Systems and methods for complex process flow approval using distributed ledgers are disclosed. The method may include generating a process initiation message based on input from a second service provider or a user. The method may include recording the process initiation message on a first distributed ledger. The method may include monitoring the first distributed ledger for an indication of an approval event. The method may include generating a settlement event based on the indication of the approval event. The method may include recording the settlement event on the first distributed ledger. The method may include communicating a settlement event message to a second distributed ledger. The method may include generating a virtual payment instrument associated with the settlement event message, the indication of the approval event, and the process initiation message.

Methods and systems for automatically deploying an autonomous drone from a vehicle in response to a triggering event or accident so that data associated with the triggering event or accident may be automatically obtained are described. In one embodiment, a method for deploying an autonomous drone in response to a triggering event is described. The method includes providing an autonomous drone in a vehicle. The method also includes detecting a triggering event associated with the vehicle. Upon detection of the triggering event, the method includes automatically deploying the autonomous drone from the vehicle. The method further includes implementing, by the autonomous drone, a plurality of automatic actions, including recording data associated with the vehicle in which the autonomous drone is provided.

Methods and systems for automatically deploying an autonomous drone from a vehicle in response to a triggering event or accident so that data associated with the triggering event or accident may be automatically obtained are described. In one embodiment, a method for deploying an autonomous drone in response to a triggering event is described. The method includes providing an autonomous drone in a vehicle. The method also includes detecting a triggering event associated with the vehicle. Upon detection of the triggering event, the method includes automatically deploying the autonomous drone from the vehicle. The method further includes implementing, by the autonomous drone, a plurality of automatic actions, including recording data associated with the vehicle in which the autonomous drone is provided.

Methods and systems for monitoring use and determining risks associated with operation of a vehicle having one or more autonomous operation features are provided. According to certain aspects, operating data may be recorded during operation of the vehicle. This may include information regarding the vehicle, the vehicle environment, use of the autonomous operation features, and/or control decisions made by the features. The control decisions may include actions the feature would have taken to control the vehicle, but which were not taken because a vehicle operator was controlling the relevant aspect of vehicle operation at the time. The operating data may be recorded in a log, which may then be used to determine risk levels associated with vehicle operation based upon risk levels associated with the autonomous operation features. The risk levels may further be used to adjust an insurance policy associated with the vehicle.

Methods and systems for monitoring use and determining risks associated with operation of a vehicle having one or more autonomous operation features are provided. According to certain aspects, operating data may be recorded during operation of the vehicle. This may include information regarding the vehicle, the vehicle environment, use of the autonomous operation features, and/or control decisions made by the features. The control decisions may include actions the feature would have taken to control the vehicle, but which were not taken because a vehicle operator was controlling the relevant aspect of vehicle operation at the time. The operating data may be recorded in a log, which may then be used to determine risk levels associated with vehicle operation based upon risk levels associated with the autonomous operation features. The risk levels may further be used to adjust an insurance policy associated with the vehicle.

Computing systems for vehicle diagnostics are provided. In accordance with some aspects, a computing system may receive, from a vehicle (e.g., from a computing device installed in and/or at the vehicle), a diagnostic code generated by an on-board diagnostic (OBD) system of the vehicle. The computing system may determine an issue with the vehicle based on the diagnostic code and may determine, based on the issue, a remedial action for addressing the issue and a timeframe for performing the remedial action. The computing system may store data identifying the issue, the remedial action, and the timeframe in a record associated with the vehicle.

Computing systems for vehicle diagnostics are provided. In accordance with some aspects, a computing system may receive, from a vehicle (e.g., from a computing device installed in and/or at the vehicle), a diagnostic code generated by an on-board diagnostic (OBD) system of the vehicle. The computing system may determine an issue with the vehicle based on the diagnostic code and may determine, based on the issue, a remedial action for addressing the issue and a timeframe for performing the remedial action. The computing system may store data identifying the issue, the remedial action, and the timeframe in a record associated with the vehicle.

Systems and methods in accordance with aspects of this disclosure may be provided to determine and calculate an overall driving risk index value corresponding to a driver and scene configuration. The overall driving risk index value may provide driving risk modeling and estimation at a personalized driving level. In some cases, the overall driving risk index value may be determined using a risk-predictive modeling system with weighting and machine learning and may include one or more of: a driver score system, a driver-contextual risk score system, and a conflict index system.

A system and method are presented in which known genetic attributes associated with a condition are used to seed the determination of additional attributes which are associated with the condition. Based on the learning, the additional attributes (genetic, behavioral, or both) provide for an increased correlation between the combined attributes and the condition. For behavioral attributes, a measure of the impact of the behavioral attribute on the risk of the condition can be transmitted to another device or system.

A system and method are presented in which known genetic attributes associated with a condition are used to seed the determination of additional attributes which are associated with the condition. Based on the learning, the additional attributes (genetic, behavioral, or both) provide for an increased correlation between the combined attributes and the condition. For behavioral attributes, a measure of the impact of the behavioral attribute on the risk of the condition can be transmitted to another device or system.