Robust loss reserving in a log-linear model

Georgios Pitselis, Vasiliki Grigoriadou and Ioannis Badounas

Insurance: Mathematics and Economics, 2015, vol. 64, issue C, 14-27

Abstract: It is well known that the presence of outlier events can overestimate or underestimate the overall reserve when using the chain-ladder method. The lack of robustness of loss reserving estimators leads to the development of this paper. The appearance of outlier events (including large claims—catastrophic events) can offset the result of the ordinary chain ladder technique and perturb the reserving estimation. Our proposal is to apply robust statistical procedures to the loss reserving estimation, which are insensitive to the occurrence of outlier events in the data. This paper considers robust log-linear and ANOVA models to the analysis of loss reserving by using different type of robust estimators, such as LAD-estimators, M-estimators, LMS-estimators, LTS-estimators, MM-estimators (with initial S-estimate) and Adaptive-estimators. Comparisons of these estimators are also presented, with application of a well known data set.

Keywords: Log-linear model; Diagnostics; Robust estimators; Loss reserving; Chain ladder (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:insuma:v:64:y:2015:i:c:p:14-27

DOI: 10.1016/j.insmatheco.2015.04.005

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