Patent Issued for Systems and methods of utilizing unmanned vehicles to detect insurance claim buildup (USPTO 11195234): State Farm Mutual Automobile Insurance Company

2021 DEC 27 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- State Farm Mutual Automobile Insurance Company (Bloomington, Illinois, United States) has been issued patent number 11195234, according to news reporting originating out of Alexandria, Virginia, by NewsRx editors.

The patent’s inventors are Baumann, Nathan W (Bloomington, IL, US), Grant, Rosemarie Geier (Ellsworth, IL, US), Harvey, Brian N (Bloomington, IL, US), Jacob, Michael Shawn (Le Roy, IL, US), Lillie, Joshua David (Bloomington, IL, US), Lyons, Roxane (Chenoa, IL, US), Ryan, Timothy W (Hudson, IL, US), Tofte, Nathan L (Downs, IL, US).

This patent was filed on July 12, 2019 and was published online on December 7, 2021.

From the background information supplied by the inventors, news correspondents obtained the following quote: “After a loss event, an individual who owns an insured asset such as a vehicle may file an insurance claim with their insurance company. The insurance claim typically specifies a monetary amount that the claimant individual claims represents an amount of damage incurred by the insured asset and/or any individuals associated with the loss event. However, claim buildup may occur when the claimant individual submits an insurance claim that contains an inflated monetary amount that includes damage not associated with the loss event. For example, the individual may submit an insurance claim that indicates additional or unrelated pain clinic treatments, the costs of which inflate the total monetary amount included in the insurance claim.

“Buildup is estimated to result in billions of dollars in excess payments to customers and also raises insurance costs for all customers. Consequently, it is beneficial for insurance companies to reliably detect buildup in submitted insurance claims to avoid making excess payments and reduce fraud.”

Supplementing the background information on this patent, NewsRx reporters also obtained the inventors’ summary information for this patent: “The present embodiments may relate to, inter alia, using at least one unmanned vehicle to obtain data relating to a loss event. In one aspect, the unmanned vehicle may be an unmanned aerial vehicle (commonly known as a “drone,” or UAV). The loss event data may be used to predict the extent of damage from a loss event, such as an expected total claim amount for a loss event. The prediction may consider several aspects of an insurance claim, such as an estimated repair cost for the damage to an insured asset and/or an estimated total medical treatment for the passengers. To estimate these figures, systems and methods may analyze data captured by the unmanned vehicle to predict the type of insured asset that was damaged (e.g., the type of vehicle), the number of passengers, the type of repairs required and/or the type of medical treatment required.

“For instance, the data detected by the at least one unmanned vehicle or drone may be video data and the loss event may be a collision between two vehicles. The video data may be analyzed to determine that the vehicles are sedans and the expected number of passengers is two per vehicle. The extent of damage to the vehicles may be estimated by analyzing video or image data for depictions of the vehicles before and after the collision. The damage may also be estimated by analyzing any telematics data of the vehicles before and during the collision. The at least one unmanned vehicle may directly capture the telematics. Additionally, a server or similar component may calculate the telematics based upon one or more depictions of the loss event. The types of repairs required may be estimated based upon the estimated damage or may be based upon historic data associated with previously-submitted claims. For example, if the loss event is a low-speed collision with minimal visible damage, the repairs may be estimated by examining previous low-speed collisions. However, if the loss event is a high-speed collision with visible damage, the repairs may be estimated by looking at previous high-speed collisions. In that way, the repairs may include potential internal damage to the vehicle (e.g., issues with the frame or transmission) that may not be directly visible in video or image data. Similarly, the medical treatment may be estimated by comparing the severity of the collision with previously-submitted claims. Therefore, a low-speed collision may have minimal estimated treatment and a high-speed collision may have an estimated medical treatment that may include a hospital stay.

“A server or similar component may calculate an estimated insurance claim based upon these parameters. The estimated insurance claim may include information on one or more of these parameters and may include an estimated total claim amount. A claimant individual may submit an actual insurance claim associated with one or more of the insured assets involved in the loss event. Once the server receives the actual insurance claim, the server may compare the actual insurance claim to the estimated insurance claim. This comparison may include comparing one or more fields of the estimated insurance claim (e.g., estimated total claim amount, estimated medical treatment total and/or estimated repair total) with the corresponding fields on the actual insurance claim (e.g., actual total claim amount, actual medical treatment total and/or actual repair total). If the fields of the respective insurance claims differ by a predetermined threshold, then the server may deem that there is potential claim buildup included in the actual insurance claim. The server may then process the actual insurance claim based upon the potential claim buildup, which may include forwarding the actual insurance claim to a fraud investigations team or adjusting the total claim amount and forwarding the adjusted claim to the claimant for review.

