Mitigating Moral Hazard in Cyber Insurance Using Risk Preference Design

TL;DR

This paper introduces a framework for designing risk preferences in cyber insurance to reduce moral hazard, improve contract efficiency, and enhance cybersecurity resilience in cyber-physical systems.

Contribution

It proposes a novel risk preference design approach that enables incentive-compatible contracts and provides a quantitative method to mitigate moral hazard in cyber insurance.

Findings

Optimal contracts are monotone in outcomes.

Linear contracts are practically feasible.

Risk preference design can effectively reduce moral hazard.

Abstract

Cyber insurance is a risk-sharing mechanism that can improve cyber-physical systems (CPS) security and resilience. The risk preference of the insured plays an important role in cyber insurance markets. With the advances in information technologies, it can be reshaped through nudging, marketing, or other types of information campaigns. In this paper, we propose a framework of risk preference design for a class of principal-agent cyber insurance problems. It creates an additional dimension of freedom for the insurer for designing incentive-compatible and welfare-maximizing cyber insurance contracts. Furthermore, this approach enables a quantitative approach to reduce the moral hazard that arises from information asymmetry between the insured and the insurer. We characterize the conditions under which the optimal contract is monotone in the outcome. This justifies the feasibility of linear contracts in practice. This work establishes a metric to quantify the intensity of moral hazard and create a theoretic underpinning for controlling moral hazard through risk preference design. We use a linear contract case study to show numerical results and demonstrate its role in strengthening CPS security.