公开(公告)号：US20210334695A1

公开(公告)日：2021-10-28

申请号：US16859684

申请日：2020-04-27

Applicant: BANK OF AMERICA CORPORATION

Inventor： Utkarsh Raj ,  Maharaj Mukherjee

IPC: G06N20/00

Abstract: A model correction tool automatically detects and corrects model drift in a model for a machine learning application. To detect drift, the tool continuously monitors input data, outputs, and/or technical resources (e.g., processor, memory, network, and input/output resources) used to generate outputs. The tool analyzes changes to input data, outputs, and/or resource usage to determine when drift has occurred. When drift is determined to be occurring, the tool retrains a model for a machine learning application.

公开(公告)号：US12217190B2

公开(公告)日：2025-02-04

申请号：US17166087

申请日：2021-02-03

Applicant: Bank of America Corporation

Inventor： Maharaj Mukherjee ,  Utkarsh Raj

IPC: G06N20/00 ,  G06N5/022

Abstract: Aspects of the disclosure relate to machine learning models and knowledge graphs. A computing platform may receive event processing data. Using a machine learning mode, the computing platform may identify k nearest data points corresponding to the event processing data. Using a knowledge graph, the computing platform may identify k nearest data nodes corresponding to the event processing data. The computing platform may generate first weighted relative distances between the event processing data and the k nearest data points, and second weighted relative distances between the event processing data and the k nearest data nodes. Based on the weighted relative distances, the computing platform may identify a data cluster for the event processing data. The computing platform may send, based on the identified data cluster, event processing information and one or more commands directing an enterprise computing device to display the event processing information.

公开(公告)号：US20240385917A1

公开(公告)日：2024-11-21

申请号：US18198367

申请日：2023-05-17

Applicant: Bank of America Corporation

Inventor： Maharaj Mukherjee ,  Utkarsh Raj ,  Colin Murphy ,  Elvis Nyamwange ,  Suman Roy Choudhury ,  Vijay Kumar Yarabolu ,  Carl Benda

IPC: G06F11/00 ,  G06V10/74 ,  G06V10/764

Abstract: A computing platform may train a hybrid deep learning model, including a CNN and RNN, to predict system failure for a system based on telemetry state images and transitions between the telemetry state images. The computing platform may receive initial telemetry data, and may generate an initial telemetry state image. The computing platform may receive additional telemetry data, and may generate an additional telemetry state image. The computing platform may classify, using the CNN and based on historical telemetry state images, the initial telemetry state image and the additional telemetry state image. The computing platform may identify, using the RNN and based on the classified telemetry state images and transitions between the classified telemetry state images, a matching pattern. The computing platform may identify, using the identified matching pattern, a likelihood of failure for the system, and may cause modification of operations at the system to prevent a predicted failure.

公开(公告)号：US20240385612A1

公开(公告)日：2024-11-21

申请号：US18198375

申请日：2023-05-17

Applicant: Bank of America Corporation

Inventor： Maharaj Mukherjee ,  Utkarsh Raj ,  Colin Murphy ,  Elvis Nyamwange ,  Carl Benda ,  Suman Roy Choudhury ,  Vijay Kumar Yarabolu

IPC: G05B23/02

Abstract: A computing platform may configure a rules-based state machine to predict system failure for a system based on telemetry state images and transitions between the telemetry state images. The computing platform may receive initial telemetry data. The computing platform may generate, based on the initial telemetry data, an initial telemetry state image. The computing platform may receive additional telemetry data, and may generate, based on the additional telemetry data, an additional telemetry state image. The computing platform may compare a pattern, corresponding to the initial telemetry state image, the additional telemetry state image, and a corresponding transition, to historical patterns to identify a match. The computing platform may identify, using the identified matching pattern, a likelihood of failure for the system, and may send, based on the likelihood of failure for the system, preemptive resolution commands causing modification of operations at the system to prevent a predicted failure.

公开(公告)号：US20240232891A1

公开(公告)日：2024-07-11

申请号：US18094447

申请日：2023-01-09

Applicant: Bank of America Corporation

Inventor： Yogi Ahuja ,  Mardochee Macxis ,  Monika Kapur ,  Albena Fairchild ,  Utkarsh Raj

IPC: G06Q20/40 ,  G06Q20/38

CPC classification number: G06Q20/4016 ,  G06Q20/389 ,  G06Q20/405

Abstract: Systems and methods for fraud prevention in a blockchain-based digital transactional system with machine-learning (ML)-powered rule generation are provided. Methods may include creating a distributed ledger in which digital blocks may include foundational transactional parameter rules, and digital blocks may include historical transactional data. Methods may include hosting ML models on the nodes, running each ML model to generate new transactional parameter rules, and adding the new transactional parameter rule as a digital block on the distributed ledger in response to a consensus. Methods may include receiving additional transactional data, running each ML model to generate a score representing a probability that the additional transactional data is associated with fraudulent activity, and triggering an alert for an account associated with the additional transactional data in response to a consensus across the plurality of ML models that the score exceeds a predetermined threshold score.