“A system and method of implementing unmanned vehicles or drones to detect insurance claim buildup may be provided. In particular, the method of implementing unmanned vehicles to detect claim buildup may include receiving, at a server associated with an insurance provider, data detected by at least one unmanned vehicle, the data indicating a loss event involving at least one of an individual and an insured asset; and examining, by a processor, the data detected by the at least one unmanned vehicle to calculate an estimated amount of damage resulting from the loss event. The method may further include generating, by the processor, an estimated insurance claim for the loss event based upon the estimated amount of damage resulting from the loss event; receiving, at the server, an actual insurance claim related to the loss event and submitted by a claimant individual; and/or comparing, by the processor, the estimated insurance claim to the actual insurance claim to identify potential buildup included in the actual insurance claim. The method may further include processing the actual insurance claim based upon the potential buildup. As a result, fraudulent claims may be reduced, and/or insurance cost savings may ultimately be provided to the average consumer. The method may include additional, less, or alternate actions, including those discussed elsewhere herein, and/or may be implemented via one or more local or remote processors.

“In another example of the present disclosure, a system for implementing unmanned vehicles, which may include unmanned aerial vehicles or drones, to detect insurance claim buildup may be provided. The system may include a transceiver adapted to interface with and receive data detected by at least one unmanned vehicle, a memory adapted to store non-transitory computer executable instructions, and a processor adapted to interface with the transceiver and the memory. The processor may be configured to execute the non-transitory computer executable instructions to cause the process to receive, via the transceiver, data detected by the at least one unmanned vehicle, the data indicating a loss event involving at least one of an individual and an insured asset and examine the data detected by the at least one unmanned vehicle to calculate an estimated amount of damage resulting from the loss event. The processor may also be configured to generate an estimated insurance claim for the loss event based upon the estimated amount of damage resulting from the loss event, receive an actual insurance claim related to the loss event and submitted by a claimant individual, compare the estimated insurance claim to the actual insurance claim to identify potential buildup included in the actual insurance claim, and/or process the actual insurance claim based upon the potential buildup. As a result, more accurate insurance claim amounts may ultimately be paid out to insureds, and insurance cost savings may be provided to an average consumer. The system may include additional, less, or alternate functionality, including that discussed elsewhere herein.”

The claims supplied by the inventors are:

“1. A computer-implemented method of fraudulent claim detection, the method comprising: directing, by a server associated with an insurance provider, at least one unmanned vehicle to a location of at least one of an individual or an insured asset to collect data indicating a loss event involving the individual or the insured asset; receiving, at the server, the data detected by the at least one unmanned vehicle; examining, by a processor, the data detected by the at least one unmanned vehicle to calculate an estimated amount of damage resulting from the loss event; generating, by the processor, an estimated insurance claim for the loss event based upon the estimated amount of damage resulting from the loss event; receiving, at the server, an actual insurance claim related to the loss event and submitted by a claimant individual; and comparing, by the processor, the estimated insurance claim to the actual insurance claim to identify potential buildup included in the actual insurance claim.

“2. The computer-implemented method of claim 1, wherein receiving the data detected by the at least one unmanned vehicle comprises: receiving at least one of image data, video data, and audio data detected by the at least one unmanned vehicle.

“3. The computer-implemented method of claim 1, wherein examining the data detected by the at least one unmanned vehicle comprises: analyzing the data detected by the at least one unmanned vehicle, and based upon the analyzing, identifying at least one condition associated with the insured asset.

“4. The computer-implemented method of claim 3, wherein identifying the at least one condition associated with the insured asset comprises: identifying at least one of: damage to the insured asset due to the loss event, pre-existing damage to the insured asset prior to the loss event, a required repair for the insured asset, a location of the insured asset, an orientation of the insured asset relative to a roadway, and an operating condition at the time of the loss event.

“5. The computer-implemented method of claim 1, wherein examining the data detected by the at least one unmanned vehicle comprises: identifying at least one of: an expected type of vehicle, an expected number of passengers, at least one expected injury of the passengers, and at least one expected type of medical treatment for the passengers.

“6. The computer-implemented method of claim 1, wherein examining the data detected by the at least one unmanned vehicle comprises: accessing telematics information corresponding to at least one operating condition of the insured asset around a time of the loss event; and analyzing the telematics information.

“7. The computer-implemented method of claim 1, wherein examining the data detected by the at least one unmanned vehicle comprises: determining a percentage fault for the loss event for at least one of: at least one human driver, at least one autonomous or semi-autonomous vehicle, at least one road condition, at least one traffic condition, at least one weather condition, and road construction.

“8. The computer-implemented method of claim 1, wherein generating the estimated insurance claim for the loss event comprises: populating the estimated insurance claim for the loss event with at least one of: an estimated total monetary claim amount, an estimated total repair amount, and an estimated total medical treatment amount.

“9. The computer-implemented method of claim 1, wherein generating the estimated insurance claim for the loss event comprises: accessing historical data associated with previously-submitted insurance claims; and generating the estimated insurance claim for the loss event based upon the estimated amount of damage resulting from the loss event and the historical data.

