SYSTEMS AND METHODS FOR EVENT EVALUATION BASED ON CHANGE IN TELEMATICS INFERENCES VIA A TELEMATICS MARKETPLACE

1 . A computer-implemented method for data management, the computer-implemented method comprising:

collecting a first set of operator data associated with a group of vehicle operators during a first time period prior to a user management event, the first set of operator data including a first set of personal data, a first set of sensor data, and a first set of user management data;

applying the user management event to the group of vehicle operators, the group of vehicle operators being managed by a marketplace participant;

collecting a second set of operator data associated with the group of vehicle operators continually during a second time period after the user management event, the second set of operator data including a second set of personal data, a second set of sensor data, and a second set of user management data;

determining a first set of telematics inferences based at least in part upon the first set of sensor data, the first set of telematics inferences being indicative of at least the driving characteristics exhibited by the group of vehicle operators during the first time period;

determining and continually updating a second set of telematics inferences based at least in part upon the second set of sensor data during the second time period, the second set of telematics inferences being indicative of at least the driving characteristics exhibited by the group of vehicle operators during the second time period;

determining and continually updating an event evaluation based at least in part upon one or more differences between the first set of telematics inferences and the second set of telematics inferences; and

transmitting the event evaluation to the marketplace participant continually.

2 . The computer-implemented method of claim 1 , wherein:

the determining the first set of telematics inferences includes determining a first predicted profitability based at least in part upon the first set of personal data and the first set of sensor data; and

the determining and continually updating the second set of telematics inferences includes determining and continually updating a second predicted profitability based at least in part upon the second set of personal data and the second set of sensor data.

3 . The computer-implemented method of claim 2 , wherein, the determining and continually updating an event evaluation:

determining and continually updating one or more differences between the first predicted profitability and the second predicted profitability.

4 . The computer-implemented method of claim 1 , wherein:

the determining the first set of telematics inferences includes determining a first predicted costs and a first predicted expenses based at least in part upon the first set of personal data and the first set of sensor data; and

the determining and continually updating the second set of telematics inferences includes determining and continually updating a second predicted costs and a second predicted expenses based at least in pant upon the second set of personal data and the second set of sensor data.

5 . The computer-implemented method of claim 4 , wherein, the determining and continually updating an event evaluation includes:

determining and continually updating one or more differences between the first predicted costs and the second predicted costs; and

determining and continually updating one or more differences between the first predicted expenses and the second predicted expenses.

6 . The computer-implemented method of claim 1 , wherein:

the first set of sensor data and the second set of sensor data are collected via one or more common sensing modules used by a plurality of mobile applications;

the one or more common sensing modules includes a software module or a common hardware module; and

each vehicle operator of the group of vehicle operators uses at least one mobile application of the plurality of mobile applications.

7 . The computer-implemented method of claim 1 , wherein, the management event includes modifying a policy premium, modifying a risk allowance, modifying a user incentive, or issuing a user challenge.

8 . The computer-implemented method of claim 1 , wherein, the user management data includes historic customer service expenses, historic user experience costs, historic user acquisition costs, historic user retention costs, historic claim losses, or historic referral revenue.

9 . The computer-implemented method of claim 1 , wherein, the one or more differences between the first set of telematics inferences and the second set of telematics inferences includes one or more differences in profitability scores, reliability scores, financial stability scores, financial reliability scores, demographic scores, mobility scores, predicted risk scores, predicted costs scores, predicted retention scores, or payment reliability scores.

10 . A computing system for data management, the computing system comprising:

one or more processors, and

a memory storing instructions that, upon execution by the one or more processors, cause the computing system to perform one or more processes including:

collecting a first set of operator data associated with a group of vehicle operators during a first time period prior to a user management event, the first set of operator data including a first set of personal data, a first set of sensor data, and a first set of user management data;

applying the user management event to the group of vehicle operators, the group of vehicle operators being managed by a marketplace participant;

collecting a second set of operator data associated with the group of vehicle operators continually during a second time period after the user management event, the second set of operator data including a second set of personal data, a second set of sensor data, and a second set of user management data;

determining a first set of telematics inferences based at least in part upon the first set of sensor data, the first set of telematics inferences being indicative of at least the driving characteristics exhibited by the group of vehicle operators during the first time period;

determining and continually updating a second set of telematics inferences based at least in part upon the second set of sensor data during the second time period, the second set of telematics inferences being indicative of at least the driving characteristics exhibited by the group of vehicle operators during the second time period;

determining and continually updating an event evaluation based at least in part upon one or more differences between the first set of telematics inferences and the second set of telematics inferences; and

transmitting the event evaluation to the marketplace participant continually.

