Dependence Modelling of Frequency-Severity of Insurance Claims Using Waiting Time for Claim

Guangyuan Gao, Jiahong Li
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Abstract

We propose a dependent frequency-severity model using a Gaussian copula. The copula links a latent variable of waiting time for the second claim with the claim severity. By assuming a log-normal distributed claim severity, we can analyze the effect of claim counts on the conditional expectation of severity. We propose a Monte Carlo simulation algorithm to simulate the predictive distribution of the aggregated claims amount. In an empirical example, we compare the proposed method with the conditional modeling by Garrido et al. (2016) and the mixed copula modeling by Czado et al. (2012).
基于等待理赔时间的保险理赔频度-严重性相关性模型
我们提出了一个依赖的频率-严重性模型使用高斯联结。该联结关系将第二项权利要求的等待时间的潜在变量与该权利要求的严重性联系起来。通过假设一个对数正态分布的索赔严重性,我们可以分析索赔计数对严重性条件期望的影响。我们提出了一种蒙特卡罗模拟算法来模拟总索赔金额的预测分布。在一个实证示例中,我们将所提出的方法与Garrido等人(2016)的条件建模和Czado等人(2012)的混合copula建模进行了比较。
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