Assessing Hail Risk for Property Insurers with a Dependent Marked Point Process
提出一个统计模型，帮助财产保险公司从索赔到达模式和财务影响两方面评估冰雹风险，利用美国保险公司和雷达数据验证模型能改进索赔预测和管理决策。
Abstract Hail risk is among the most challenging perils to insure and property damage due to hailstones has been on the top of the list of annual claims for most non-life insurers. In this article, we present a simple yet flexible statistical model for insurers to assess and manage hail risks from two aspects: analysing the insurance claims arrival pattern upon occurrence of a hailstorm and quantifying the subsequent financial impact of the hailstorm. We formulate the problem using a marked point process where the reporting of insurance claims due to a hailstorm is treated as recurrent events and the claim amounts are viewed as associated marks. Three complications are addressed in model building: the unobserved heterogeneity in claim arrival, the dependence between the event time and the mark and the complex distribution in claim amount. Using a unique data that combine the exposure data from a major US insurer and the radar data from a third-party vendor, we show the proposed method help improve predictive analytics for post-hailstorm claims volume, arrival rate and severity, and thus claim management decisions for the insurer.