11 . The computer system of claim 10 , wherein:

the determining the first set of telematics inferences includes determining a first predicted profitability based at least in part upon the first set of personal data and the first set of sensor data; and

the determining and continually updating the second set of telematics inferences includes determining and continually updating a second predicted profitability based at least in part upon the second set of personal data and the second set of sensor data.

12 . The computer system of claim 11 , wherein, the determining and continually updating an event evaluation:

determining and continually updating one or more differences between the first predicted profitability and the second predicted profitability.

13 . The computer system of claim 10 , wherein:

the determining the first set of telematics inferences includes determining a first predicted costs and a first predicted expenses based at least in part upon the first set of personal data and the first set of sensor data; and

the determining and continually updating the second set of telematics inferences includes determining and continually updating a second predicted costs and a second predicted expenses based at least in part upon the second set of personal data and the second set of sensor data.

14 . The computer system of claim 13 , wherein, the determining and continually updating an event evaluation includes:

determining and continually updating one or more differences between the first predicted costs and the second predicted costs; and

determining and continually updating one or more differences between the first predicted expenses and the second predicted expenses.

15 . The computer system of claim 10 , wherein:

the first set of sensor data and the second set of sensor data are collected via one or more common sensing modules used by a plurality of mobile applications;

the one or more common sensing modules includes a software module or a common hardware module; and

each vehicle operator of the group of vehicle operators uses at least one mobile application of the plurality of mobile applications.

16 . The computer system of claim 10 , wherein, the management event includes modifying a policy premium, modifying a risk allowance, modifying a user incentive, or issuing a user challenge.

17 . The computer system of claim 10 , wherein, the user management data includes historic customer service expenses, historic user experience costs, historic user acquisition costs, historic user retention costs, historic claim losses, or historic referral revenue.

18 . The computer system of claim 10 , wherein, the one or more differences between the first set of telematics inferences and the second set of telematics inferences includes one or more differences in profitability scores, reliability scores, financial stability scores, financial reliability scores, demographic scores, mobility scores, predicted risk scores, predicted costs scores, predicted retention scores, or payment reliability scores.

19 . A non-transitory computer-readable medium storing instructions for data management, the instructions upon execution by one or more processors of a computing system, cause the computing system to perform one or more processes including:

collecting a first set of operator data associated with a group of vehicle operators during a first time period prior to a user management event, the first set of operator data including a first set of personal data, a first set of sensor data, and a first set of user management data;

applying the user management event to the group of vehicle operator, the group of vehicle operators being managed by a marketplace participant;

collecting a second set of operator data associated with the group of vehicle operators continually during a second time period after the user management event, the second set of operator data including a second set of personal data, a second set of sensor data, and a second set of user management data;

determining a first set of telematics inferences based at least in part upon the first set of sensor data, the first set of telematics inferences being indicative of at least the driving characteristics exhibited by the group of vehicle operators during the first time period;

determining and continually updating a second set of telematics inferences based at least in pan upon the second set of sensor data during the second time period, the second set of telematics inferences being indicative of at least the driving characteristics exhibited by the group of vehicle operators during the second time period;

determining and continually updating an event evaluation based at least in part upon one or more differences between the first set of telematics inferences and the second set of telematics inferences; and

transmitting the event evaluation to the marketplace participant continually.

20 . The non-transitory computer-readable medium of claim 19 , wherein:

the determining the first set of telematics inferences includes determining a first predicted profitability based at least in pan upon the first set of personal data and the first set of sensor data; and

the determining and continually updating the second set of telematics inferences includes determining and continually updating a second predicted profitability based at least in part upon the second set of personal data and the second set of sensor data.