Abstract: In a method for applying penalties or incentives to a driver of a rented vehicle, an indication that the driver has agreed to terms for renting the vehicle from the vehicle owner is received, with the terms including the potential application of penalties or incentives to the driver based on driving behavior. Telematics data, indicative of operation of the rented vehicle by the driver during a period of time, is received. By analyzing the telematics data, one or more driving behaviors of the driver during the time period is/are identified. For each driving behavior, a corresponding state of an environment of the rented vehicle when the driving behavior occurred is determined. One or more penalties or incentives are caused to be applied to the driver, based on the driving behavior(s) and the corresponding state(s) of the environment of the rented vehicle.

Abstract: An analytics computing device is disclosed that includes a processor in communication with at least one memory device. The processor is configured to receive dynamic data corresponding to activity of a user, and including telematics data generated by a user device associated with the user. The processor is also configured to generate a plurality of analytics values based upon the dynamic data by applying at least one artificial intelligence (AI) model to the dynamic data, and generate an analytics vector for the user. The analytics vector includes the plurality of analytics values. The processor is further configured to use the analytics vector and at least one rule set of a plurality of rule sets to calculate at least one price for a usage-based insurance (UBI) policy of the user.

Abstract: A computer-implemented method for assessing damage to a plurality of properties is provided. After an occurrence of an event that is a potential cause of insured losses, image data depicting an aerial view of the properties may be received from an aerial platform. The image data may be processed to determine a subsequent condition of each property after occurrence of the event. Further, a damage severity level may be determined for each property, and used to display a map depicting different regions having properties with different respective damage severity levels.

Abstract: A computer system for verifying hail damage and/or detecting hail fraud, using computer vision and artificial intelligence, includes a processor and a non-transitory, tangible, computer-readable storage medium having instructions stored thereon that, in response to execution by the processor, cause the processor to perform operations including: (i) receiving at least one image of at least a portion of a rooftop; (ii) analyzing the image to identify a plurality of damaged locations; (iii) analyzing the damaged locations to determine a distance between each of the damaged locations, a size of each of the damaged locations, and a shape of each of the damaged locations; and (iv) determining whether the damaged locations are a result of actual hail damage based upon at least one of the distance between each of the damaged locations, the size of each of the damaged locations, and the shape of each of the damaged locations.

Abstract: The present embodiments relate to detecting fraudulent insurance claims. According to certain aspects, a central monitoring server may receive and examine data detected by at least one unmanned vehicle and generate an estimated insurance claim for a loss event. The central monitoring server may then receive an actual insurance claim relating to the loss event, and may compare the estimated insurance claim to the actual insurance claim to identify potential buildup included in the actual insurance claim. If buildup is detected, the central monitoring server may then process the actual insurance claim accordingly based upon the potential buildup. As a result, claim monies may be paid to insureds that more accurately reflect actual losses resulting from the loss event, and insurance cost savings may be ultimately passed onto typical insurance customers.

Abstract: Embodiments described herein generate a first set of prompts, the first set of prompts configured to prompt a vehicle owner for a first set of answers used to learn preferred vehicle renter characteristics; receive the first set of answers; generate, based upon the first set of answers, a second set of prompts, the second set of prompts configured to prompt the owner for a second set of answers used to learn additional preferred vehicle renter characteristics; receive the second set of answers; predict user preference value(s) of a profile of the owner based upon the second set of answers, wherein the user preference value(s) define criteria for sharing a vehicle associated with the profile with vehicle renters who satisfy the criteria; apply the criteria to potential vehicle renters; and cause an indication of the vehicle to be displayed only to the potential vehicle renters who satisfy the criteria.

Abstract: A computer-implemented method for providing data associated with insured losses is presented. Data regarding an event that is a cause of the insured losses may be received. Respective indications of locations of properties insured by an insurance provider and sustaining the insured losses may be received. Image data from at least one image capturing device, where the image data is obtained from an aerial view of the properties and indicative of respective conditions of the properties, may be received. The image data may be processed to determine, for each property, an indication of the respective condition. The data associated with the insured losses may be provided via a user interface. The data associated with the insured losses may include (i) the respective indications of the locations of the properties, and (ii) the indications of the respective conditions of the properties.

