MANAGING VEHICLE OPERATOR PROFILES BASED ON 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 a one or more party-specific predictive models based at least in part upon the sensor data set associated with the vehicle operator, each party-specific predictive model of the one or more party-specific predictive models being provided by one marketplace participant of the plurality of marketplace participants and having a plurality of weights and biases provided by the marketplace participant from which the party-specific predictive model is provided;

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, for each marketplace participant of the plurality of marketplace participants, a predicted profitability 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, for each marketplace participant of the plurality of marketplace participants, the predicted profitability using a profitability predictive model provided by the marketplace participant having a plurality of profitability weights and profitability biases that correspond to the importance of each type of sensor data in the determination of the predicted profitability to the marketplace participant.

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

determining and continually updating, for each marketplace participant of the plurality of marketplace participants, 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.

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

determining and continually updating, for each marketplace participant of the plurality of marketplace participants, a predicted losses using a loss predictive model provided by the marketplace participant and having a plurality of losses weights and losses biases; and

determining and continually updating, for each marketplace participant of the plurality of marketplace participants, a predicted expenses using an expenses predictive model provided by the marketplace participant and having a plurality of expenses weights and expenses biases.

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

providing an input interface configured for marketplace participants to provide the one or more party-specific predictive models;

wherein each party-specific predictive model of the one or more party-specific predictive models is hidden from the plurality of marketplace participants except for the marketplace participant from which the party-specific predictive model is provided.

7 . 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.

8 . The computer-implemented method of claim 7 , 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.

9 . 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.

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 a one or more party-specific predictive models based at least in part upon the sensor data set associated with the vehicle operator, each party-specific predictive model of the one or more party-specific predictive models being provided by one marketplace participant of the plurality of marketplace participants and having a plurality of weights and biases provided by the marketplace participant from which the party-specific predictive model is provided;

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

listing arid 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, for each marketplace participant of the plurality of marketplace participants, a predicted profitability based at least in part 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, for each marketplace participant of the plurality of marketplace participants, the predicted profitability using a profitability predictive model provided by the marketplace participant having t plurality of profitability weights and profitability biases that correspond to the importance of each type of sensor data in the determination of the predicted profitability to the marketplace participant.

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

determining and continually updating, for each marketplace participant of the plurality of marketplace participants, a predicted costs and a predicted revenue basal at least in part upon the associated continually received personal data set and the associated continually received sensor data set.

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

determining and continually updating, for each marketplace participant of the plurality of marketplace participants, a predicted losses using a loss predictive model provided by the marketplace participant and having a plurality of losses weights and losses biases; and

determining and continually updating, for each marketplace participant of the plurality of marketplace participants, a predicted expenses using an expenses predictive model provided by the marketplace participant and having a plurality of expenses weights and expenses biases.

15 . The computer system of claim 10 , wherein, the memory, upon execution by the one or more processors, further cause the computing system to perform one or more processes including:

provide an input interface configured for marketplace participants to provide the one or more party-specific predictive models;

wherein each party-specific predictive model of the one or more party-specific predictive models is hidden from the plurality of marketplace participants except for the marketplace participant from which the party-specific predictive model is provided.

16 . 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.

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

18 . 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.

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 party-specific predictive models based at least in part upon the sensor data set associated with the vehicle operator, each party-specific predictive model of the one or more party-specific predictive models being provided by one marketplace participant of the plurality of marketplace participants and having a plurality of weights and biases provided by the marketplace participant from which the party-specific predictive model is provided;

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 tire computing system to perform one or more processes including:

determining and continually updating, for each marketplace participant of the plurality of marketplace participants, a predicted profitability based at least in part upon the associated continually received personal data set and the associated continually received sensor data set.