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    Cognitive computing for generating targeted offers to inactive account holders
    4.
    发明授权
    Cognitive computing for generating targeted offers to inactive account holders 有权

    公开(公告)号：US10891655B1

    公开(公告)日：2021-01-12

    申请号：US15498872

    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: G06Q30/00 ,  G06Q30/02

    Abstract: Techniques are disclosed utilizing cognitive computing to improve banking experiences. A user's financial account(s) and location may be monitored to predict when a user is near a retail store and the user has not used a particular account in a predetermined amount of time. The techniques disclosed include receiving a location for a user's mobile device, and determining when the mobile device is within a predetermined threshold distance of a retail store. The techniques include building a shopping profile for the user based upon shopping habits for the user. The shopping profile may be used to determine what commercial communications should be transmitted to the user to encourage them to utilize an inactive account to make a purchase at the retail store when the user is within the threshold distance of the retail store.

    USING COGNITIVE COMPUTING TO PROVIDE A PERSONALIZED BANKING EXPERIENCE
    6.
    发明申请
    USING COGNITIVE COMPUTING TO PROVIDE A PERSONALIZED BANKING EXPERIENCE 有权

    公开(公告)号：US20220083995A1

    公开(公告)日：2022-03-17

    申请号：US15499061

    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: G06Q20/10 ,  G06Q40/02 ,  G06N99/00 ,  G06N5/02 ,  G06Q30/02

    Abstract: Techniques are disclosed utilizing cognitive computing to improve banking experiences. A customer's account may be monitored to determine an amount of customer interactions, and that the amount of customer interactions for the customer through at least one self-service channel is less than the amount of customer interactions for the customer through at least one full-service channel. When the amount of customer interactions for the customer through the at least one self-service channel is less than the amount of customer interactions through the at least one full-service channel, the system may generate an electronic offer for the customer that includes a reward for an account associated with the customer if the customer increases usage of the at least one self-service channel and decreases usage of the at least one full-service channel for future customer interactions with the vendor.

    CUSTOMIZING LOAN SPECIFICS ON A PER-USER BASIS
    7.
    发明申请
    CUSTOMIZING LOAN SPECIFICS ON A PER-USER BASIS 有权

    公开(公告)号：US20210150625A1

    公开(公告)日：2021-05-20

    申请号：US17161471

    申请日：2021-01-28

    Applicant: State Farm Mutual Automobile Insurance Company

    Inventor： Elizabeth A. 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.

    Using cognitive computing to improve relationship pricing
    9.
    发明授权
    Using cognitive computing to improve relationship pricing 有权

    公开(公告)号：US10891628B1

    公开(公告)日：2021-01-12

    申请号：US15499205

    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: G06Q30/00 ,  G06Q10/06 ,  G06Q30/02 ,  G06N5/04

    Abstract: Techniques are disclosed utilizing cognitive computing to assess customer value and provide specific promotional campaigns based upon this assessed value. Users may opt in to a rewards program. With user permission or affirmative consent, user behavioral data may be monitored that may be relevant to the user's relationship as a customer with a particular business and may include various indications of the users' behaviors, actions, and/or preferences. This data may be stored as part of each user's behavioral profile, the contents of which may be analyzed to determine which customers are more profitable to the business than others. Each user may be assigned a customer value indicative of his or her individual profitability, which may be used to provide specific promotional campaigns in an attempt to maintain the more profitable customers and to improve the profitability of others.

    OPTIMIZING INTEREST ACCRUAL BETWEEN A USER'S FINANCIAL ACCOUNTS
    10.
    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.

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