MANAGING VEHICLE OPERATOR PROFILES BASED ON IMITATED PARTY-SPECIFIC TELEMATICS INFERENCES VIA A TELEMATICS MARKETPLACE

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

collecting a plurality of personal data sets associated with a plurality of vehicle operators continually;

collecting a plurality of sensor data sets associated with the plurality of vehicle operators continually via one or more sensing modules;

for each vehicle operator of the plurality of vehicle operators:

generating and continually updating an operator profile including the personal data set associated with the vehicle operator;

determining and continually updating one or more telematics inferences using one or more imitating predictive models based at least in part upon the sensor data set associated with the vehicle operator, each imitating predictive model of the plurality of imitating predictive models having a plurality of weights and biases determined based at least in part upon a plurality of inputs and outputs of one or more party-specific predictive models provided by the plurality of marketplace participants;

generating and continually updating a data profile including the one or more telematics inferences associated with the vehicle operator; and

listing and continually updating the data profile onto a telematics marketplace to be accessible by a plurality of marketplace participants;

receiving, from a requesting party of the plurality of marketplace participants, an information request for a target operator profile associated with a target data profile selected from the listed data profiles of the plurality of vehicle operators; and

transmitting, in response to the information request, the target operator profile to the requesting party.

2 . The computer-implemented method of claim 1 , wherein, the determining and continually updating one or more telematics inferences includes:

determining and continually updating a predicted profitability using a first imitating predictive model based at least in part upon the associated continually received personal data set and the associated continually received sensor data set.

3 . The computer-implemented method of claim 2 , wherein, the determining and continually updating the predicted profitability includes:

determining and continually updating a predicted costs and a predicted revenue based at least in part upon the associated continually received personal data set and the associated continually received sensor data set.

4 . The computer-implemented method of claim 4 , wherein, the determining and continually updating the predicted costs includes:

determining and continually updating a predicted losses using a second imitating predictive model; and

determining and continually updating a predicted expenses using a third imitating predictive model.

5 . The computer-implemented method of claim 1 , wherein, the determining and continually updating one or more telematics inferences includes:

determining the plurality of inputs and outputs of the one or more party-specific predictive models, the one or more party-specific predictive models having at least a common target industry, common target market, or a common target use; and

determining the plurality of weights and biases based at least in part upon the plurality of inputs and outputs.

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

the one or more sensing modules includes a common module used by a plurality of mobile applications;

the common module is a software module or a common hardware module, and

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

7 . The computer-implemented method of claim 6 , wherein, the plurality of mobile applications includes a system software application, an entertainment software application, a gaming software application, a navigation software application, or an environment software application.

8 . The computer-implemented method of claim 1 , wherein, the one or more telematics inferences includes a profitability score, a reliability score, a financial stability score, a financial reliability score, a demographic score, a mobility score, a predicted risk score, a predicted costs score, a predicted retention score, or a payment reliability score.

9 . The computer-implemented method of claim 1 , wherein, the personal data set includes vehicle operator-answered questionnaire data, application-usage data, device-usage data, internet-browsing data, or government data.

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 plurality of personal data sets associated with a plurality of vehicle operators continually;

collecting a plurality of sensor data sets associated with the plurality of vehicle operators continually via one or more sensing modules;

for each vehicle operator of the plurality of vehicle operators;

generating and continually updating an operator profile including the personal data set associated with the vehicle operator;

determining and continually updating one or more telematics inferences using one or more imitating predictive models based at least in part upon the sensor data set associated with the vehicle operator, each imitating predictive model of the plurality of imitating predictive models having a plurality of weights and biases determined based at least in part upon a plurality of inputs and outputs of one or more party-specific predictive models provided by the plurality of marketplace participants;

generating and continually updating a data profile including the one or more telematics inferences associated with the vehicle operator; and

listing and continually updating the data profile onto a telematics marketplace to be accessible by a plurality of marketplace participants;

receiving, from a requesting party of the plurality of marketplace participants, an information request for a target operator profile associated with a target data profile selected from the listed data profiles of the plurality of vehicle operators; and

transmitting, in response to the information request, the target operator profile to the requesting party.

11 . The computer system of claim 10 , wherein, the determining and continually updating one or more telematics inferences includes:

determining and continually updating a predicted profitability using a first imitating predictive model based at least in pan upon the associated continually received personal data set and the associated continually received sensor data set.

12 . The computer system of claim 11 , wherein, the determining and continually updating the predicted profitability includes:

determining and continually updating a predicted costs and a predicted revenue based at least in part upon the associated continually received personal data set and the associated continually received sensor data set.

13 . The computer system of claim 12 , wherein, the determining and continually updating the predicted costs includes:

determining and continually updating a predicted losses using a second imitating predictive model; and

determining and continually updating a predicted expenses using a third imitating predictive model.

14 . The computer system of claim 10 , wherein, the determining and continually updating one or more telematics inferences includes:

determining the plurality of inputs and outputs of the one or more party-specific predictive models, the one or more party-specific predictive models having at least a common target industry, common target market, or a common target use; and

determining the plurality of weights and biases based at least in part upon the plurality of inputs and outputs.

15 . The computer system of claim 10 , wherein

the one or more sensing modules includes a common module used by a plurality of mobile applications;

the common module is a software module or a common hardware module; and

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

16 . The computer system of claim 16 , wherein, the plurality of mobile applications includes a system software application, an entertainment software application, a gaming software application, a navigation software application, or an environment software application.

17 . The computer system of claim 10 , wherein, the one or more telematics inferences includes a profitability score, a reliability score, a financial stability score, a financial reliability score, a demographic score, a mobility score, a predicted risk score, a predicted costs score, a predicted retention score, or a payment reliability score.

18 . The computer system of claim 10 , wherein, the personal data set includes vehicle operator-answered questionnaire data, application-usage data, device-usage data, internet-browsing data, or government data.

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 plurality of personal data sets associated with a plurality of vehicle operators continually;

collecting a plurality of sensor data sets associated with the plurality of vehicle operators continually via one or more sensing modules;

for each vehicle operator of the plurality of vehicle operators:

generating and continually updating an operator profile including the personal data set associated with the vehicle operator;

determining and continually updating one or more telematics inferences using one or more imitating predictive models based at least in part upon the sensor data set associated with the vehicle operator, each imitating predictive model of the plurality of imitating predictive models having a plurality of weights and biases determined based at least in part upon a plurality of inputs and outputs of one or more party-specific predictive models provided by the plurality of marketplace participants;

generating and continually updating a data profile including the one or more telematics inferences associated with the vehicle operator; and

listing and continually updating the data profile onto a telematics marketplace to be accessible by a plurality of marketplace participants;

receiving, from a requesting party of the plurality of marketplace participants, an information request for a target operator profile associated with a target data profile selected from the listed data profiles of the plurality of vehicle operators; and

transmitting, in response to the information request, the target operator profile to the requesting party.

20 . The non-transitory computer-readable medium of claim 19 , the instructions upon execution by the one or more processors of the computing system, further cause the computing system to perform one or more processes including:

determining and continually updating a predicted profitability using a first imitating predictive model based at least in part upon the associated continually received personal data set and the associated continually received sensor data set.