The optimal pricing strategy for an insurer when risk preferences are stochastically distributed

The present paper analyzes the demand for insurance when the insurer has incomplete information about types of potential customers. We assume that customers' risk preferences cannot be distinguished by the insurer. Therefore, the standard result in insurance economics that the insurer discriminates perfectly in prices cannot be applied. Instead, the present article examines the optimal pricing rule for an insurer faced with stochastic distribution of risk preferences. Within this general model framework, we show that an optimal strategy always exists. Both fixed and proportionate premium loadings (relative to expected loss) are considered.