Value of Information framework for natural hazard insurance
本文提出一个数据驱动的决策框架，量化减少不确定性对自然灾害保险损失估计的益处，并应用于希腊帕特雷市地震风险保费设定，发现信息价值在高风险场景中最高。
Natural hazard insurance plays a critical role in managing financial risks of catastrophic events. Insurance pricing relies on understanding risk-related parameters, which are often subject to uncertainty. Many of these uncertainties can be reduced through targeted data collection, leading to more realistic loss estimates. Incorrect estimates may result in underinsurance or excessive coverage, both carrying financial consequences. By aligning premiums more closely with actual risk, insurers maintain financial stability, while policyholders avoid overpaying or being inadequately covered. This article presents a data-informed decision-making framework that quantifies the benefits of reducing uncertainty and improving loss estimates in natural hazard insurance. It is applied to the challenge of setting insurance premiums for a building exposed to seismic hazard in Patras, Greece. Using Value of Information ( VoI ) analysis, the study evaluates how acquiring additional data can enhance risk assessment accuracy. Results show that VoI is highest in high-risk scenarios, where uncertainty amplifies potential financial losses, and decreases in lower-risk settings. While data collection often benefits policyholders by reducing financial uncertainty, its value to insurer’s depends on initial premium selection and profitability. The framework identifies conditions under which additional information is most valuable, offering practical insights for improving insurance decisions in hazard-prone regions.