Patent Application Titled “Methods Of Providing Insurance Savings Based Upon Telematics And Driving Behavior Identification” Published Online (USPTO 20230130493): State Farm Mutual Automobile Insurance Company

2023 MAY 16 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- According to news reporting originating from Washington, D.C., by NewsRx journalists, a patent application by the inventors Baumann, Megan Michal (Bloomington, IL, US); Baumann, Nathan W. (Bloomington, IL, US); Bonnom, Atlanta (Bloomington, IL, US); Carter, Dustin Ryan (Normal, IL, US); Clauss, Mark E. (Bloomington, IL, US); Cope, Craig (Bloomington, IL, US); Graff, Douglas Albert (Mountain View, MO, US); Lawyer, Jennifer Luella (Bloomington, IL, US); Potter, Thomas Michael (Normal, IL, US); Simpson, Curtis (Bloomington, IL, US), filed on December 22, 2022, was made available online on April 27, 2023.

The assignee for this patent application is State Farm Mutual Automobile Insurance Company (Bloomington, Illinois, United States).

Reporters obtained the following quote from the background information supplied by the inventors: “Conventional insurance techniques and policies may be subject to inaccuracies due to limited information and/or inadequate risk mitigation or prevention. For example, conventional automobile insurance policies are based upon risk estimates using the age, location, and reported driving history (e.g., reported accidents) of a an insured driver. When such a policy covers multiple drivers (e.g., family members), estimates of risks associated with each driver are used, based upon typical drivers having similar demographic characteristics. Thus, conventional automobile insurance fails to accurately account for different risk levels posed by personal risk preferences and/or driving styles, as well as different risks associated with different usage levels of insured drivers. Conventional insurance techniques may also suffer from the lack of incentivizing the preferred types of behaviors; failure to properly identify risks associated with an individual; inefficient or ineffective customer communications; inadequate or incorrect behavior-based policies; and/or other drawbacks. The present embodiments may overcome these and/or other deficiencies.”

In addition to obtaining background information on this patent application, NewsRx editors also obtained the inventors’ summary information for this patent application: “The present embodiments disclose systems and methods that may relate to the intersection of telematics and insurance. In some embodiments, for example, telematics and/or other data may be gathered and used to determine risks associated with an insured vehicle or person. The data may be gathered from one or more sources, such as mobile devices (e.g., smart phones, smart glasses, smart watches, smart wearable devices, smart contact lenses, and/or other devices capable of wireless communication); smart vehicles; smart vehicle or smart home mounted sensors; third party sensors or sources of data (e.g., other vehicles, public transportation systems, government entities, and/or the Internet); and/or other sources of information. The data may further be collected or gathered from other vehicles (either directly or indirectly through vehicle-to-vehicle communication), infrastructure components, and/or other road side equipment. Insurance claims, policies, premiums, rates, discounts, rewards, deductibles, limits, and/or programs may then be adjusted based upon the risks determined from the telematics and/or other collected data. The determined risks may be applied to automobile insurance and/or other types of insurance. In some embodiments, the data may be received, risks determined, and/or insurance policies adjusted at a remote server.

“In accordance with the described embodiments, the disclosure herein generally addresses systems, methods, and computer-readable media for using anonymous driver data to adjust driving risk. The system, method, or media may include (1) collecting anonymous driver data associated with driving behavior of a plurality of drivers; (2) collecting insured driving behavior data associated with the driving behavior of an insured driver; (3) determining a driving risk score associated with the insured driver by comparing the anonymous driver data with the insured driving behavior data; (4) determining an adjustment to an insurance policy associated with the insured driver based upon the determined driving risk score; and/or (5) causing the adjustment to the insurance policy to be implemented.

“The anonymous driver data may indicate anonymous driver behavior associated with one or more road segments. The insured driving behavior data may be associated with the one or more road segments and/or may include telematics data generated by one or more sensors. The one or more road segments may include one or more of the following: a specific road, a specific section of a road, and/or an intersection. In some aspects, comparing the anonymous driver data with the insured driving behavior data may include comparing one or more of the following associated with the one or more road segments for anonymous drivers and the insured driver: vehicle speed, vehicle braking, vehicle acceleration, vehicle turning, vehicle position in a lane, vehicle distance from other vehicles, use of safety equipment, and/or driver alertness.

