Paid-incurred chain claims reserving method
AbstractWe present a novel stochastic model for claims reserving that allows us to combine claims payments and incurred losses information. The main idea is to combine two claims reserving models (Hertig's (1985) model and Gogol's (1993) model ) leading to a log-normal paid-incurred chain (PIC) model. Using a Bayesian point of view for the parameter modelling we derive in this Bayesian PIC model the full predictive distribution of the outstanding loss liabilities. On the one hand, this allows for an analytical calculation of the claims reserves and the corresponding conditional mean square error of prediction. On the other hand, simulation algorithms provide any other statistics and risk measure on these claims reserves.
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Bibliographic InfoArticle provided by Elsevier in its journal Insurance: Mathematics and Economics.
Volume (Year): 46 (2010)
Issue (Month): 3 (June)
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Web page: http://www.elsevier.com/locate/inca/505554
Claims reserving Outstanding loss liabilities Ultimate loss Claims payments Claims incurred Incurred losses Prediction uncertainty;
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- Gogol, Daniel, 1993. "Using expected loss ratios in reserving," Insurance: Mathematics and Economics, Elsevier, vol. 12(3), pages 297-299, June.
- Robert, Christian Y., 2013. "Market Value Margin calculations under the Cost of Capital approach within a Bayesian chain ladder framework," Insurance: Mathematics and Economics, Elsevier, vol. 53(1), pages 216-229.
- Gareth W. Peters & Alice X. D. Dong & Robert Kohn, 2012. "A Copula Based Bayesian Approach for Paid-Incurred Claims Models for Non-Life Insurance Reserving," Papers 1210.3849, arXiv.org, revised Dec 2012.
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