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公开(公告)号：US11710033B2
公开(公告)日：2023-07-25
申请号：US16006559
申请日：2018-06-12
Applicant: Bank of America Corporation
Inventor： Ronnie J. Morris , Dana M. Pusey-Conlin , Lorraine C. Edkin , Scott A. Sims , Joel Filliben , Margaret A. Payne , Craig Douglas Widmann , Eren Kursun
CPC classification number: G06N3/08 , G06F16/2291 , G06F16/26 , G06F16/288 , G06N3/04
Abstract: Machine learning models, semantic networks, adaptive systems, artificial neural networks, convolutional neural networks, and other forms of knowledge processing systems are disclosed. An ensemble machine learning system is coupled to a graph module storing a graph structure, wherein a collection of entities and the relationships between those entities forms nodes and connection arcs between the various nodes. A hotfile module and hotfile propagation engine coordinate with the graph module or may be subsumed within the graph module, and implement the various hot file functionality generated by the machine learning systems.
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公开(公告)号：US20230208852A1
公开(公告)日：2023-06-29
申请号：US18118423
申请日：2023-03-07
Applicant: BANK OF AMERICA CORPORATION
CPC classification number: H04L63/107 , H04W12/08 , H04W12/63
Abstract: Systems, computer program products, and methods are described herein for intrusion detection using resource activity analysis. The present invention is configured to receive, from a computing device of a user, an indication that the user has accessed a resource allocation portfolio of a customer; determine a geographic information of the user; retrieve a geographic information of the customer; determine that the geographic information of the user does not match the geographic information of the customer; determine an exposure level associated with the user access of the resource allocation portfolio of the customer; determine that the exposure level is greater than a predetermined threshold; and automatically trigger a transmission of a notification to a computing device of an administrator indicating that the exposure level associated with the user access of the resource allocation portfolio of the customer is greater than the predetermined threshold.
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公开(公告)号：US11563744B2
公开(公告)日：2023-01-24
申请号：US17181608
申请日：2021-02-22
Applicant: BANK OF AMERICA CORPORATION
Inventor： Scott Anderson Sims , Jeffrey Brian Bashore , Jeffrey David Finocchiaro , Craig Douglas Widmann
Abstract: Systems, computer program products, and methods are described herein for detection and classification of intrusion using machine learning techniques. The present invention is configured to electronically receive, from a computing device of a user, an indication that the user has initiated a first resource interaction; retrieve information associated with the first resource interaction, wherein the information comprises at least one or more parameters associated with the first resource interaction; initiate a machine learning model on the one or more parameters associated with the first resource interaction; and classify, using the machine learning model, the first resource interaction into one or more classes, wherein the one or more classes comprises one or more access types.
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公开(公告)号：US11816198B2
公开(公告)日：2023-11-14
申请号：US17223079
申请日：2021-04-06
Applicant: BANK OF AMERICA CORPORATION
Inventor： Scott Anderson Sims , Sai Kishan Alapati , Jeffrey Brian Bashore , Michael Joseph Carroll , Brian H. Corr , Andrew Dongho Kim , Holly J. Martinez , Aron Megyeri , Ronnie Joe Morris, Jr. , Elliot Piatetsky , Jennifer Quillen , Tracy R. Regehr , Dharmender Kumar Satija , Craig Douglas Widmann
IPC: G06F21/32 , H04L9/40 , G06V10/147 , G06V40/16 , H04N23/90
CPC classification number: G06F21/32 , G06V10/147 , G06V40/168 , G06V40/172 , H04L63/0861 , H04N23/90 , G06F2221/2111
Abstract: The present invention is generally related to systems and methods for providing an improved authentication and verification system through the use of compiled user data and user location or traffic data from multiple channels of input. Multiple devices may be utilized by the system in order to receive and process data to authenticate user identities and verify the validity of account activity.
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公开(公告)号：US20230089968A1
公开(公告)日：2023-03-23
申请号：US18072526
申请日：2022-11-30
Applicant: BANK OF AMERICA CORPORATION
Inventor： Scott Anderson Sims , Jeffrey Brian Bashore , Jeffrey David Finocchiaro , Craig Douglas Widmann
Abstract: Systems, computer program products, and methods are described herein for detection and classification of intrusion using machine learning techniques. The present invention is configured to electronically receive, from a computing device of a user, an indication that the user has initiated a first resource interaction; retrieve information associated with the first resource interaction, wherein the information comprises at least one or more parameters associated with the first resource interaction; initiate a machine learning model on the one or more parameters associated with the first resource interaction; and classify, using the machine learning model, the first resource interaction into one or more classes, wherein the one or more classes comprises one or more access types.
