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    Automobile monitoring systems and methods for detecting damage and other conditions
    11.
    发明授权
    Automobile monitoring systems and methods for detecting damage and other conditions 有权

    公开(公告)号：US11373249B1

    公开(公告)日：2022-06-28

    申请号：US16136357

    申请日：2018-09-20

    Applicant: State Farm Mutual Automobile Insurance Company

    Inventor： Gregory L Hayward ,  Meghan Sims Goldfarb ,  Nicholas U. Christopulos ,  Erik Donahue

    IPC: G06Q40/08 ,  G06N3/08 ,  G06V20/00 ,  G06V30/194

    Abstract: A method of determining damage to property includes inputting historical data into a machine learning model to identify an insured type, features, and/or characteristics. The method may include identifying a peril, repair and/or replacement cost of the vehicle by analyzing a digital image from a device of an insured, the digital image depicting damage to the vehicle. The method may include inputting the digital image into the trained machine learning model to identify a type, feature, and/or characteristic of the vehicle, and may include identifying a peril, repair, and/or replacement cost associated with the vehicle. A method may include receiving and/or retrieving free-form text associated with an insurance claim and/or a vehicle, identifying at least one key word composing the free-form text, and determining based on the at least one key word a cause of loss and/or peril that caused damage to the vehicle.

    Automobile Monitoring Systems and Methods for Risk Determination
    12.
    发明申请
    Automobile Monitoring Systems and Methods for Risk Determination 有权

    公开(公告)号：US20210256616A1

    公开(公告)日：2021-08-19

    申请号：US16136370

    申请日：2018-09-20

    Applicant: State Farm Mutual Automobile Insurance Company

    Inventor： Gregory L. Hayward ,  Meghan Sims Goldfarb ,  Nicholas U. Christopulos ,  Erik Donahue

    IPC: G06Q40/08 ,  G06N3/08 ,  G10L15/26 ,  G06K9/72 ,  G06F17/30

    Abstract: A method of determining an automobile-based risk level via one or more processors includes training a machine learning program, such as a neural network, to identify risk factors within electronic claim features, receiving information corresponding to one or both of (i) an automobile, such as an autonomous or semi-autonomous vehicle, and (ii) an automobile operator, analyzing the information using the trained machine learning program to generate one or more risk indicators, determining, by analyzing the risk indicators, a risk level corresponding to the automobile, and/or displaying, to a user, a quotation based upon analyzing the risk indicators. The risk factors, risk indicators, and/or risk level may be used for many purposes, such as pricing, quoting, and/or underwriting of insurance policies.

    Real property monitoring systems and methods for detecting damage and other conditions
    13.
    发明授权
    Real property monitoring systems and methods for detecting damage and other conditions 有权

    公开(公告)号：US10943464B1

    公开(公告)日：2021-03-09

    申请号：US16668072

    申请日：2019-10-30

    Applicant: State Farm Mutual Automobile Insurance Company

    Inventor： Gregory L. Hayward ,  Meghan Sims Goldfarb ,  Nicholas U. Christopulos ,  Erik Donahue

    IPC: G08B25/01 ,  G06Q40/08 ,  G06N20/00 ,  G08B23/00

    Abstract: Machine learning systems, methods, and techniques for detecting damage and/or other conditions associated with a building, land, structure, or other real property using a real property monitoring system are disclosed. The property monitoring system is used in conjunction with machine learning techniques to determine and/or predict various conditions associated with the real property, including particular damage thereto, e.g., based upon dynamic characteristic data obtained via on-site sensors, static characteristic data, third-party input descriptive of an event impacting the building, etc. Accordingly, damage and/or loss associated with the building/real property is more quickly and/or accurately ascertained so that suitable mitigation techniques may be applied. In some scenarios, previously undetectable or uncharacterized damage and/or other conditions may be discovered and mitigated.

    Automatic building assessment
    16.
    发明授权
    Automatic building assessment 有权
    自动建筑评估

    公开(公告)号：US09082015B2

    公开(公告)日：2015-07-14

    申请号：US13839634

    申请日：2013-03-15

    Applicant: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY

    Inventor： Nicholas U. Christopulos ,  Jonathan D. Maurer ,  Nathan L. Tofte ,  Roger D. Schmidgall ,  James M. Freeman

    IPC: G06K9/62 ,  G06K9/00 ,  G06Q40/08

    CPC classification number: G06K9/00637 ,  G06K9/00536 ,  G06K9/00704 ,  G06K9/6267 ,  G06K9/6268 ,  G06K9/6279 ,  G06K9/628 ,  G06Q40/08 ,  G06Q50/16

    Abstract: Disclosed systems and methods automatically assess buildings and structures. A device may receive one or more images of a structure, such as a building or portion of the building, and then label and extract relevant data. The device may then train a system to automatically assess other data describing similar buildings or structures based on the labeled and extracted data. After training, the device may then automatically assess new data, and the assessment results may be sent directly to a client or to an agent for review and/or processing.