“In accordance with the described embodiments, the disclosure herein also generally addresses systems, methods, and computer-readable media for generating, adjusting, or updating an insurance policy using telematics data. The system, method, or media may include (1) collecting telematics data associated with driving behavior of an insured driver from one or more sensors; (2) determining one or more driving risk scores associated with the insured driver based upon the collected telematics data; (3) determining a risk aversion score associated with the insured driver based upon the one or more driving risk scores; (4) determining an adjustment to an insurance policy associated with the insured driver based upon the determined risk aversion score; and/or (5) causing the adjustment to the insurance policy to be implemented. In some aspects, the system, method, or media may further include transmitting information regarding the adjustment to the insurance policy to one or more insurance customers associated with the insurance policy for review and/or receiving a confirmation of the adjustment to the insurance policy from at least one of the one or more insurance customers.

“The insurance policy may be an automobile insurance policy or another type of insurance policy, such as a life insurance policy, a health insurance policy, a disability insurance policy, an accident insurance policy, a homeowners insurance policy, a renters insurance policy, and/or an excess liability insurance policy.

“Determining the one or more driving risk scores may include analyzing the collected telematics data to determine one or more of the following usage characteristics: (i) driving characteristics associated with the driving behavior of the insured driver (which may include one or more of the following: vehicle speed, vehicle braking, vehicle acceleration, vehicle turning, vehicle position in a lane, vehicle distance from other vehicles, use of safety equipment, and/or insured driver alertness), and/or (ii) driving environments associated with the driving behavior of the insured driver (which may include one or more of the following: geographic location, time of day, type of road, weather conditions, traffic conditions, construction conditions, route traveled, and/or a daily commute of the insured driver to and from a workplace). Determining the one or more driving risk scores may further include determining the one or more driving risk scores based upon the determined usage characteristics.

“Additionally, or alternatively, the one or more driving risk scores may be determined based, at least in part, upon one or more of the following: biometric data associated with the insured driver, the identity and usage of an insured vehicle by one or more drivers, a location an insured vehicle is parked, an amount of time the insured vehicle is garaged, and/or vehicle maintenance records. The identity and usage of an insured vehicle by one or more drivers may be determined based upon determined identities of one or more drivers of one or more insured vehicles and/or usage characteristics of the one or more drivers associated with the one or more insured vehicles, which may include one or more of the following: (i) an amount that each of the one or more drivers uses each of the one or more insured vehicles, (ii) driving behavior characteristics of each of the one or more drivers with respect to each of the one or more insured vehicles, and/or (iii) the vehicle environments in which each of the one or more drivers operates the one or more insured vehicles.

“In accordance with the described embodiments, the disclosure herein also generally addresses systems, methods, and computer-readable media for updating, adjusting, or generating an insurance policy associated with one or more insured vehicles based upon vehicle usage. The system, method, or media may include (1) collecting telematics data from one or more sensors associated with the one or more insured vehicles during one or more vehicle trips; (2) determining the identity of one or more drivers during each vehicle trip by analyzing the telematics data; (3) determining a summary of vehicle usage for the one or more insured vehicles over a plurality of vehicle trips; (4) determining an adjustment to the insurance policy based upon the determined summary of vehicle usage; and/or (5) causing the adjustment to the insurance policy to be implemented. In some aspects, the system, method, or media may further include transmitting information regarding the adjustment to the insurance policy to one or more insurance customers associated with the insurance policy for review and/or receiving a confirmation of the adjustment to the insurance policy from at least one of the one or more insurance customers.

“The telematics data may include sensor data regarding the identity of the driver and driving behavior during each vehicle trip. The summary of vehicle usage may include one or more of the following: (1) an amount that each of the one or more drivers uses each of the one or more insured vehicles, (2) driving behavior characteristics of each of the one or more drivers with respect to each of the one or more insured vehicles, and/or (3) the vehicle environments in which each of the one or more drivers operates the one or more insured vehicles. The vehicle environment of each vehicle trip may include the following: geographic location, time of day, type of road, weather conditions, traffic conditions, construction conditions, and/or route traveled.

