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    SYSTEM FOR DYNAMIC, SECURE, TOKEN-BASED SNAPSHOT GENERATION
    2.
    发明申请
    SYSTEM FOR DYNAMIC, SECURE, TOKEN-BASED SNAPSHOT GENERATION 有权

    公开(公告)号：US20250062908A1

    公开(公告)日：2025-02-20

    申请号：US18234254

    申请日：2023-08-15

    Applicant: BANK OF AMERICA CORPORATION

    Inventor： Elvis Nyamwange ,  Sailesh Vezzu ,  Amer Ali ,  Rahul Yaksh ,  Hari Vuppala ,  Pratap Dande ,  Brian Neal Jacobson ,  Erik Dahl ,  Rahul Shashidhar Phadnis

    IPC: H04L9/32 ,  G06F16/11

    Abstract: Systems, computer program products, and methods are described herein for dynamic, secure, token-based snapshot generation. The present disclosure is configured to receive, via an alternative access point, a user request to receive a snapshot of one or more resource repositories associated with a user; generate, using a token generator, a token based on at least the user request; authenticate, using an authentication subsystem, the user using the token to confirm legitimacy of the user request; generate, using a snapshot generator, the snapshot of the one or more resource repositories based on at least confirming the legitimacy of the user request, wherein the snapshot is generated based on pre-defined user preferences; embed, using a digital signature subsystem, the snapshot with a digital signature serving as an attestation; and display the snapshot on the user input device.

    INTELLIGENT VIRTUAL ASSIST FOR RESOURCE ADVANCEMENT
    6.
    发明申请
    INTELLIGENT VIRTUAL ASSIST FOR RESOURCE ADVANCEMENT 有权

    公开(公告)号：US20250103848A1

    公开(公告)日：2025-03-27

    申请号：US18372394

    申请日：2023-09-25

    Applicant: BANK OF AMERICA CORPORATION

    Inventor： Pratap Dande ,  Amer Ali ,  Erik Dahl ,  Brian Neal Jacobson ,  Elvis Nyamwange ,  Rahul Shashidhar Phadnis ,  Sailesh Vezzu ,  Hari Vuppala ,  Rahul Yaksh

    IPC: G06N3/006

    Abstract: Intelligent autonomous software (i.e., a “bot”) configured to compile and present resource advancement requestor-specific dashboards that summarize the results of analysis of resource advancement data related to the resource advancement request/requestor. In compiling a dashboard presentation for a specific resource advancement requestor, the intelligent autonomous software executes a set of predetermined queries directed to a database that stores the results of the data analysis. In response to receiving the responses to the queries, the intelligent autonomous software is configured to identify data omissions/anomalies in the data that will prevent approval of the resource advancement request and identify, and in some instances generate, corrective action(s) that will rectify the data omissions/anomalies. Subsequently, a resource advancement requestor-specific dashboard presentation is generated and communicated to the user that (i) summarizes the data responsive to the predetermined queries, and (ii) highlights the data omissions/anomalies and the corrective actions necessary to rectify the data omissions/anomalies.

    AUTOMATION OF FRAUD DETECTION WITH MACHINE LEARNING UTILIZING PUBLICLY AVAILABLE FORMS
    7.
    发明申请
    AUTOMATION OF FRAUD DETECTION WITH MACHINE LEARNING UTILIZING PUBLICLY AVAILABLE FORMS 有权

    公开(公告)号：US20250061469A1

    公开(公告)日：2025-02-20

    申请号：US18234911

    申请日：2023-08-17

    Applicant: Bank of America Corporation

    Inventor： Rahul Yaksh ,  Amer Ali ,  Brian Jacobson ,  Elvis Nyamwange ,  Erik Dahl ,  Hari Vuppala ,  Pratap Dande ,  Rahul Phadnis ,  Sailesh Vezzu

    IPC: G06Q30/018 ,  G06V30/412

    Abstract: Systems and methods for alerting an organization about activity that may be fraudulent. Systems may include a computer processor, a storage module, a cleaning module, a preprocessing module, a features extraction module, and a machine learning module. The computer processor may be configured to run a fraud detection engine by collecting publicly available electronic forms every 36 hours, using the modules to store the forms, clean the data, preprocess the data, and run a machine learning model to extract features and to determine if a threshold indicating a risk of fraud has been exceeded. The machine learning models include a liquid, solvency, and profitability ratio classification model, a disclosure classification model, a sentiment analysis model, an anomaly detection classification model, an ownership analysis classification model, and an ESG disclosure classification model. When exceeding a threshold, the computer processor may notify an administrator of the exceeded threshold's identity.

    Multi-Computer System for Fail-Safe Event Processing
    9.
    发明公开
    Multi-Computer System for Fail-Safe Event Processing 审中-公开

    公开(公告)号：US20240193680A1

    公开(公告)日：2024-06-13

    申请号：US18076710

    申请日：2022-12-07

    Applicant: Bank of America Corporation

    Inventor： Pratap Dande ,  Erik Dahl ,  Rahul Yaksh ,  Tileshia Brenda Alford ,  Steven Allan Reich ,  Vishwanath Prasad Karra ,  Sailesh Vezzu

    IPC: G06Q40/03

    CPC classification number: G06Q40/03

    Abstract: Arrangements for providing fail-safe event processing functions are provided. In some aspects, an account may be generated and a first account number associated with a payment device of the account may be generated. The first account number may be transmitted or sent to the user. A second account number, different from the first account number, may be generated and stored by the enterprise organization in an inactive state. A user may request recurring payments with one or more vendors and may provide the first account number for use in processing the payments. An issue may be detected with the first account number or associated payment device. If a creditworthiness score meets or exceeds a threshold, the second account number may be activated and used (e.g., by the enterprise organization) to process recurring payments that may otherwise have lapsed due to the compromise of the first account number or payment device.

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