-
41.发明申请公开(公告)号：US20200167786A1
公开(公告)日：2020-05-28
申请号：US16200065
申请日：2018-11-26
Applicant: Bank of America Corporation
Inventor： Eren Kursun
IPC: G06Q20/40 , G06F16/901 , H04L29/08
Abstract: Embodiments of the present invention provide a system for anomaly detection and remediation based on dynamic directed and undirected graph network flow analysis. Information for multiple accounts is extracted to generate a plurality of dynamic directed and undirected graphs made up of multiple nodes and edges. The nodes represent at least one of the multiple accounts, and each edge represents at least an association or transfer between two nodes. A custom entropy and divergence value is determined for each pair of nodes linked by an edge, as compared to similar or related nodes and edges. A nodal set of a first node and multiple additional nodes linked to the first node by an edge is identified as having a custom entropy and divergence value associated with anomalous directional flow. In response, a remediation action is executed with respect to one or more accounts associated with the nodal set.
-
42.发明申请公开(公告)号：US20200167784A1
公开(公告)日：2020-05-28
申请号：US16200027
申请日：2018-11-26
Applicant: Bank of America Corporation
Inventor： Eren Kursun
Abstract: Embodiments of the present invention provide a system for active malfeasance examination and detection based on dynamic graph network flow analysis. The system is typically configured for extracting resource distribution information for a plurality of resource pools, generating a dynamic graph comprising a plurality of nodes and a plurality of edges, calculating custom reputation values for each of the plurality of nodes, identifying a first node of the plurality of nodes comprising a custom reputation value associated with a malfeasance, identifying a user associated with the first node and identify user information associated with the user, communicating a resource distribution request to the user based on the identified user information, receiving an acceptance of the resource distribution request from a computing device of the user, and executing one or more remediation actions on one or more resource pools of the user.
-
公开(公告)号：US20190372974A1
公开(公告)日：2019-12-05
申请号：US15995830
申请日：2018-06-01
Applicant: BANK OF AMERICA CORPORATION
Inventor： Dharmender Kumar Satija , Eren Kursun , Andrew DongHo Kim , Scott Anderson Sims , Craig D. Widmann
IPC: H04L29/06
Abstract: A system and methods for alternate user communication routing are described. Unauthorized users are identified and alternate treatments are provided in order to deter unauthorized access and create opportunities for data collection. The use of a varied set of alternate treatments provides an enhanced view of unauthorized user behavior and an increased ability to track future unauthorized user actions by recording various user identity/communication characteristics specific to known unauthorized users. Alternate treatments may be provided randomly based on a set of alternate treatments previously provided to a specific user, or may be varied based on an identified group of unauthorized users presumed to be acting in concert.
-
公开(公告)号：US20190289025A1
公开(公告)日：2019-09-19
申请号：US15921395
申请日：2018-03-14
Applicant: BANK OF AMERICA CORPORATION
Inventor： Eren Kursun , Craig D. Widmann , Dharmender Kumar Satija , Andrew DongHo Kim , Shawn Parris Bench , Kolt Arthur Bell , Scott Anderson Sims
Abstract: The invention describes a system and method employing machine learning and artificial intelligence engines to monitor data streams in real-time across multiple channels in order to detect anomalies and generate prioritized alerts. In particular, the invention may continuously collect data across multiple channels. The obtained data may be compared with reference data to continuously update a confidence level associated with the user, channel, entity, or other identifying factor. Based on the confidence level, profile the user to detect any inconsistencies in the data collected over time and generate an alert to the user in question and potentially to other downstream users or entities. In this way, the invention not only provides a way to detect anomalies in a cross-channel fashion, but also creates a mechanism for feedback wherein the system may incorporate user feedback to resolve alerts and detected anomalies.
-
45.发明申请公开(公告)号：US20190244306A1
公开(公告)日：2019-08-08
申请号：US15889016
申请日：2018-02-05
Applicant: BANK OF AMERICA CORPORATION
Inventor： Eren Kursun
CPC classification number: G06Q40/12 , H04L9/0637 , H04L2209/38
Abstract: Embodiments of the invention are directed to a decentralized block chain regulation architecture. The invention utilizes the collective nature of block chain communication to perform key regulatory and control functions. Instead of relying on a centralized regulatory source, the present system allows the block chain structures themselves to simultaneously function as both regulated and regulatory chains for one another to form an interconnected network of decentralized, regulatory chains. Further, the system allows for control of non-compliant block chains, wherein regulatory chains may issue commands to the non-compliant chains, rewrite data, overwrite an incorrect consensus, or deactivate a chain and remove it from a block chain environment before propagation of an error.
