知搜-全球专利检索

  1. Login
  2. Sign Up

Search Results

88 records (took 0.026 seconds)

    INTELLIGENT VIRTUAL ASSIST FOR RESOURCE ADVANCEMENT
    1.
    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
    2.
    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.

    System and method for transpilation of machine interpretable languages
    4.
    发明授权
    System and method for transpilation of machine interpretable languages 有权

    公开(公告)号：US12147422B2

    公开(公告)日：2024-11-19

    申请号：US17557208

    申请日：2021-12-21

    Applicant: Bank of America Corporation

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

    IPC: G06F16/24 ,  G06F16/21 ,  G06F16/242 ,  G06F16/2452 ,  G06F16/2453 ,  G06F16/248 ,  G06F16/25 ,  G06F40/205

    Abstract: Aspects of the disclosure relate to transliteration of machine interpretable languages. A computing platform may train a machine learning model using source syntax trees and target dialect syntax trees, which may configure the model to output source dialect keys and their corresponding target dialect queries. The computing platform may execute the corresponding target dialect queries to identify whether they are valid. For a valid target dialect query, the computing platform may store the valid target dialect query and first source dialect keys corresponding to the valid target dialect query in a lookup table. For an invalid target dialect query resulting in error, the computing platform may: 1) identify a cause of the error; 2) generate a transliteration rule to correct the error; and 3) store, in the lookup table, the invalid target dialect query, second source dialect keys corresponding to the invalid target dialect query, and the transliteration rule.

    USER-SIDE NON-FUNGIBLE TOKEN STORAGE USING SUPER NON-VOLATILE RANDOM ACCESS MEMORY
    9.
    发明公开
    USER-SIDE NON-FUNGIBLE TOKEN STORAGE USING SUPER NON-VOLATILE RANDOM ACCESS MEMORY 审中-公开

    公开(公告)号：US20240029056A1

    公开(公告)日：2024-01-25

    申请号：US17868235

    申请日：2022-07-19

    Applicant: BANK OF AMERICA CORPORATION

    Inventor： Elvis Nyamwange

    IPC: G06Q20/36 ,  G06F3/06

    CPC classification number: G06Q20/3678 ,  G06F3/0679 ,  G06F3/0631 ,  G06F3/0604 ,  G06Q2220/00

    Abstract: A system for leveraging local/user-side resources (i.e., memory) to store Non-Fungible Tokens (NFTs) and conduct NFT-related computational processes required for generating/minting or exchanging an NFT. The local/user device is equipped with super Non-Volatile Random Access Memory (NVRAM), which operates in accordance with a resource-sharing protocol, such as Network Block Device (NBD) protocol or the like. The resource-sharing protocol is registered with the user's NFT digital wallet, which is in communication with the distributed trust computing networks and, thus links the local/user-side resources (i.e., NVRAM) with the distributed trust computing network for resource sharing capabilities.

Patent Agency Ranking