Abstract: A matching computer system for electronically generating, matching, and providing online user profiles, and determining a sharing score between the online user profiles is provided. The matching computer system may be configured to generate online user profiles associated with users of the systems. The matching computer system may be also configured to calculate a base score based upon the generated online user profile. Each base score represents a level of trustworthiness of each respective user. The matching computer system may be further configured to determine a sharing score between users based upon the base scores. Each sharing score represents a level of matching between the online user profiles.

Abstract: A personalized insurance (“PI”) computing device for determining an optimal insurance product for a driver operating a vehicle for a transportation network company (“TNC”) during a period of increased demand includes at least one processor in communication with at least one memory. The processor is configured to: (i) receive, from a TNC, data indicating increased demand for transportation services, (ii) retrieve driver data that includes the driver history, (iii) generate an optimal pricing model for the driver based upon the increased demand and the driver data, (iv) execute the model to determine an optimal insurance product having characteristics reflecting at least one risk factor associated with the increased demand for transportation services and a risk profile determined from analyzing the driver data, and (v) transmit an offer to the driver to provide transportation services at an increased earnings rate and with the determined optimal insurance product.

Abstract: A method and system may survey a property using aerial images captured from an unmanned aerial vehicle (UAV), a manned aerial vehicle (MAV) or from a satellite device. The method may include identifying a commercial property for a UAV to perform surveillance, and directing the UAV to hover over the commercial property and capture aerial images at predetermined time intervals. Furthermore, the method may include receiving the aerial images of the commercial property captured at the predetermined time intervals, detecting a surveillance event at the commercial property, generating a surveillance alert, and transmitting the surveillance alert to an electronic device associated with an owner of the commercial property.

Abstract: A personalized insurance (“PI”) computing device for determining an optimal insurance product for a driver operating a vehicle for a transportation network company (“TNC”) during a period of increased demand includes at least one processor in communication with at least one memory. The processor is configured to: (i) receive, from a TNC, data indicating increased demand for transportation services, (ii) retrieve driver data that includes the driver history, (iii) generate an optimal pricing model for the driver based upon the increased demand and the driver data, (iv) execute the model to determine an optimal insurance product having characteristics reflecting at least one risk factor associated with the increased demand for transportation services and a risk profile determined from analyzing the driver data, and (v) transmit an offer to the driver to provide transportation services at an increased earnings rate and with the determined optimal insurance product.

Abstract: Unmanned aerial vehicles (UAVs) may facilitate insurance-related tasks. UAVs may actively be dispatched to an area surrounding a property, and collect data related to property. A location for an inspection of a property to be conducted by a UAV may be received, and one or more images depicting a view of the location may be displayed via a user interface. Additionally, a geofence boundary may be determined based on an area corresponding to a property boundary, where the geofence boundary represents a geospatial boundary in which to limit flight of the UAV. Furthermore, a navigation route may be determined which corresponds to the geofence boundary for inspection of the property by the UAV, the navigation route having waypoints, each waypoint indicating a location for the UAV to obtain drone data. The UAV may be directed around the property using the determined navigation route.

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: A user analytics computing device for processing mobile device telematics data and generating user offerings includes at least one processor in communication with a memory device. The processor is programmed to: (i) form a first group, (ii) receive first telematics data, (iii) parse subsets of the first telematics data, (iv) receive second telematics data, (v) parse subsets of the second telematics data, (vi) retrieve at least one eligibility condition that defines eligibility for the first group to qualify for a user offering, (vii) aggregate one subset of the first telematics data and one subset of the second telematics data associated into first group telematics data, (viii) determine whether the first group telematics data satisfies the at least one eligibility condition, and (ix) compare the first group telematics data to a plurality of other group telematics data to determine whether the first group has won the user offering.

Abstract: A matching computer system for electronically generating, matching, and providing online user profiles, and determining a sharing score between the online user profiles is provided. The matching computer system may be configured to generate online user profiles associated with users of the systems. The matching computer system may be also configured to calculate a base score based upon the generated online user profile. Each base score represents a level of trustworthiness of each respective user. The matching computer system may be further configured to determine a sharing score between users based upon the base scores. Each sharing score represents a level of matching between the online user profiles.

