. A computing platform may receive, from a teleconference hosting computer system, a content stream associated with a teleconference. Responsive to receiving the content stream associated with the teleconference, the computing platform may generate, based on a machine learning dataset, real-time transcript data comprising a real-time textual transcript of the teleconference. The computing platform may detect, during the teleconference, based on the real-time transcript data comprising the real-time textual transcript of the teleconference, an action item associated with the teleconference. Responsive to detecting the action item associated with the teleconference, and based on the machine learning dataset, the computing platform may identify and execute one or more automated tasks associated with the action item associated with the teleconference.

A system and method of determining a recommended location for performing a work function is provided. In some examples, the system and method may include receiving a plurality of process criteria, such as hours of operation associated with the work function, type of work performed, skill set desired, language skills desired, and the like. The system and method may further include receiving a plurality of provider attributes, such as languages spoken, knowledge base/skill set, flexibility of staffing, and the like. One or more recommended locations for performing the work function may be determined based on the business and provider attributes.

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Charlotte, NC, United States of America

Jason Daniel Latta