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    SYSTEMS AND METHODS FOR MACHINE LEARNING BASED EXECUTION OF ACTIONS BASED ON CALENDAR EVENT DATA
    12.
    发明公开
    SYSTEMS AND METHODS FOR MACHINE LEARNING BASED EXECUTION OF ACTIONS BASED ON CALENDAR EVENT DATA 审中-公开

    公开(公告)号：US20240169324A1

    公开(公告)日：2024-05-23

    申请号：US18057446

    申请日：2022-11-21

    申请人： Capital One Services, LLC

    发明人： Joshua EDWARDS ,  Jason ZWIERZYNSKI ,  Abhay DONTHI ,  Sara Rose BRODSKY ,  Jennifer KWOK ,  Tania Cruz MORALES

    IPC分类号： G06Q10/10

    CPC分类号： G06Q10/1097

    摘要： A method for executing actions based on event data using machine learning is disclosed. The method comprises: receiving occasion data associated with a user; analyzing, using a trained machine learning model, the occasion data to identify an occasion associated with a first classification, wherein the trained machine learning model has been trained based on (i) training occasion data that includes information regarding one or more occasions associated with the training occasion data and (ii) training classification data that includes a prior classification for each of the occasions, to learn relationships between the training occasion data and the training classification data, such that the trained machine learning model is configured to use the learned relationships to identify an occasion associated with a first classification in response to input of the occasion data; determining an action based on the occasion associated with the first classification; and automatically executing the action.

    MACHINE LEARNING FOR DETECTING AND MODIFYING FAULTY CONTROLS
    14.
    发明公开
    MACHINE LEARNING FOR DETECTING AND MODIFYING FAULTY CONTROLS 审中-公开

    公开(公告)号：US20240168472A1

    公开(公告)日：2024-05-23

    申请号：US18056851

    申请日：2022-11-18

    申请人： Capital One Services, LLC

    发明人： Joshua EDWARDS ,  Jennifer KWOK ,  Albert HERGENROEDER ,  Tyler MAIMAN ,  Sarah Jane CUNNINGHAM

    IPC分类号： G05B23/02

    CPC分类号： G05B23/0272 ,  G05B23/0281

    摘要： In some aspects, a computing system may use machine learning to determine whether a control is faulty or generate recommendations to make a modification to a control. may identify a portion of problematic computer code that implements the faulty control through the use of machine learning. A computing system may use machine learning to generate embeddings that map incident data and control data (e.g., computer-readable code of a control) to the same vector space. Further, a computing system may use a weighting mechanism that may be used to weight each sample used to train a machine learning model, which may allow a model to train more efficiently.

    SYSTEM AND METHOD FOR DETECTING AND PREVENTING AN IDENTITY THEFT ATTEMPT
    15.
    发明公开
    SYSTEM AND METHOD FOR DETECTING AND PREVENTING AN IDENTITY THEFT ATTEMPT 审中-公开

    公开(公告)号：US20240160708A1

    公开(公告)日：2024-05-16

    申请号：US17984499

    申请日：2022-11-10

    申请人： Capital One Services, LLC

    发明人： Dwij TRIVEDI ,  Abhay DONTHI ,  Salik SHAH ,  Jennifer KWOK ,  Leeyat Bracha TESSLER

    IPC分类号： G06F21/32

    CPC分类号： G06F21/32

    摘要： A system and method for detecting and prevent identity theft attempts, such as phishing, vishing or other similar attacks is disclosed. A smart device, such as a smartphone operates in tandem with a biometric sensor, such as is included in a wearable device like a smartwatch or fitness tracker. The wearable tracks certain biometric and/or physiological data that can be used to identify whether the user is in a stressed state. The smart device then accesses usage logs that may indicate whether the stressed state is justified, such as whether the user had a calendar appointment at that time, or whether the call was received from a known contact etc. Justifications reduce the likelihood that the user's stress is a result of an identity theft attempt, whereas lack of justification increases the likelihood. In the latter scenario, the user is notified not to divulge sensitive information.

    SYSTEMS AND METHODS FOR EXTERNAL ACCOUNT AUTHENTICATION
    16.
    发明公开
    SYSTEMS AND METHODS FOR EXTERNAL ACCOUNT AUTHENTICATION 审中-公开

    公开(公告)号：US20240135381A1

    公开(公告)日：2024-04-25

    申请号：US18049092

    申请日：2022-10-23

    申请人： Capital One Services, LLC

    发明人： Jennifer KWOK ,  Sara Rose BRODSKY ,  Jason ZWIERZYNSKI ,  Joshua EDWARDS ,  Abhay DONTHI ,  Tania Cruz MORALES

    IPC分类号： G06Q20/40 ,  G06Q20/38

    CPC分类号： G06Q20/4016 ,  G06Q20/382

    摘要： Systems and methods for external account authentication are disclosed herein. They include receiving a call to pair the external account with a secure account, extracting external data from the external account, the external data corresponding to external account content, providing user activity data from the secure account as an input to an authentication machine learning model, providing the external data as an input to the authentication machine learning model, the authentication machine learning model configured to output a certainty level that the external account is associated with a user of the secure account based on the external data and the activity data, receiving the certainty level from the authentication machine learning model, determining that the certainty level meets a certainty threshold, and pairing the external account with the secure account based on determining that the certainty level meets the certainty threshold.

    USING TRANSACTION DATA TO PREDICT VEHICLE DEPRECIATION AND PRESENT VALUE
    19.
    发明申请
    USING TRANSACTION DATA TO PREDICT VEHICLE DEPRECIATION AND PRESENT VALUE 有权

    公开(公告)号：US20210312511A1

    公开(公告)日：2021-10-07

    申请号：US16841825

    申请日：2020-04-07

    申请人： Capital One Services, LLC

    发明人： Viraj CHAUDHARY ,  Cruz VARGAS ,  Jennifer KWOK

    IPC分类号： G06Q30/02 ,  G06N20/00 ,  G06Q40/02

    摘要： Various embodiments are directed to a system or platform with machine learning capabilities configured to accurately predict in real-time a depreciation factor of a vehicle associated with a customer and further accurately predict a present value of the vehicle based at least in part on card transaction data associated with the customer. Based on one or more factors, such as a determination that the present value of the vehicle falls below a predefined threshold value, one or more auto financing products may be generated and provided to the customer by the system.