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Bayesian over-dispersed Poisson model and the Bornhuetter & Ferguson claims reserving method

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  • England, Peter D.
  • Verrall, Richard J.
  • Wüthrich, Mario V.

Abstract

We consider the Bayesian over-dispersed Poisson (ODP) model for claims reserving in general insurance. We choose two different types of prior distributions for the parameters and then study the different Bayesian predictors. This study leads, on the one hand, to the classical chain ladder predictor and, on the other hand, to Bornhuetter & Ferguson predictors. We highlight (either analytically or numerically) how these predictors are obtained and how their prediction uncertainty can be determined.

Suggested Citation

  • England, Peter D. & Verrall, Richard J. & Wüthrich, Mario V., 2012. "Bayesian over-dispersed Poisson model and the Bornhuetter & Ferguson claims reserving method," Annals of Actuarial Science, Cambridge University Press, vol. 6(2), pages 258-283, September.
    • Handle: RePEc:cup:anacsi:v:6:y:2012:i:02:p:258-283_00
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    Cited by:

    1. Boratyńska, Agata, 2017. "Robust Bayesian estimation and prediction of reserves in exponential model with quadratic variance function," Insurance: Mathematics and Economics, Elsevier, vol. 76(C), pages 135-140.
    2. Gigante, Patrizia & Picech, Liviana & Sigalotti, Luciano, 2013. "Claims reserving in the hierarchical generalized linear model framework," Insurance: Mathematics and Economics, Elsevier, vol. 52(2), pages 381-390.
    3. Alessandro Ricotta & Gian Paolo Clemente, 2016. "An Extension of Collective Risk Model for Stochastic Claim Reserving," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 6(5), pages 1-3.

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