Methods of providing insurance savings based upon telematics and driving behavior identification
A system and method may collect telematics and/or other data, and apply the data to insurance-based applications. From the data, an insurance provider may determine accurate vehicle usage information, including information regarding who is using a vehicle and under what conditions. An insurance provider may likewise determine risk levels or a risk profile for an insured driver (or other drivers), which may be used to adjust automobile or other insurance policies. The insurance provider may also use the data collected to adjust behavior based insurance using incentives, recommendations, or other means. For customers that opt-in to the data collection program offered, the present embodiments present the opportunity to demonstrate a low or moderate risk lifestyle and the chance for insurance-related savings based upon that low or moderate risk.
1. A computer-implemented method for modifying mobile device functionality based at least in part on telematics data, comprising:
collecting, at one or more processors and from one or more sensors, telematics data associated with driving behavior of a driver and biometric data associated with the driver, the telematics data comprising sensor data indicative of visual information and a hard braking event;
verifying, by the one or more processors based at least in part on the visual information, an accuracy of the hard braking event and whether an unexpected action of an object is a cause of the hard braking event;
determining, by the one or more processors, a driving risk score for the driver based at least in part on the telematics data and the cause of the hard braking event, wherein the driving risk score indicates a level of risk of a vehicle accident;
generating, by the one or more processors, a risk aversion score associated with the driver based at least in part on the driving risk score, wherein the risk aversion score indicates risk preferences of the driver; and
transmitting, by the one or more processors to a mobile device associated with the driver, based at least in part on the risk aversion score, instructions to limit texting functionality of the mobile device.
2. The computer-implemented method of claim 1 , wherein the telematics data and the biometric data are collected by a first 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 a second 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 driving risk score, and the generating of the risk aversion score.
3. The computer-implemented method of claim 2 , further comprising:
operating the mobile device associated with the driver or an on-board vehicle computer in real-time as a pass-through communication node to facilitate communication with the at least one back-end component of the telematics system.
4. The computer-implemented method of claim 2 , wherein the at least one front-end component is configured to communicate with the at least one back-end component via a network comprising at least one of: a proprietary network, a secure public internet, or a virtual private network.
5. The computer-implemented method of claim 4 , further comprising:
transmitting, by the at least one front-end component via the network, the telematics data and the biometric data; and
receiving, by the at least one back-end component via the network, the telematics data and the biometric data prior to performing the verifying of the accuracy, the determining of the driving risk score, and the generating of the risk aversion score.
6. The computer-implemented method of claim 1 , wherein determining the driving risk score includes:
analyzing the telematics data to determine usage characteristics including one or more of: (i) driving characteristics associated with the driving behavior of the driver, or (ii) driving environments associated with the driving behavior of the driver, and
determining the driving risk score based at least in part on the usage characteristics.
7. The computer-implemented method of claim 6 , wherein:
the driving characteristics include one or more of vehicle speed, vehicle braking, vehicle acceleration, vehicle turning, vehicle position in a lane, vehicle distance from other vehicles, use of safety equipment, or driver alertness; and
the driving environments include one or more of: geographic location, time of day, type of road, weather conditions, traffic conditions, construction conditions, or route traveled.
8. The computer-implemented method of claim 1 , wherein:
the telematics data is first telematics data,
the one or more sensors are configured at a vehicle in a geographical area, and
the computer-implemented method further comprises:
collecting, by the one or more processors, from a third-party database, second telematics data associated with a plurality of vehicles excluding the vehicle, the second telematics data comprising braking data indicative of braking events in the geographical area and associated with the plurality of vehicles; and
determining, by the one or more processors, the driving risk score further based at least in part on a comparison of the first telematics data to the braking data.
9. The computer-implemented method of claim 1 , further comprising adjusting a price for a product associated with the driver by adjusting a risk level associated with the driver for the product based at least in part on the risk aversion score.
10. The computer-implemented method of claim 9 , wherein the product is one or more of an automobile insurance policy, a health insurance policy, a disability insurance policy, an accident insurance policy, or an excess liability insurance policy.
11. The computer-implemented method of claim 9 , wherein adjusting the price includes adjusting one or more of a premium, a rate, a reward, a deductible, or a limit.
12. The computer-implemented method of claim 9 , further comprising:
transmitting, via a communication network, information regarding adjusting the price to a customer associated with the product for review; and
receiving, at the one or more processors, a confirmation of the information from the customer.
13. The computer-implemented method of claim 1 , wherein determining the driving risk score includes:
determining an identity of one or more drivers of one or more vehicles, including a vehicle associated with the driver;
determining usage characteristics of the one or more drivers, including one or more of: (i) an amount that each of the one or more drivers uses each of the one or more vehicles, (ii) driving behavior characteristics of each of the one or more drivers with respect to each of the one or more vehicles, or (iii) one or more vehicle environments in which each of the one or more drivers operates the one or more vehicles; and
determining the driving risk score based at least in part on the usage characteristics.