Abstract: Systems and methods are described for using data collected by unmanned aerial vehicles (UAVs) to generate insurance claim estimates that an insured individual may quickly review, approve, or modify. When an insurance-related event occurs, such as a vehicle collision, crash, or disaster, one or more UAVs are dispatched to the scene of the event to collect various data, including data related to vehicle or real property (insured asset) damage. With the insured's permission or consent, the data collected by the UAVs may then be analyzed to generate an estimated insurance claim for the insured. The estimated insurance claim may be sent to the insured individual, such as to their mobile device via wireless communication or data transmission, for subsequent review and approval. As a result, insurance claim handling and/or the online customer experience may be enhanced.

Abstract: Various techniques are described utilizing unmanned aerial vehicles (UAVs, or “drones”) for various disaster and/or catastrophe-related purposes. An area at risk of an insurance-related event (catastrophe, hurricane, natural disaster, wild fire, etc.) that requires evacuation may be determined, as well as insured premises or assets within that area. With an insured's permission, drones may be directed to the area to collect image or other data of insured premises or assets before, during, or after the event strikes. The drone data may be received and analyzed to identify losses to insured assets that should properly be classified as theft losses for insurance purposes. Insurance claims may be prepared or adjusted for insureds based upon the theft losses in accordance with various types of insurance policies (auto, home, personal articles, etc.) or endorsements to ensure that insureds are properly and promptly reimbursed for the theft losses.

Abstract: A method and system may assess the damage to infrastructure using aerial images captured from an unmanned aerial vehicle (UAV), a manned aerial vehicle (MAV) or from a satellite device. Specifically, an item of infrastructure may be identified for assessing damage. The UAV, MAV, or satellite device may then capture aerial images within an area which surrounds the identified infrastructure item. Subsequently, the aerial images may be analyzed to determine a condition and the extent and/or severity of the damage to the infrastructure item. Furthermore, the aerial images along with indications of the extent of the damage may be displayed on a computing device, where one indication of the severity of the damage surrounds another indication of the severity of the damage on the display.

Abstract: Various techniques are described utilizing one or more unmanned aerial vehicles (UAVs, or “drones”) for various disaster and/or catastrophe-related purposes. UAVs may collect data in an attempt to predict the occurrence and/or extent of a catastrophe and/or to mitigate the impact of a catastrophe before and, if not at that time, once it has occurred. The UAVs may perform various tasks such that the damage to property caused by a catastrophe (or potential catastrophe) may be eliminated or mitigated. The drone data may be transmitted by the UAVs to an external computing device, which may be associated with an insurer and used, with an insured's permission, to begin and/or facilitate an insurance claim process or other various insurance-related tasks. Damage to insured property may be estimated from the drone data, and proposed or estimated insurance claims may be generated for customer review, modification, or approval.

Abstract: A matching computer system for electronically generating, matching, and providing online user profiles, and determining a trust score for a user based upon at least social media data and insurance data is provided. The matching computer system may be configured to register users within the matching computer system, receive consent from the users to capture the social media data, and collect the social media data and the insurance data from each registered user. The matching computer system may be also configured to retrieve the social media data and the insurance data associated with each registered user. The matching computer system may be further configured to determine a trust score for each registered user based upon each respective social media data and each respective insurance data. Each trust score represents a level of trustworthiness of the user.

Abstract: Unmanned aerial vehicles (UAVs) may facilitate the generation of a virtual reconstruction model of a vehicle collision. UAVs may collect data (including images) related to the vehicle collision, such as with the insured's permission, which may be received by an external computing device associated with the insurer and utilized to perform a photogrammetric analysis of the images to determine vehicle impact points, the road layout at the scene of the collision, the speeds and directions of vehicles, etc. This data may be used to generate a virtual reconstruction model of the vehicle collision. An insurer may use the virtual reconstruction model to perform various insurance-related tasks, such as allocating fault to drivers or autonomous vehicles involved in the vehicle collision, and adjustment of insurance pricing based upon the fault allocation. As a result, innocent drivers or vehicles may not be unfairly penalized for vehicle collisions not their fault.

Abstract: Various techniques are described to facilitate the control of an unmanned aerial vehicle (UAV). A graphical user interface (GUI) is provided that allows a user to control a UAV using familiar gestures. The GUI may include live video that is captured and transmitted by a UAV, which may be displayed in a display window on a portable computing device. Upon a user interacting with the display window, the video may be updated to display a new UAV perspective by changing a zoom level, panning, rotating, etc., based upon the type of user interaction. In response to the user interaction, a command may be generated and transmitted to the UAV, causing the UAV to navigate to a location to reflect the change in perspective. Upon the UAV moving to the new position, the live video data that is displayed may match the perspective indicated by the user gesture.

