Reducing asymmetric information with usage-based automobile insurance

Abstract

Automobile insurers currently use available information about the vehicle, the owner and residential area when determining the probability of a claim (insurance risk). A drawback is that several risk classification variables are based on the policyholder’s self-reported risk. This study highlights the fact that the information asymmetry associated with classifying risk may cause unfair premiums, since it is possible for high risk drivers to mimic low risk drivers. The aim of this paper is to explore the possibility of reducing information asymmetries by introducing a Usage Based Insurance (UBI) option where the driving behavior is monitored. While most models focus on identifying the high risk type, this approach provides an opportunity for the low risk individuals to reveal their type. The results suggest that voluntary UBI is an efficient instrument to separate risks and that the low risk drivers do not suffer the utility loss generally associated with asymmetric information. Introducing UBI as an additional contract enables full coverage at an actuarially fair premium for both types of policyholders. Besides, by reducing information asymmetries UBI can, in a wider perspective, provide incentives for the high risk driver to become a low risk driver by reducing risk-taking behavior.