Invention Grant
- Patent Title: Dynamic hierarchical learning engine matrix
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Application No.: US15909309Application Date: 2018-03-01
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Publication No.: US10776462B2Publication Date: 2020-09-15
- Inventor: Eren Kursun , Dharmender Kumar Satija
- Applicant: BANK OF AMERICA CORPORATION
- Applicant Address: US NC Charlotte
- Assignee: BANK OF AMERICA CORPORATION
- Current Assignee: BANK OF AMERICA CORPORATION
- Current Assignee Address: US NC Charlotte
- Agency: Moore & Van Allen PLLC
- Agent Michael A. Springs; Nicholas C. Russell
- Main IPC: G06F21/31
- IPC: G06F21/31 ; H04L29/08 ; G06F21/45 ; G06N20/00

Abstract:
Embodiments of the invention are directed to systems, methods, and computer program products for identification of normal state authenticity indicators for user and entity authentication into applications in real-time to prevent misappropriation at the point of authenticity. In this way, the system uses multiple modeling processes for identification of authentic access requests to prevent misappropriation including utilizing phase-based characterization of different perspectives to make real-time determinations on authenticity of an interaction and/or misappropriation likelihood. The invention relies on multiple characteristics and models in simultaneous utilization for real-time authenticity decisions.
Public/Granted literature
- US20190272360A1 DYNAMIC HIERARCHICAL LEARNING ENGINE MATRIX Public/Granted day:2019-09-05
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