Moral-Hazard-Free Optimal Insurance in Behavioral Finance Framework

This paper investigates Pareto optimal (PO, for short) insurance contracts in a behavioral finance framework, in which the insured evaluates contracts by the rank-dependent utility (RDU) theory and the insurer uses the expected value premium principle. The incentive compatibility constraint is taken into account, so the contracts are free of moral hazard arisen in Bernard et al. [3]. The problem is initially formulated as a non-concave maximization problem involving Choquet expectation, then turned into a quantile optimization problem and tackled by calculus of variations method. The optimal contracts are expressed by a double-obstacle ordinary differential equation for a semi-linear second-order elliptic operator with nonlocal boundary conditions. We provide a simple numerical scheme as well as a numerical example to calculate the optimal contracts. Let θ and m0 denote the relative safety loading and the mass of the potential loss at 0. We find that every moral-hazard-free contract is optimal for infinitely many RDU insureds if $0 < \theta < m_0/(1−m_0)$ contrast, some contracts such as the full coverage contract are never optimal for any RDU insured if $\theta >m_0/(1−m_0)$. We also derive all the PO contracts when either the compensation or the retention losses the monotonicity constraint