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Patent Agency Ranking
公开(公告)号：US20220318348A1
公开(公告)日：2022-10-06
申请号：US17223079
申请日：2021-04-06
Applicant: BANK OF AMERICA CORPORATION
Inventor： Scott Anderson Sims , Sai Kishan Alapati , Jeffrey Brian Bashore , Michael Joseph Carroll , Brian H. Corr , Andrew DongHo Kim , Holly J. Martinez , Aron Megyeri , Ronnie Joe Morris, JR. , Elliot Piatetsky , Jennifer Quillen , Tracy R. Regehr , Dharmender Kumar Satija , Craig Douglas Widmann
Abstract: The present invention is generally related to systems and methods for providing an improved authentication and verification system through the use of compiled user data and user location or traffic data from multiple channels of input. Multiple devices may be utilized by the system in order to receive and process data to authenticate user identities and verify the validity of account activity.
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公开(公告)号：US11949686B2
公开(公告)日：2024-04-02
申请号：US18118423
申请日：2023-03-07
Applicant: BANK OF AMERICA CORPORATION
CPC classification number: H04L63/107 , G06F21/32 , G06F21/6245 , H04W12/08 , H04W12/63
Abstract: Systems, computer program products, and methods are described herein for intrusion detection using resource activity analysis. The present invention is configured to receive, from a computing device of a user, an indication that the user has accessed a resource allocation portfolio of a customer; determine a geographic information of the user; retrieve a geographic information of the customer; determine that the geographic information of the user does not match the geographic information of the customer; determine an exposure level associated with the user access of the resource allocation portfolio of the customer; determine that the exposure level is greater than a predetermined threshold; and automatically trigger a transmission of a notification to a computing device of an administrator indicating that the exposure level associated with the user access of the resource allocation portfolio of the customer is greater than the predetermined threshold.
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公开(公告)号：US20220272093A1
公开(公告)日：2022-08-25
申请号：US17181608
申请日：2021-02-22
Applicant: BANK OF AMERICA CORPORATION
Inventor： Scott Anderson Sims , Jeffrey Brian Bashore , Jeffrey David Finocchiaro , Craig Douglas Widmann
Abstract: Systems, computer program products, and methods are described herein for detection and classification of intrusion using machine learning techniques. The present invention is configured to electronically receive, from a computing device of a user, an indication that the user has initiated a first resource interaction; retrieve information associated with the first resource interaction, wherein the information comprises at least one or more parameters associated with the first resource interaction; initiate a machine learning model on the one or more parameters associated with the first resource interaction; and classify, using the machine learning model, the first resource interaction into one or more classes, wherein the one or more classes comprises one or more access types.
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公开(公告)号：US20180165681A1
公开(公告)日：2018-06-14
申请号：US15376252
申请日：2016-12-12
Applicant: Bank of America Corporation
Inventor： Aron Megyeri , Craig Douglas Widmann , Eduardo J. Ramirez , Amijo Bearley , Robert D. Jones
CPC classification number: G06Q20/4016 , G06Q20/1085 , G06Q20/405
Abstract: Aspects of the disclosure relate to detection of unauthorized usage in debit card transactions using a transaction management computing platform and an analytics computing platform. A computing platform may monitor a plurality of transactions at an automated teller machine. Subsequently, the computing platform may identify at least one unusual activity in the plurality of transactions at the automated teller machine. In response to identifying the at least one unusual activity in the plurality of transactions, the computing may analyze each account corresponding to the plurality of transactions to identify a common point of purchase for a subset of accounts. Thereafter, the computing platform may flag the subset of accounts for unauthorized usage.
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公开(公告)号：US11985136B2
公开(公告)日：2024-05-14
申请号：US18072526
申请日：2022-11-30
Applicant: BANK OF AMERICA CORPORATION
Inventor： Scott Anderson Sims , Jeffrey Brian Bashore , Jeffrey David Finocchiaro , Craig Douglas Widmann
CPC classification number: H04L63/102 , G06F18/24 , G06N20/00 , H04L63/1441 , H04L63/20
Abstract: Systems, computer program products, and methods are described herein for detection and classification of intrusion using machine learning techniques. The present invention is configured to electronically receive, from a computing device of a user, an indication that the user has initiated a first resource interaction; retrieve information associated with the first resource interaction, wherein the information comprises at least one or more parameters associated with the first resource interaction; initiate a machine learning model on the one or more parameters associated with the first resource interaction; and classify, using the machine learning model, the first resource interaction into one or more classes, wherein the one or more classes comprises one or more access types.
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