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: An on-demand insurance (ODI) server for generating dynamic user offerings may be provided. The ODI server may include at least one processor in communication with a memory device. The at least one processor may be programmed to (i) receive, from a user computing device associated with a user, an insurance policy request for a trip from a start location to an end location, (ii) determine at least one transportation mode available for the trip, (iii) access contextual data associated with the trip, (iv) assess a risk associated with the at least one transportation mode, (v) calculate a risk score associated with the at least one transportation mode based upon at least the contextual data, (vi) generate an insurance offering associated with the at least one transportation mode, and/or (vii) transmit the insurance offering in real time to the user computing device for purchase by the user.

Abstract: A user analytics computing device for processing mobile device telematics data includes a processor in communication with a memory device. The processor is programmed to: (i) store a model to predict a travel mode for a user based upon historical telematics data, (ii) form a first group by assigning a user to the first group, (iii) receive telematics data associated with movement of the user, (iv) input the telematics data into the model to determine a travel mode of the user, (v) parse subsets of the telematics data based upon the determined travel modes, (vi) retrieve an eligibility condition defining eligibility to qualify for a user offering, (vii) aggregate one subset of the telematics data associated with the first travel mode of the user, (viii) determine that the group telematics data satisfies the eligibility condition, and (ix) cause a notification to be displayed on the mobile device of the user.

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: An on-demand insurance (ODI) server for generating dynamic user offerings may be provided. The ODI server may include at least one processor in communication with a memory device. The at least one processor may be programmed to (i) receive, from a user computing device associated with a user, an insurance policy request for a trip from a start location to an end location, (ii) determine at least one transportation mode available for the trip, (iii) access contextual data associated with the trip, (iv) assess a risk associated with the at least one transportation mode, (v) calculate a risk score associated with the at least one transportation mode based upon at least the contextual data, (vi) generate an insurance offering associated with the at least one transportation mode, and/or (vii) transmit the insurance offering in real time to the user computing device for purchase by the user.

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 vehicle routing system includes a vehicle routing and analytics (VRA) computing device, one or more databases, and one or more vehicles communicatively coupled to the VRA computing device. The VRA computing device is configured to generate an optimal route for a vehicle to travel that maximizes potential revenue for operation of the vehicle, the optimal route including a schedule of a plurality of tasks, and generate analytics associated with operation of the vehicle. The VRA computing device is further configured to provide a management hub software application accessible by vehicle users associated with vehicles, tasks sources, and other users.

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: A vehicle routing system includes a vehicle routing and analytics (VRA) computing device, one or more databases, and one or more vehicles communicatively coupled to the VRA computing device. The VRA computing device is configured to generate an optimal route for a vehicle to travel that maximizes potential revenue for operation of the vehicle, the optimal route including a schedule of a plurality of tasks, and generate analytics associated with operation of the vehicle. The VRA computing device is further configured to provide a management hub software application accessible by vehicle users associated with vehicles, tasks sources, and other users.

Abstract: A vehicle routing system includes a vehicle routing and analytics (VRA) computing device, one or more databases, and one or more vehicles communicatively coupled to the VRA computing device. The VRA computing device is configured to generate an optimal route for a vehicle to travel that maximizes potential revenue for operation of the vehicle, the optimal route including a schedule of a plurality of tasks, and generate analytics associated with operation of the vehicle. The VRA computing device is further configured to provide a management hub software application accessible by vehicle users associated with vehicles, tasks sources, and other users.

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: A vehicle routing system includes a vehicle routing and analytics (VRA) computing device, one or more databases, and one or more vehicles communicatively coupled to the VRA computing device. The VRA computing device is configured to generate an optimal route for a vehicle to travel that maximizes potential revenue for operation of the vehicle, the optimal route including a schedule of a plurality of tasks, and generate analytics associated with operation of the vehicle. The VRA computing device is further configured to provide a management hub software application accessible by vehicle users associated with vehicles, tasks sources, and other users.

Abstract: A vehicle routing system includes a vehicle routing and analytics (VRA) computing device, one or more databases, and one or more vehicles communicatively coupled to the VRA computing device. The VRA computing device is configured to generate an optimal route for a vehicle to travel that maximizes potential revenue for operation of the vehicle, the optimal route including a schedule of a plurality of tasks, and generate analytics associated with operation of the vehicle. The VRA computing device is further configured to provide a management hub software application accessible by vehicle users associated with vehicles, tasks sources, and other users.

Abstract: A vehicle routing system includes a vehicle routing and analytics (VRA) computing device, one or more databases, and one or more vehicles communicatively coupled to the VRA computing device. The VRA computing device is configured to generate an optimal route for a vehicle to travel that maximizes potential revenue for operation of the vehicle, the optimal route including a schedule of a plurality of tasks, and generate analytics associated with operation of the vehicle. The VRA computing device is further configured to provide a management hub software application accessible by vehicle users associated with vehicles, tasks sources, and other users.

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: A property sharing insurance management (“PSIM”) computing device for analyzing data from a property sharing platform to adjust insurance premiums for an offerer of a property may be provided. The PSIM computing device may include at least one processor programmed to (i) receive, from a data source, a plurality of property data, (ii) store the property data in a plurality of data records in a database, wherein each data record is associated with one property and stores the plurality of property data for that property, (iii) analyze the property data for the property, (iv) determine a percentage of time that the property is used for commercial purposes in an insurance billing cycle, and (v) process one or more adjusted insurance premiums for the offerer based upon the determined percentage of time that the property is used for commercial purposes in the insurance billing cycle.

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.