-
Patent Agency Ranking
46.发明授权公开(公告)号：US11531883B2
公开(公告)日：2022-12-20
申请号：US16537882
申请日：2019-08-12
Applicant: BANK OF AMERICA CORPORATION
Inventor： Eren Kursun
Abstract: Embodiments of the present invention provide an improvement to convention machine model training techniques by providing an innovative system, method and computer program product for the generation of synthetic data using an iterative process that incorporates multiple machine learning models and neural network approaches. A collaborative system for receiving data and continuously analyzing the data to determine emerging patterns is provided. Common characteristics of data from the identified emerging patterns are broadened in scope and used to generate a synthetic data set using a generative neural network approach. The resulting synthetic data set is narrowed based on analysis of the synthetic data as compared to the detected emerging patterns, and can then be used to further train one or more machine learning models for further pattern detection.
-
公开(公告)号：US11475363B2
公开(公告)日：2022-10-18
申请号：US16706522
申请日：2019-12-06
Applicant: BANK OF AMERICA CORPORATION
Inventor： Eren Kursun
Abstract: A system for machine learning data pattern recognition for misappropriation identification is provided. The system comprises a controller configured for learning and identifying misappropriation data patterns. The controller is further configured to: receive interaction data associated with a received interaction, the interaction data comprising one or more features, wherein the one or more features are measurable characteristics of the interaction; calculate a feed-forward scoring of an input of the interaction data comprising one or more features; generate a relevance visualization map of the one or more features of the feed-forward scoring; match, using a machine learning model, the relevance visualization map of the received interaction to a visualization pattern associated with a known labeled misappropriation type, wherein the machine learning model is trained with known misappropriation data patterns; and display the relevance visualization map and the visualization pattern from the known misappropriation patterns with the known labeled misappropriation type.
-
公开(公告)号：US11336646B2
公开(公告)日：2022-05-17
申请号：US16915371
申请日：2020-06-29
Applicant: BANK OF AMERICA CORPORATION
Inventor： Dharmender Kumar Satija , Eren Kursun , Andrew DongHo Kim , Scott Anderson Sims , Craig D. Widmann
IPC: H04L29/06
Abstract: A system and methods for alternate user communication routing are described. Unauthorized users are identified and alternate treatments are provided in order to deter unauthorized access and create opportunities for data collection. The use of a varied set of alternate treatments provides an enhanced view of unauthorized user behavior and an increased ability to track future unauthorized user actions by recording various user identity/communication characteristics specific to known unauthorized users. Alternate treatments may be provided randomly based on a set of alternate treatments previously provided to a specific user, or may be varied based on an identified group of unauthorized users presumed to be acting in concert.
-
49.发明授权公开(公告)号：US11275819B2
公开(公告)日：2022-03-15
申请号：US16210427
申请日：2018-12-05
Applicant: Bank of America Corporation
Inventor： Eren Kursun
IPC: G06F21/32 , G06F21/57 , G06F16/9535 , G06N3/08 , G06K9/00
Abstract: Embodiments of the present invention provide a system for generative adversarial network training and feature extraction for biometric authentication. The system collects electronic biometric data of a user from one or more data sources, and stores the collected electronic biometric data as a biometric user account for the user in a personal NoSQL database library associated with the user. A generative adversarial neural network system then determines improved biometric feature selection and improved model refinements for existing biometric authentication models based on the biometric account for the user in the personal library associated with the user. The system can then determine user exposure levels for different authentication channels, including certain biometric authentication channels. A custom adversarial strategy for general adversarial network attacks is then established based on the user exposure levels to generate a biometric authentication process that is more accurate and secure.
-
50.发明授权公开(公告)号：US11270206B2
公开(公告)日：2022-03-08
申请号：US16197197
申请日：2018-11-20
Applicant: BANK OF AMERICA CORPORATION
Inventor： Eren Kursun
Abstract: A system for reconfiguring neural network architecture responsive to a system state is provided. A controller for modifying a neural network learning engine is configured to monitor a data stream having a data pattern by comparing the data pattern to a trained data pattern; identify a change in the data pattern of the data stream; determine a state of the neural network learning engine, the state defining one or more neural network parameters for monitoring the data stream with the neural network learning engine; and in response to identifying the change in the data pattern and determining the state, reconfigure an architectural configuration of the neural network learning engine by modifying the one or more neural network parameters.
-
-
-
-
-
-
-
-
-
Search Results
128
records
(took 0.018 seconds)
