A new approach to data can help insurers become AVs enablers
According to market analysts, autonomous vehicle insurance policies would generate at least 81 billion USD in new insurance revenues by 2025. Insurers who find a way to calculate and price technologies that have new data types and unknown risk factors, will have a strong advantage.
Currently there is no critical mass of real data available; insurers have almost zero data to use in their calculations to write their policies, and with AV prototypes being mostly tested with safety drivers on board, it will take time until a large volume of realistic data can be collected.
The solution can come from massive simulation engines and synthetic data: simulating the most complex and heterogeneous context conditions would allow to gain knowledge about the impact on risk profiles. Meaningful edge cases and complex scenarios for the type of deployment location can also be generated.
In trucking insurance, the adoption of telematics and ADAS during the last decade has allowed insurers to gather data about vehicle location, engine diagnostics and driver behaviour. However there is an enormous gap between ADAS today and the complexity of behavioural models going into L4 systems insurance.