• DOI:10.1080/03461238.2016.1263236
• Corpus ID: 88521939

Robust bootstrap procedures for the chain-ladder method

@article{Peremans2017RobustBP,
  title={Robust bootstrap procedures for the chain-ladder method},
  author={Kris Peremans and Pieter Segaert and Stefan Van Aelst and Tim Verdonck},
  journal={Scandinavian Actuarial Journal},
  year={2017},
  volume={2017},
  pages={870 - 897}
}

• Kris Peremans, P. Segaert, +1 author Tim Verdonck
• Published 14 January 2017
• Mathematics
• Scandinavian Actuarial Journal

Insurers are faced with the challenge of estimating the future reserves needed to handle historic and outstanding claims that are not fully settled. A well-known and widely used technique is the chain-ladder method, which is a deterministic algorithm. To include a stochastic component one may apply generalized linear models to the run-off triangles based on past claims data. Analytical expressions for the standard deviation of the resulting reserve estimates are typically difficult to derive. A popular alternative approach to obtain inference is to use the bootstrap technique. However, the standard procedures are very sensitive to the possible presence of outliers. These atypical observations, deviating from the pattern of the majority of the data, may both inflate or deflate traditional reserve estimates and corresponding inference such as their standard errors. Even when paired with a robust chain-ladder method, classical bootstrap inference may break down. Therefore, we discuss and implement several robust bootstrap procedures in the claims reserving framework and we investigate and compare their performance on both simulated and real data. We also illustrate their use for obtaining the distribution of one year risk measures.