Neural networks applied to chain–ladder reserving

被引：37

作者：

Wüthrich M.V. ^{[1
]}

机构：

[1] Department of Mathematics, ETH Zurich, RiskLab, Zurich

来源：

European Actuarial Journal | 2018年 / 8卷 / 2期

关键词：

Claims covariates; Claims reserving; Individual claims features; Individual claims reserving; Mack’s CL model; Micro-level reserving; Neural networks;

D O I：

10.1007/s13385-018-0184-4

中图分类号：

学科分类号：

摘要：

Classical claims reserving methods act on so-called claims reserving triangles which are aggregated insurance portfolios. A crucial assumption in classical claims reserving is that these aggregated portfolios are sufficiently homogeneous so that a coarse reserving algorithm can be applied. We start from such a coarse reserving method, which in our case is Mack’s chain–ladder method, and show how this approach can be refined for heterogeneity and individual claims feature information using neural networks. © 2018, EAJ Association.

引用

页码：407 / 436

页数：29

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