Robust Loss Development Using MCMC

49 Pages Posted: 8 Nov 2009 Last revised: 17 Feb 2010

Date Written: February 15, 2010


A Bayesian model of developing aggregate loss triangles in property casualty insurance is introduced. This model makes use of a heteroskedastic and skewed t-likelihood with endogenous degrees of freedom, employs model averaging by means of Reversible Jump MCMC, and accommodates a structural break in the consumption path. Further, the model is capable of incorporating expert information in the calendar year effect. The model, which has been compiled into the R package lossDev, is applied to two widely studied General Liability and Auto Bodily Injury Liability loss triangles.

Keywords: Loss development, skewed Student distribution, Reversible Jump MCMC

JEL Classification: G22

Suggested Citation

Schmid, Frank A., Robust Loss Development Using MCMC (February 15, 2010). Available at SSRN: or

Frank A. Schmid (Contact Author)


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New York, NY 10005
United States

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