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    OPTIMIZING INTEREST ACCRUAL BETWEEN A USER'S FINANCIAL ACCOUNTS
    11.
    发明公开
    OPTIMIZING INTEREST ACCRUAL BETWEEN A USER'S FINANCIAL ACCOUNTS 审中-公开

    公开(公告)号：US20230206316A1

    公开(公告)日：2023-06-29

    申请号：US16783979

    申请日：2020-02-06

    Applicant: State Farm Mutual Automobile Insurance Company

    Inventor： Elizabeth Flowers ,  Puneit Dua ,  Alan Zwilling ,  Adam Mattingly ,  Melissa Attig ,  Reena Batra

    IPC: G06Q40/02 ,  G06Q30/02

    CPC classification number: G06Q40/02 ,  G06Q30/0205

    Abstract: Techniques are disclosed utilizing cognitive computing to improve banking experiences. A user's financial account(s) may be monitored to predict when a surplus of funds is unnecessarily present and for how long this will likely be the case. Once this is determined, techniques include automatically drafting funds from the account to another account having a higher interest rate where the funds may accrue more interest. The techniques also include predicting when an overdraft may occur and taking appropriate action when such a prediction is made. Predictions may be based upon different weighted inputs used in accordance with a predictive modeling system, which may attempt to predict for a particular user, location, and retailer, whether the user will spend an anticipated amount in excess of the user's current balance. If so, passive (e.g., notifications) and active (e.g., transferring cover funds) actions may be performed.

    IDENTIFYING FRAUDULENT INSTRUMENTS AND IDENTIFICATION
    13.
    发明申请
    IDENTIFYING FRAUDULENT INSTRUMENTS AND IDENTIFICATION 有权

    公开(公告)号：US20220122071A1

    公开(公告)日：2022-04-21

    申请号：US15465981

    申请日：2017-03-22

    Applicant: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY

    Inventor： Timothy Kramme ,  Elizabeth Flowers ,  Reena Batra ,  Miriam Valero ,  Puneit Dua ,  Shanna L. Phillips ,  Russell Ruestman ,  Bradley A. Craig

    IPC: G06Q20/40 ,  G06Q30/00

    Abstract: In a computer-implemented method, a digital image of a signed financial instrument or identification card may be received from a financial institution or merchant computing terminal. The digital image may be analyzed to identify a type of financial instrument or identification card, and an originating entity. Expected fields of the instrument or card may be determined based upon the type and the originating entity. The digital image may be analyzed to identify actual fields on the instrument or card, and it may be determined whether the expected fields match the actual fields to determine whether a fraudulent field exists on the signed financial instrument or identification card. If it is determined that no fraudulent field exists, additional operations may be performed to determine whether the instrument or card contains fraudulent characters or content.

    PREDICTING WHEN A USER IS IN NEED OF A LOAN AND NOTIFYING THE USER OF LOAN OFFERS
    15.
    发明申请
    PREDICTING WHEN A USER IS IN NEED OF A LOAN AND NOTIFYING THE USER OF LOAN OFFERS 有权

    公开(公告)号：US20210358030A1

    公开(公告)日：2021-11-18

    申请号：US15499089

    申请日：2017-04-27

    Applicant: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY

    Inventor： Elizabeth Flowers ,  Puneit Dua ,  Alan Zwilling ,  Adam Mattingly ,  Melissa Attig ,  Reena Batra

    IPC: G06Q40/02 ,  G06N7/00

    Abstract: Techniques are disclosed to determine when a user is in need of a loan and notifying the user of loan offers. With user permission or affirmative consent, user data may be monitored for several users, which is used to build a user profile for each user. The user profile may then be analyzed to determine whether a user will require a loan within a future time period. To do so, the user data may include data from various sources, which indicate the user's interactions and behaviors such as demographic data, data indicative of user shopping habits, online browsing, life events, or other relevant behaviors. This data may then be analyzed to predict a statistical likelihood that a user will need a loan. When this statistical likelihood is exceeded, a user may be preapproved for a loan and/or a targeted notification may be sent indicating offers for certain types of loans.

    CUSTOMIZING LOAN SPECIFICS ON A PER-USER BASIS
    16.
    发明申请
    CUSTOMIZING LOAN SPECIFICS ON A PER-USER BASIS 有权

    公开(公告)号：US20210142401A1

    公开(公告)日：2021-05-13

    申请号：US15499203

    申请日：2017-04-27

    Applicant: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY

    Inventor： Elizabeth Flowers ,  Puneit Dua ,  Alan Zwilling ,  Adam Mattingly ,  Melissa Attig ,  Reena Batra

    IPC: G06Q40/02 ,  G06F17/18

    Abstract: Techniques are disclosed to provide customized loans on a per-user basis. With user permission or affirmative consent, user data may be monitored for several users, which may be used to calculate initial loan specifics such as a loan rate and term based upon a portion of this user input data. The user data may include demographic data, behavioral data, or other data indicative of a user's future potential earnings or other relevant information that may be analyzed to determine, for that specific user, the current likelihood that the user will default on the loan and a future likelihood of default. When this future statistical likelihood is determined, the initial loan specific may be further modified and/or a targeted notification may be sent indicating these customized loan specifics.

    Preventing account overdrafts and excessive credit spending
    17.
    发明授权
    Preventing account overdrafts and excessive credit spending 有权

    公开(公告)号：US10977725B1

    公开(公告)日：2021-04-13

    申请号：US15498740

    申请日：2017-04-27

    Applicant: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY

    Inventor： Elizabeth Flowers ,  Puneit Dua ,  Alan Zwilling ,  Adam Mattingly ,  Melissa Attig ,  Reena Batra

    IPC: G06Q40/02 ,  G06Q30/02

    Abstract: Techniques are disclosed utilizing cognitive computing to improve banking experiences. A user's financial account(s) may be monitored to predict when a surplus of funds is unnecessarily present and for how long this will likely be the case. Once this is determined, techniques include automatically drafting funds from the account to another account having a higher interest rate where the funds may accrue more interest. The techniques also include predicting when an overdraft may occur and taking appropriate action when such a prediction is made. Predictions may be based upon different weighted inputs used in accordance with a predictive modeling system, which may attempt to predict for a particular user, location, and retailer, whether the user will spend an anticipated amount in excess of the user's current balance. If so, passive (e.g., notifications) and active (e.g., transferring cover funds) actions may be performed.

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