Stochastic Loss Reserving in Discrete Time: Individual vs. Aggregate Data Models
Stochastic Loss Reserving in Discrete Time: Individual vs. Aggregate Data Models
复制标题
离散时间的随机损失保留：个体数据模型与聚合数据模型
DOI：
10.1080/03610926.2014.976473
复制
发表时间：
2015
影响因子：
0.8
通讯作者：
Wu Xianyi
中科院分区：
文献类型：
--
作者：
Huang Jinlong;Qiu Chunjuan;Wu Xianyi
In this paper, a stochastic individual data model is considered. It accommodates occurrence times, reporting, and settlement delays and severity of every individual claims. This formulation gives rise to a model for the corresponding aggregate data under which classical chain ladder and Bornhuetter–Ferguson algorithms apply. A claims reserving algorithm is developed under this individual data model and comparisons of its performance with chain ladder and Bornhuetter–Ferguson algorithms are made to reveal the effects of using individual data to instead aggregate data. The research findings indicate a remarkable promotion in accuracy of loss reserving, especially when the claims amounts are not too heavy-tailed.
