Good drivers pay less: A study of usage-based vehicle insurance models

Usage-based insurance (UBI) has been attracting more and more attention; however, two open research questions are how behavioral data of drivers affects driving risk and how driver behavior should affect UBI pricing schemas. This paper proposes a driver risk classification model to evaluate the risk level of drivers based on in-car sensor data. A Behavior-centric Vehicle Insurance Pricing model (BVIP) and a vehicle premium calculation prototype are developed in this paper. Based on empirical data, our research results show that BVIP achieves better accuracy in terms of risk-level classification and the prototype achieves good performance in terms of effectiveness and usability.