“10. The computer-implemented method of claim 1, wherein comparing the estimated insurance claim to the actual insurance claim to identify the potential buildup included in the actual insurance claim comprises: comparing at least one field of the estimated insurance claim with at least one corresponding field of the actual insurance claim, the at least one field including at least one of: a total monetary amount, a total repair amount, a type of repair, a total medical treatment amount, a number of passengers, and a type of medical treatment; and identifying the potential buildup if the at least one field of the estimated insurance claim differs from the at least one corresponding field of the actual insurance claim by a predetermined threshold.

“11. The computer-implemented method of claim 1, the method further comprising: processing the actual insurance claim by at least one of: flagging the actual insurance claim for further review, and forwarding the actual insurance claim to a fraud investigations team associated with the insurance provider.

“12. A central monitoring server for detecting fraudulent claims, the system comprising: a transceiver adapted to interface with and receive data detected by at least one unmanned vehicle; a memory adapted to store non-transitory computer executable instructions; and a processor adapted to interface with the transceiver and the memory, wherein the processor is configured to execute the non-transitory computer executable instructions to cause the processor to: direct the at least one unmanned vehicle to a location of at least one of an individual or an insured asset to collect data indicating a loss event involving the individual or the insured asset; receive, via the transceiver, the data detected by the at least one unmanned vehicle; examine the data detected by the at least one unmanned vehicle to calculate an estimated amount of damage resulting from the loss event; generate an estimated insurance claim for the loss event based upon the estimated amount of damage resulting from the loss event; receive an actual insurance claim related to the loss event and submitted by a claimant individual; and compare the estimated insurance claim to the actual insurance claim to identify potential buildup included in the actual insurance claim.

“13. The central monitoring system of claim 12, wherein to receive the data detected by the at least one unmanned vehicle, the processor is configured to: receive at least one of image data, video data, and audio data detected by the at least one unmanned vehicle; and wherein to examine the data detected by the at least one unmanned vehicle, the processor is configured to: analyze the data detected by the at least one unmanned vehicle; and based upon the analysis, identify at least one condition associated with the insured asset.

“14. The central monitoring server of claim 13, wherein to identify the at least one condition associated with the insured asset, the processor is configured to: identify at least one of: damage to the insured asset due to the loss event, pre-existing damage to the insured asset prior to the loss event, a required repair for the insured asset, a location of the insured asset, an orientation of the insured asset relative to a roadway, and an operating condition at the time of the loss event.

“15. The central monitoring server of claim 12, wherein to examine the data detected by the at least one unmanned vehicle, the processor is configured to: identify at least one of: an expected type of vehicle, an expected number of passengers, at least one expected injury of the passengers, and at least one expected type of medical treatment for the passengers.

“16. The central monitoring server of claim 12, wherein to examine the data detected by the at least one unmanned vehicle, the processor is configured to: access telematics information corresponding to at least one operating condition of the insured asset around a time of the loss event; and analyze the telematics information.

“17. The central monitoring server of claim 12, wherein to examine the data detected by the at least one unmanned vehicle, the processor is configured to: determine a percentage fault for the loss event for at least one of: at least one human driver, at least one autonomous or semi-autonomous vehicle, at least one road condition, at least one traffic condition, at least one weather condition, and road construction.

“18. The central monitoring server of claim 12, wherein to generate the estimated insurance claim for the loss event, the processor is configured to: populate the estimated insurance claim for the loss event with at least one of: an estimated total monetary claim amount, an estimated total repair amount, and an estimated total medical treatment amount.

“19. The central monitoring server of claim 12, wherein to generate the estimated insurance claim for the loss event, the processor is configured to: access historical data associated with previously-submitted insurance claims; and generate the estimated insurance claim for the loss event based upon the estimated amount of damage resulting from the loss event and the historical data.

“20. The central monitoring server of claim 12, wherein to compare the estimated insurance claim to the actual insurance claim to identify the potential buildup included in the actual insurance claim, the processor is configured to: compare at least one field of the estimated insurance claim with at least one corresponding field of the actual insurance claim, the at least one field including at least one of: a total monetary amount, a total repair amount, a type of repair, a total medical treatment amount, a number of passengers, and a type of medical treatment; and identify the potential buildup if the at least one field of the estimated insurance claim differs from the at least one corresponding field of the actual insurance claim by a predetermined threshold.”

For the URL and additional information on this patent, see: Baumann, Nathan W. Systems and methods of utilizing unmanned vehicles to detect insurance claim buildup. U.S. Patent Number 11195234, filed July 12, 2019, and published online on December 7, 2021. Patent URL: http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PALL&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.htm&r=1&f=G&l=50&s1=11195234.PN.&OS=PN/11195234RS=PN/11195234

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