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Paid-incurred chain claims reserving method

Listed author(s):
  • Merz, Michael
  • Wüthrich, Mario V.
Registered author(s):

    We 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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    Article provided by Elsevier in its journal Insurance: Mathematics and Economics.

    Volume (Year): 46 (2010)
    Issue (Month): 3 (June)
    Pages: 568-579

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    Handle: RePEc:eee:insuma:v:46:y:2010:i:3:p:568-579
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    1. Gisler, Alois & Wüthrich, Mario V., 2008. "Credibility for the Chain Ladder Reserving Method," ASTIN Bulletin: The Journal of the International Actuarial Association, Cambridge University Press, vol. 38(02), pages 565-600, November.
    2. Gogol, Daniel, 1993. "Using expected loss ratios in reserving," Insurance: Mathematics and Economics, Elsevier, vol. 12(3), pages 297-299, June.
    3. Bühlmann, Hans & De Felice, Massimo & Gisler, Alois & Moriconi, Franco & Wüthrich, Mario V., 2009. "Recursive Credibility Formula for Chain Ladder Factors and the Claims Development Result," ASTIN Bulletin: The Journal of the International Actuarial Association, Cambridge University Press, vol. 39(01), pages 275-306, May.
    4. Mack, Thomas, 1993. "Distribution-free Calculation of the Standard Error of Chain Ladder Reserve Estimates," ASTIN Bulletin: The Journal of the International Actuarial Association, Cambridge University Press, vol. 23(02), pages 213-225, November.
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