“In accordance with the described embodiments, the disclosure herein also generally addresses systems, methods, and computer-readable media for providing insurance-based incentives or recommendations for vehicle insurance. The system, method, or media may include (1) collecting telematics data associated with driving behavior of an insured driver from one or more sensors; (2) analyzing the collected telematics data to determine one or more usage characteristics for the insured driver; (3) determining driving behavior summary for the insured driver based upon the determined usage characteristics; (4) determining one or more risky driving behaviors of the insured driver based upon the driving behavior summary; (5) determining one or more recommendations to the insured driver; and (6) causing the one or more recommendation to be transmitted to a computing device associated with the insured driver. The computing device may be a mobile device and/or a computer system of a vehicle associated with the insured driver.”

There is additional summary information. Please visit full patent to read further.”

The claims supplied by the inventors are:

“1.-40. (canceled)

“41. A computer-implemented method for using telematics data, comprising: collecting, at one or more processors, telematics data associated with driving behavior of an insured driver and biometric data associated with the insured driver from one or more sensors, the telematics data comprising sensor data indicative of visual information and at least one hard braking event; verifying, by the one or more processors based on the visual information, an accuracy of the at least one hard braking event and whether an unexpected action of another vehicle or a pedestrian is a cause of the at least one hard braking event; determining, by the one or more processors, one or more driving risk scores associated with the insured driver based upon the collected telematics data and the verified cause and accuracy of the at least one hard braking event, wherein each driving risk score indicates a level of risk of a vehicle accident; and generating, by the one or more processors, a risk aversion score associated with the insured driver based upon the one or more driving risk scores, wherein the risk aversion score indicates risk preferences of the insured driver.

“42. The computer-implemented method of claim 41, wherein the telematics data and the biometric data are collected by at least one processor in at least one front-end component of a telematics system, and the telematics data and the biometric data are communicated to at least one processor in at least one back-end component of the telematics system to perform the verifying of the accuracy, the determining of the one or more driving risk scores, and the generating of the risk aversion score.

“43. The computer-implemented method of claim 42, further comprising: operating a mobile device of the insured driver or an onboard computer of the insured vehicle in real-time as a pass-through communication node to facilitate communication with the back-end component of the telematics system.

“44. The computer-implemented method of claim 42, wherein the front-end component is configured to communicate with the back-end component via a network comprising at least one of: a proprietary network, a secure public internet, and a virtual private network.

“45. The computer-implemented method of claim 44, further comprising: transmitting, by the front-end component via the network, the telematics data and the biometric data that are collected in a remote server; and receiving, by the back-end component via the network, the telematics data and the biometric data from the remote server prior to performing the verifying of the accuracy, the determining of the one or more driving risk scores, and the generating of the risk aversion score.

“46. The computer-implemented method of claim 41, wherein determining the one or more driving risk scores includes: analyzing the collected telematics data to determine one or more of the following usage characteristics: (i) driving characteristics associated with the driving behavior of the insured driver, or (ii) driving environments associated with the driving behavior of the insured driver, and determining the one or more driving risk scores based upon the determined usage characteristics.

“47. The computer-implemented method of claim 46, wherein the driving characteristics include one or more of the following: vehicle speed, vehicle braking, vehicle acceleration, vehicle turning, vehicle position in a lane, vehicle distance from other vehicles, use of safety equipment, or insured driver alertness; and the driving environments include one or more of the following: geographic location, time of day, type of road, weather conditions, traffic conditions, construction conditions, or route traveled.

“48. The computer-implemented method of claim 46, wherein the driving environment includes a daily commute of the insured driver to and from a workplace.

“49. The computer-implemented method of claim 41, further comprising adjusting an insurance policy associated with the insured driver by adjusting a risk level associated with the insured driver for the insurance policy based upon the determined risk aversion score.

“50. The computer-implemented method of claim 49, wherein the insurance policy is one or more of the following: an automobile insurance policy, a health insurance policy, a disability insurance policy, an accident insurance policy, or an excess liability insurance policy.

“51. The computer-implemented method of claim 49, wherein the adjustment to the insurance policy includes one or more of the following: a premium, a rate, a reward, a deductible, or a limit.

