An Empirical Investigation of Asymmetric Information in China’s Automobile Insurance Market

In this paper, we investigate the asymmetric information in China’s automobile insurance market and propose a set of risk classification approaches to alleviate it. Using a unique data set of automobile insurance coverage in China from 2011 to 2013, we discover that policyholders who purchase more insurance coverage are riskier, which indicates the presence of information asymmetry in China’s automobile insurance market. Controlling the attributes of the automobiles does not affect the main results. Moreover, based on data mining technology, we find that the risk classification approach is able to mitigate the problem of asymmetric information in China’s automobile insurance market to some extent with little additional cost.