Abstract: A personalized insurance (“PI”) computing device for determining an optimal insurance product for a driver operating a vehicle for a transportation network company (“TNC”) during a period of increased demand includes at least one processor in communication with at least one memory. The processor is configured to: (i) receive, from a TNC, data indicating increased demand for transportation services, (ii) retrieve driver data that includes the driver history, (iii) generate an optimal pricing model for the driver based upon the increased demand and the driver data, (iv) execute the model to determine an optimal insurance product having characteristics reflecting at least one risk factor associated with the increased demand for transportation services and a risk profile determined from analyzing the driver data, and (v) transmit an offer to the driver to provide transportation services at an increased earnings rate and with the determined optimal insurance product.

Abstract: The present embodiments may relate to systems for user mobility data analytics for a usage-based insurance platform. For instance, a user mobility analytics computing device may be configured to: (1) receive, from a user device, telematics data; (2) identify, from the telematics data, a plurality of trips; (3) identify, for each of the plurality of trips, a transportation mode based upon the telematics data; (4) build a trip database including the plurality of trips and trip data associated with each trip, the trip data including the transportation mode; (5) parse the trip data in the trip database to aggregate trip data associated with a particular transportation mode; (6) retrieve insurance policy data associated with an insurance policy and including a coverage type and a coverage amount; and (7) calculate an insurance premium based upon the aggregated trip data for the particular transportation mode and the insurance policy data.

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 also received. By analyzing the telematics data, one or more driving behaviors of the driver during the time period is/are identified. One or more characteristics of the rented vehicle are also determined. One or more penalties or incentives are caused to be applied to the driver, based on the driving behavior(s) and the one or more characteristics of the rented vehicle.

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.

Abstract: A computing device for analyzing data from a property sharing platform may be provided. The computing device may include a processor in communication with a memory device and the property sharing platform. The processor may be programmed to (i) receive a plurality of property data associated with commercial transactions of a plurality of properties, (ii) organize the received property data in a plurality of data records by date, (iii) identify patterns in the subset of property data for a selected property for a predetermined period of time, the patterns indicating when the selected property was used for commercial purposes during the predetermined period of time, and (iv) transmit content to a client device including the identified patterns and a percentage of time the selected property was used for commercial purposes during the predetermined period of time.

Abstract: Embodiments described herein receive telematics data collected over a period of time, wherein the telematics data is indicative of operation of a vehicle by an owner of the vehicle during the period of time; analyze the telematics data to identify driving behavior(s) of the owner during the period of time; predict one or more user preference values of a vehicle-sharing platform profile of the owner based on the identified one or more driving behaviors, wherein the one or more user preference values define one or more criteria for vehicle renters with whom the first vehicle can be shared; apply the one or more criteria to a potential vehicle renter; and cause an indication of the first vehicle of the owner to be displayed via a mobile device of the potential renter only if the potential vehicle renter satisfies the one or more criteria.

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 state of the traffic light 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.

Abstract: Unmanned aerial vehicles (UAVs) may facilitate insurance-related tasks. UAVs may actively be dispatched to an area surrounding a property, and collect data related to property. A location for an inspection of a property to be conducted by a UAV may be received, and one or more images depicting a view of the location may be displayed via a user interface. Additionally, a geofence boundary may be determined based on an area corresponding to a property boundary, where the geofence boundary represents a geospatial boundary in which to limit flight of the UAV. Furthermore, a navigation route may be determined which corresponds to the geofence boundary for inspection of the property by the UAV, the navigation route having waypoints, each waypoint indicating a location for the UAV to obtain drone data. The UAV may be directed around the property using the determined navigation route.

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 shape and a size of each of the damaged locations; and (vi) determining, based upon the analyzing, whether the damaged locations are a result of hail damage by comparing the shape and the size of at least one damaged location to the shape and the size of at least one other damaged location.

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: 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 also received. By analyzing the telematics data, one or more driving behaviors of the driver during the time period is/are identified. One or more characteristics of the rented vehicle are also determined. One or more penalties or incentives are caused to be applied to the driver, based on the driving behavior(s) and the one or more characteristics of the rented vehicle.

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 state of the traffic light 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.