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Detection and correction of outliers in the bivariate chain-ladder method

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  • Verdonck, T.
  • Van Wouwe, M.

Abstract

The expected profit or loss of a non-life insurance company is determined for the whole of its multiple business lines. This implies the study of the claims reserving problem for a portfolio consisting of several correlated run-off triangles. A popular technique to deal with such a portfolio is the multivariate chain-ladder method of Merz and Wüthrich (2008). However, it is well known that the chain-ladder method is very sensitive to outlying data. For the univariate case, we have already developed a robust version of the chain-ladder method. In this article we propose two techniques to detect and correct outlying values in a bivariate situation. The methodologies are illustrated and compared on real examples from practice.

Suggested Citation

  • Verdonck, T. & Van Wouwe, M., 2011. "Detection and correction of outliers in the bivariate chain-ladder method," Insurance: Mathematics and Economics, Elsevier, vol. 49(2), pages 188-193, September.
    • Handle: RePEc:eee:insuma:v:49:y:2011:i:2:p:188-193
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    References listed on IDEAS

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    1. Zani, Sergio & Riani, Marco & Corbellini, Aldo, 1998. "Robust bivariate boxplots and multiple outlier detection," Computational Statistics & Data Analysis, Elsevier, vol. 28(3), pages 257-270, September.
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    Cited by:

    1. Nataliya Chukhrova & Arne Johannssen, 2017. "State Space Models and the K alman -Filter in Stochastic Claims Reserving: Forecasting, Filtering and Smoothing," Risks, MDPI, vol. 5(2), pages 1-23, May.
    2. Benjamin Avanzi & Mark Lavender & Greg Taylor & Bernard Wong, 2022. "Detection and treatment of outliers for multivariate robust loss reserving," Papers 2203.03874, arXiv.org, revised Jun 2023.
    3. Kris Peremans & Stefan Van Aelst & Tim Verdonck, 2018. "A Robust General Multivariate Chain Ladder Method," Risks, MDPI, vol. 6(4), pages 1-18, September.

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