Modeling the blockchain-related insurance contracts with moral hazard and adverse selection

Abstract

Information asymmetry has been a challenging topic in the field of game theory, leading to numerous real-world dilemmas. It is common for the principal to simultaneously consider the adverse selection and moral hazard under realistic scenarios in order to manage various agents against the backdrop of principal-agent relationships. Concurrently, advancements in technology, such as artificial intelligence, blockchain and smart contract systems, offer new solutions to these dilemmas. Therefore, this work constructs a comprehensive theoretical framework to solve the bi-directional information asymmetry of moral hazard and adverse selection by use of the basic insurance model, and then analyzes the effect of blockchain technology on the insurance efficiency. Aiming to address those issues induced by information asymmetry, such as low-risk agents bearing additional risk burdens and losses in the market, an improved model is further proposed on the basis of federated blockchain. In the basic model, insurance companies design partial insurance contracts to mitigate the incentives for high-risk agents to disguise their risk levels; however, low-risk agents still face the suboptimal risk exposure. Furthermore, case analyses in multi-agent scenarios demonstrate that the introduction of blockchain, along with the characteristics of smart contracts and distributed ledgers, reduces various costs and alleviates the moral hazard through dynamically adjusted premium incentive mechanisms. Theoretical results indicate that when the adoption rate of blockchain and the cost function meet specific conditions, agents are more inclined to adopt blockchain technology, thereby reducing information rents and optimizing risk distribution. In general, this research provides a potential framework for the application of blockchain technology into the insurance under complex information asymmetry environments.