“52. The computer-implemented method of claim 49, further comprising: transmitting, via a communication network, information regarding the adjustment to the insurance policy to one or more insurance customers associated with the insurance policy for review; and receiving, at the one or more processors, a confirmation of the adjustment to the insurance policy from at least one of the one or more insurance customers.

“53. The computer-implemented method of claim 41, wherein determining the one or more driving risk scores includes: determining the identity of one or more drivers of one or more insured vehicles, including the insured vehicle; determining usage characteristics of the one or more drivers associated with the one or more insured vehicles, including one or more of the following: (i) an amount that each of the one or more drivers uses each of the one or more insured vehicles, (ii) driving behavior characteristics of each of the one or more drivers with respect to each of the one or more insured vehicles, or (iii) the vehicle environments in which each of the one or more drivers operates the one or more insured vehicles; and determining the one or more driving risk scores based upon the determined usage characteristics.

“54. The computer-implemented method of claim 41, wherein determining the one or more driving risk scores is based, at least in part, upon one or more of the following: a location the insured vehicle is parked or an amount of time the insured vehicle is garaged.

“55. The computer-implemented method of claim 41, wherein determining the one or more driving risk score is based, at least in part, upon analysis of vehicle maintenance records.

“56. The computer-implemented method of claim 41, wherein the one or more sensors are disposed within or communicatively connected to one or more of the following: the mobile device or the on-board computer.

“57. The computer-implemented method of claim 41, wherein the telematics data further includes data generated by one or more of the following: (i) a vehicle other than the insured vehicle associated with the insured driver; (ii) the insured vehicle, based upon vehicle-to-vehicle communication with one or more other vehicles; (iii) an infrastructure component; or (iv) road side equipment.

“58. A computer system for using telematics data, comprising: one or more processors; one or more communication modules adapted to communicate data; and a program memory coupled to the one or more processors and storing executable instructions that when executed by the one or more processors cause the computer system to: collect telematics data associated with driving behavior of an insured driver and biometric data associated with the insured driver from one or more sensors via the one or more communication modules, the telematics data comprising sensor data indicative of visual information and at least one hard braking event; verify based on the visual information an accuracy of the at least one hard braking event and whether an unexpected action of another vehicle or a pedestrian is a cause of the at least one hard braking event; determine one or more driving risk scores associated with the insured driver based upon the collected telematics data and the verified cause and accuracy of the at least one hard braking event, wherein each driving risk score indicates a level of risk of a vehicle accident; and generate a risk aversion score associated with the insured driver based upon the one or more driving risk scores, wherein the risk aversion score indicates risk preferences of the insured driver.

“59. The computer system of claim 58, further comprising a telematics system including: at least one front-end component including at least one processor configured to collect the telematics data and the biometric data; and at least one back-end component including at least one processor configured to receive the telematics data and the biometric data to verify the accuracy, determine the one or more driving risk scores, and generate the risk aversion score.

“60. The computer system of claim 59, further comprising a mobile device of the insured driver or an onboard computer of the insured vehicle operable in real-time as a pass-through communication node to facilitate communication with the back-end component of the telematics system.

“61. The computer system of claim 59, further comprising a network through which the front-end component is configured to communicate with the back-end component, the network comprising at least one of: a proprietary network, a secure public internet, and a virtual private network.

“62. The computer system of claim 61, wherein the front-end component is configured to transmit, via the network, the telematics data and the biometric data that are collected in a remote server; and the back-end component is configured to receive, via the network, the telematics data and the biometric data from the remote server prior to verifying the accuracy, determining the one or more driving risk scores, and generating the risk aversion score.”

There are additional claims. Please visit full patent to read further.

For more information, see this patent application: Baumann, Megan Michal; Baumann, Nathan W.; Bonnom, Atlanta; Carter, Dustin Ryan; Clauss, Mark E.; Cope, Craig; Graff, Douglas Albert; Lawyer, Jennifer Luella; Potter, Thomas Michael; Simpson, Curtis. Methods Of Providing Insurance Savings Based Upon Telematics And Driving Behavior Identification. U.S. Patent Application Number 20230130493, filed December 22, 2022 and posted April 27, 2023. Patent URL (for desktop use only): https://ppubs.uspto.gov/pubwebapp/external.html?q=(20230130493)&db=US-PGPUB&type=ids