    Abstract translation: 公开的系统和方法自动评估建筑物和结构。 设备可以接收结构的一个或多个图像，例如建筑物或建筑物的一部分，然后标记和提取相关数据。 该装置然后可以训练系统以基于标记和提取的数据来自动评估描述类似建筑物或结构的其他数据。 培训后，设备可以自动评估新数据，并将评估结果直接发送给客户或代理进行审查和/或处理。

    ASSIGNING MOBILE DEVICE DATA TO A VEHICLE
    17.
    发明公开
    ASSIGNING MOBILE DEVICE DATA TO A VEHICLE 审中-公开

    公开(公告)号：US20240161201A1

    公开(公告)日：2024-05-16

    申请号：US18423146

    申请日：2024-01-25

    Applicant: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY

    Inventor： Nicholas U. Christopulos ,  Nicholas R. Baker ,  Eric Bellas ,  Benjamin F. Bowne

    IPC: G06Q40/08 ,  G06Q30/0201

    CPC classification number: G06Q40/08 ,  G06Q30/0201 ,  G01C21/3697

    Abstract: A method for identifying a primary vehicle associated with a user of a mobile device includes receiving an indication of a vehicle entry event from a mobile device and retrieving sensor data from the mobile device. The method further includes receiving an indication of a vehicle exit event from the mobile device, generating a trip log including portions of the sensor data, and storing the trip log in a trip database. A server, or other suitable computing device, then analyzes the trip log and a plurality of previously stored trip logs in the trip database to determine a primary vehicle corresponding to the user of the mobile device. The method may allow a computing device to assign gathered mobile device data to a specific household vehicle.

    Real Property Monitoring Systems and Methods for Risk Determination
    18.
    发明申请
    Real Property Monitoring Systems and Methods for Risk Determination 有权

    公开(公告)号：US20210390624A1

    公开(公告)日：2021-12-16

    申请号：US16136519

    申请日：2018-09-20

    Applicant: State Farm Mutual Automobile Insurance Company

    Inventor： Gregory L. Hayward ,  Meghan Sims Goldfarb ,  Nicholas U. Christopulos ,  Erik Donahue

    IPC: G06Q40/08 ,  G06N3/08 ,  G06F15/18

    Abstract: Machine learning techniques for determining a risk level of a target building or other type of real property include receiving data indicative of various historical characteristics of and/or associated with real property, and/or receiving data included in historical, electronic claims pertaining to buildings/real properties, and utilizing the received data to train a machine learning or other model that identifies or discovers risk factors associated with buildings/real properties. The machine learning or other model may be applied to characteristic data associated with the target building/real property to generate risk factors and/or risk indicators of the target building/real property. The techniques may include analyzing the generated risk factors and/or risk indicators to determine a risk level of the target building/real property. The risk factors, risk indicators, and/or risk level may be used for many purposes, such as pricing, quoting, underwriting, or re-underwriting of insurance policies.

    Automobile Monitoring Systems and Methods for Loss Reserving and Financial Reporting
    19.
    发明申请
    Automobile Monitoring Systems and Methods for Loss Reserving and Financial Reporting 有权

    公开(公告)号：US20210312567A1

    公开(公告)日：2021-10-07

    申请号：US17353621

    申请日：2021-06-21

    Applicant: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY

    Inventor： Gregory L. Hayward ,  Meghan Sims Goldfarb ,  Nicholas U. Christopulos ,  Erik Donahue

    IPC: G06Q40/08 ,  G06N3/08

    Abstract: A method of determining loss reserves and/or providing automatic financial reporting related thereto via one or more processors includes (1) receiving a plurality of historical electronic claim documents, each respectively labeled with a claim loss amount; (2) normalizing each respective claim loss amount and training an artificial intelligence or machine learning algorithm, module, or model, such as an artificial neural network, by applying the plurality of electronic claim documents to the artificial intelligence or machine learning algorithm, module, or model. The method may include receiving a user claim and predicting a loss reserve amount by applying the user claim to the trained artificial intelligence or machine learning algorithm, module, or model, and may include unreported claims.

    Automobile Monitoring Systems and Methods for Loss Reserving and Financial Reporting
    20.
    发明申请
    Automobile Monitoring Systems and Methods for Loss Reserving and Financial Reporting 有权

    公开(公告)号：US20210287297A1

    公开(公告)日：2021-09-16

    申请号：US16136401

    申请日：2018-09-20

    Applicant: State Farm Mutual Automobile Insurance Company

    Inventor： Gregory L Hayward ,  Meghan Sims Goldfarb ,  Nicholas U. Christopulos ,  Erik Donahue

    IPC: G06Q40/08 ,  G06N3/08

    Abstract: A method of determining loss reserves and/or providing automatic financial reporting related thereto via one or more processors includes (1) receiving a plurality of historical electronic claim documents, each respectively labeled with a claim loss amount; (2) normalizing each respective claim loss amount and training an artificial intelligence or machine learning algorithm, module, or model, such as an artificial neural network, by applying the plurality of electronic claim documents to the artificial intelligence or machine learning algorithm, module, or model. The method may include receiving a user claim and predicting a loss reserve amount by applying the user claim to the trained artificial intelligence or machine learning algorithm, module, or model, and may include unreported claims.

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