Insurance: Mathematics and Economics ( IF 1.9 ) Pub Date : 2021-03-17 , DOI: 10.1016/j.insmatheco.2021.02.009 Sébastien Farkas , Olivier Lopez , Maud Thomas
With the rise of the cyber insurance market, there is a need for better quantification of the economic impact of this risk and its rapid evolution. Due to the heterogeneity of cyber claims, evaluating the appropriate premium and/or the required amount of reserves is a difficult task. In this paper, we propose a method for cyber claim analysis based on regression trees to identify criteria for claim classification and evaluation. We particularly focus on severe/extreme claims, by combining a Generalized Pareto modeling – legitimate from Extreme Value Theory – and a regression tree approach. Coupled with an evaluation of the frequency, our procedure allows computations of central scenarios and of extreme loss quantiles for a cyber portfolio. Finally, the method is illustrated on a public database.
中文翻译:
使用广义Pareto回归树的网络索赔分析及其在保险中的应用
随着网络保险市场的兴起,有必要对这种风险及其快速发展的经济影响进行更好的量化。由于网络声明的异质性,评估适当的溢价和/或所需的准备金金额是一项艰巨的任务。在本文中,我们提出了一种基于回归树的网络索赔分析方法,以确定索赔分类和评估的标准。通过结合广义Pareto建模(从极值理论中得出的合法证据)和回归树方法,我们特别关注严厉/极端索赔。结合对频率的评估,我们的程序允许计算网络投资组合的中心情景和极端损失分位数。最后,该方法在公共数据库中进行了说明。