公开(公告)号：US20240177298A1

公开(公告)日：2024-05-30

申请号：US18522864

申请日：2023-11-29

Applicant: BANK OF AMERICA CORPORATION

Inventor： Maharaj Mukherjee ,  Carl M. Benda ,  Elvis Nyamwange ,  Utkarsh Raj ,  Suman Roy Choudhury ,  Vidya Srikanth ,  Colin Murphy

IPC: G06T7/00

CPC classification number: G06T7/001 ,  G06T2207/30141

Abstract: Systems, computer program products, and methods are described herein for analyzing system health of individual electronic components using image mapping. The method includes receiving a component health image for a component based on an execution of a process. The method also includes comparing the component health image based on the execution of the process to previous component health image(s) for the component based on one or more previous executions of the process The method further includes determining a component health image similarity score based on the comparison of the component health image to the one or more previous component health images for the component. The method still further includes determining a component health action based on the component health image similarity score. The component health action includes causing a transmission of an alert in an instance in which the component health image similarity score is outside of a threshold range.

公开(公告)号：US20240177022A1

公开(公告)日：2024-05-30

申请号：US18522872

申请日：2023-11-29

Applicant: BANK OF AMERICA CORPORATION

Inventor： Maharaj Mukherjee ,  Carl M. Benda ,  Elvis Nyamwange ,  Utkarsh Raj ,  Suman Roy Choudhury ,  Vidya Srikanth ,  Colin Murphy

IPC: G06N5/022 ,  G06N20/00

CPC classification number: G06N5/022 ,  G06N20/00

Abstract: Systems, computer program products, and methods are described herein for analyzing system health of individual electronic components using component relational graphs. The method includes receiving a process request. The process request is a request to execute a process. The method also includes determining one or more components of the system used during the process. The method further includes generating a component knowledge graph for the process. The component knowledge graph includes one or more nodes corresponding to each of one or more components used during the process. The method still further includes determining a component health rating for each of the one or more components used in the process.

公开(公告)号：US11995075B2

公开(公告)日：2024-05-28

申请号：US17557683

申请日：2021-12-21

Applicant: Bank of America Corporation

Inventor： Maharaj Mukherjee ,  Utkarsh Raj ,  Carl M. Benda ,  Elvis Nyamwange ,  Suman Roy Choudhury

IPC: G06F16/2452 ,  G06F16/21 ,  G06F16/242 ,  G06F16/2453 ,  G06F16/248 ,  G06F16/25 ,  G06F40/205

CPC classification number: G06F16/2452 ,  G06F16/214 ,  G06F16/2425 ,  G06F16/2433 ,  G06F16/2448 ,  G06F16/24534 ,  G06F16/248 ,  G06F16/258 ,  G06F40/205

Abstract: Aspects of the disclosure relate to transliteration of machine interpretable languages. A computing platform may receive a query formatted in a first format for execution on a first database. The computing platform may translate the query to a second format for execution on a second database by: 1) extracting non-essential portions of the query from the query, and replacing the non-essential portions of the query with pointers to create a query key; 2) storing, along with their corresponding pointers, the non-essential portions of the query as query parameters; 3) executing a lookup function on a query library to identify a translated query corresponding to the query key and including the corresponding pointers; and 4) updating the translated query to include the query parameters based on the corresponding pointers to create an output query. The computing platform may execute the output query on the second database.

公开(公告)号：US20240160513A1

公开(公告)日：2024-05-16

申请号：US18508449

申请日：2023-11-14

Applicant: BANK OF AMERICA CORPORATION

Inventor： Maharaj Mukherjee ,  Carl M. Benda ,  Elvis Nyamwange ,  Utkarsh Raj ,  Suman Roy Choudhury ,  Vidya Srikanth ,  Colin Murphy

IPC: G06F11/07 ,  G06F11/00 ,  G06F11/34 ,  G06T7/00 ,  G06V10/40

CPC classification number: G06F11/0766 ,  G06F11/008 ,  G06F11/3433 ,  G06T7/0004 ,  G06V10/40 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: Systems, computer program products, and methods are described herein for real-time overload detection using image processing analysis. The present disclosure is configured to receive a first set of images associated with a device, wherein the one or more images are associated with a resiliency status of the device; deploy, using a machine learning (ML) subsystem, a trained ML model on the first set of images of the device; determine, using the trained ML model, a change in the resiliency status of the device based on the first set of images; and generate a notification indicating the change in the resiliency status of the device; and transmit control signals configured to cause a first user input device to display the notification.

公开(公告)号：US20240160422A1

公开(公告)日：2024-05-16

申请号：US18055558

申请日：2022-11-15

Applicant: Bank of America Corporation

Inventor： Utkarsh Raj ,  Paul Jacob Abernathy ,  Vijaya Rudraraju ,  William Cruise

IPC: G06F8/51

CPC classification number: G06F8/51

Abstract: Various aspects of the disclosure relate to bi-directional hybrid-feedback driven self-healing and self-scaling language transpiler system may include bi-directional hopping to support multi language transpilation, automatic conversion of a mapping into a transformation specification, a hybrid feedback mechanism to update the transformation mappings, automatic scaling and/or creation of enterprise wide mapping and token (e.g., grammar) vocabulary, and/or a self-healing and/or corrective translation capability to perform automatic correction of any partial transpilations over time from a learned mapping.