14. The computer-implemented method of claim 1 , wherein determining the driving risk score is based at least in part on one or more of a location at which a vehicle associated with the driver is parked or an amount of time the vehicle associated with the driver is garaged.
15. The computer-implemented method of claim 1 , wherein determining the driving risk score is based at least in part on analysis of vehicle maintenance records.
16. The computer-implemented method of claim 1 , wherein the one or more sensors are disposed within or communicatively connected to one or more of the mobile device or an on-board vehicle computer.
17. The computer-implemented method of claim 1 , wherein the telematics data further includes data generated by one or more of: (i) a vehicle that is not associated with the driver; (ii) a vehicle associated with the driver and based at least in part on vehicle-to-vehicle communication with one or more other vehicles; (iii) an infrastructure component; or (iv) road side equipment.
18. A computer system for modifying mobile device functionality based at least in part on 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 a driver and biometric data associated with the driver from one or more sensors via the one or more communication modules, the telematics data comprising sensor data indicative of visual information and a hard braking event;
verify, based at least in part on the visual information, an accuracy of the hard braking event and whether an unexpected action of an object is a cause of the hard braking event;
determine a driving risk score associated with the driver based at least in part on the telematics data and the cause of the hard braking event, wherein the driving risk score indicates a level of risk of a vehicle accident;
generate a risk aversion score associated with the driver based at least in part on the driving risk score, wherein the risk aversion score indicates risk preferences of the driver; and
transmit, to a mobile device associated with the driver, based at least in part on the risk aversion score, instructions to limit texting functionality of the mobile device.
19. The computer system of claim 18 , further comprising a telematics system including:
at least one front-end component including a first at least one processor configured to collect the telematics data and the biometric data; and
at least one back-end component including a second at least one processor configured to receive the telematics data and the biometric data to verify the accuracy, determine the driving risk score, and generate the risk aversion score.
20. The computer system of claim 19 , further comprising the mobile device of the driver or an on-board vehicle computer operable in real-time as a pass-through communication node to facilitate communication with the at least one back-end component of the telematics system.
21. The computer system of claim 19 , further comprising a network through which the at least one front-end component is configured to communicate with the at least one back-end component, the network comprising at least one of: a proprietary network, a secure public internet, or a virtual private network.
22. The computer system of claim 21 , wherein:
the at least one 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 at least one back-end component is configured to receive, via the network, the telematics data and the biometric data prior to verifying the accuracy, determining the driving risk score, and generating the risk aversion score.
23. The computer system of claim 18 , wherein the executable instructions that cause the computer system to determine the driving risk score cause the computer system to:
adjust a price for a product associated with the driver by adjusting a risk level associated with the driver for the product based at least in part on the risk aversion score.
24. The computer system of claim 18 , wherein the executable instructions that cause the computer system to determine the driving risk score cause the computer system to:
analyze the telematics data to determine usage characteristics including one or more of: (i) driving characteristics associated with the driving behavior of the driver, or (ii) driving environments associated with the driving behavior of the driver, and
determine the driving risk score based at least in part on the usage characteristics.
25. The computer system of claim 18 , wherein the driving risk score is determined based at least in part on one or more of a location at which a vehicle associated with the driver is parked, an amount of time the vehicle is garaged, or vehicle maintenance records.
26. A tangible, non-transitory computer-readable medium storing first instructions for modifying mobile device functionality based at least in part on telematics data that, when executed by one or more processors of a computer system, cause the computer system to:
collect telematics data associated with driving behavior of a driver and biometric data associated with the driver from one or more sensors, the telematics data comprising sensor data indicative of visual information and a hard braking event;
verify, based at least in part on the visual information, an accuracy of the hard braking event and whether an unexpected action of an object is a cause of the hard braking event;
determine a driving risk score associated with the driver based at least in part on the telematics data and the cause of the hard braking event, wherein the driving risk score indicates a level of risk of a vehicle accident;
generate a risk aversion score associated with the driver based at least in part on the driving risk score, wherein the risk aversion score indicates risk preferences of the driver; and
transmit, to a mobile device associated with the driver, based at least in part on the risk aversion score, second instructions to limit texting functionality of the mobile device.
27. The tangible, non-transitory computer-readable medium of claim 26 , wherein the first instructions that cause the computer system to determine the driving risk score cause the computer system to:
analyze the telematics data to determine usage characteristics including one or more of: (i) driving characteristics associated with the driving behavior of the driver, or (ii) driving environments associated with the driving behavior of the driver; and
determine the driving risk score based at least in part on the usage characteristics.
28. The tangible, non-transitory computer-readable medium of claim 26 , wherein the driving risk score is determined based at least in part on one or more of a location at which a vehicle associated with the driver is parked, an amount of time the vehicle is garaged, or vehicle maintenance records.