Abstract: Systems and methods are described for using data collected by unmanned aerial vehicles (UAVs) to generate insurance claim estimates that an insured individual may quickly review, approve, or modify. When an insurance-related event occurs, such as a vehicle collision, crash, or disaster, one or more UAVs are dispatched to the scene of the event to collect various data, including data related to vehicle or real property (insured asset) damage. With the insured's permission or consent, the data collected by the UAVs may then be analyzed to generate an estimated insurance claim for the insured. The estimated insurance claim may be sent to the insured individual, such as to their mobile device via wireless communication or data transmission, for subsequent review and approval. As a result, insurance claim handling and/or the online customer experience may be enhanced.

Abstract: Unmanned aerial vehicles (UAVs) may facilitate insurance-related tasks. UAVs may actively be dispatched to an insured asset and the area surrounding an insured asset, such as with the policyholder or insured's permission and collect data related to the insured asset, such as images, video, audio, weather conditions, thermal signatures, wood and soil samples, etc., and transmit this data to a computing device. The computing device may be associated with and/or utilized by an insurance provider to perform insurance-related tasks, such as processing the data to determine an amount of risk associated with the insured asset. If the amount of risk has increased, the computing device may provide a recommendation to a mobile device of the policyholder on how to reduce the risk such that corrective action may be taken. Insurance discounts may be provided based upon following recommendations that mitigate risk.

Abstract: Unmanned aerial vehicles (UAVs) may facilitate insurance-related tasks. UAVs may actively be dispatched to an area surrounding an insured or potentially insured asset, such as with the insurance customer's permission, and collect data related to the insured or potentially insured asset, such as size, height, roof shape, materials (siding, roofing), etc. which may form a basis of the underwriting detail used to evaluate a property. The drone data may reveal site characteristics, such as slope or grade of a parcel; the proximity to other structures (and their uses); trees; rivers; coastlines; and earthquake faults. The drone data may be used by an insurance provider remote server to assess the risk associated with an insured asset, generate or modify an insurance premium or discount, etc. The drone data may also be used to mitigate risk and prevent loss by alerting policyholders of the risk such that corrective action may be taken.

Abstract: A computer-based method for maintaining an autonomous or self-driving vehicle is provided. The method is implemented using a vehicle controlling (“VC”) computer device installed on the vehicle. The method may include determining that a maintenance operation is required for the self-driving vehicle, retrieving an operator schedule for an operator of the self-driving vehicle, retrieving a facility schedule for a facility, determining a time for performing the maintenance operation based upon the operator schedule, the facility schedule, and an amount of time required to (i) complete the maintenance operation, (ii) drive the self-driving vehicle from a first location to the facility to arrive at the determined time, and (iii) drive the self-driving vehicle to a second location, instructing the self-driving vehicle to drive from the first location to the facility to arrive at the determined time; and/or instructing the self-driving vehicle to drive from the facility a second location.

Abstract: Unmanned aerial vehicles (UAVs) may facilitate insurance-related tasks. UAVs may actively survey an area or be dispatched to the scene of a vehicle collision or crash, such as with an insured's permission, and collect data related to the vehicle collision or crash, such as vehicle data, insurer data, images, video, audio, weather conditions, etc., and transmit this data to a computing device. The computing device may be associated with an insurer and/or utilized by an insurer to perform insurance-related tasks, such as processing the data to assign fault to one or more parties or vehicles, such as autonomous vehicles, involved in the vehicle collision or crash, using the fault assignment to open or otherwise process an insurance claim, modifying a premium price, updating qualified discounts, etc. The drone data may also assist an insurer in opening an insurance claim by prepopulating fields associated with a submitted claim form.

Abstract: A computer system for verifying hail damage and/or detecting hail fraud includes a processor and a non-transitory, tangible, computer-readable storage medium having instructions stored thereon that, in response to execution by the processor, cause the processor to perform operations including: (i) receiving at least one image of at least a portion of a rooftop; (ii) analyzing the at least one image to identify a plurality of damaged locations; (iii) analyzing damaged locations to determine a distance between each of the damaged locations; and (iv) determining, based upon the analyzing, whether the damaged locations are a result of hail damage by determining the distance between at least some of damaged locations.