Abstract
Stochastic claims reserving has been developed mostly using models defined in the framework of the classical statistics. The recently proposed Time Series Chain Ladder (TSCL) is one of these models. In order to allow for a comparison with the Bayesian point of view, we propose a fully Bayesian model having the property of reproducing TSCL if improper priors are assumed. With “informative” priors the Bayesian model allows for incorporating into the reserving process relevant external data, e.g. expert opinions, which are largely used by the actuaries. We provide numerical examples using Markov Chain Monte Carlo methods.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Buchwalder, M., Bühlmann, H., Merz, M., Wüthrich, M.V.: The mean square error of prediction in the chain ladder reserving method (Mack and Murphy revisited). ASTIN Bulletin 36, 521–542 (2006)
de Finetti, B.: Theory of Probability. A critical introductory treatment. Wiley, New York (1975)
Gisler, A.: The Estimation Error in the Classical Chain-Ladder Reserving Method: a Bayesian Approach. ASTIN Bulletin 36, 554–565 (2006)
Gisler, A., Wüthrich, M.V.: Credibility for the Chain Ladder Method. ASTIN Bulletin 38, 565–600 (2008)
Mack, T.: Distribution-free calculation of the standard error of chain ladder reserve estimates. ASTIN Bulletin 23, 213–225 (1993)
Salzmann, R., Wüthrich, M.V., Merz, M.: Higher Moments of the Claims Development Result in General Insurance (preprint) (to appear in ASTIN Bulletin) (2010)
Wüthrich, M.V., Merz, M.: Stochastic Claims Reserving Methods in Insurance. Wiley, New York (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Castellani, G., De Felice, M., Moriconi, F. (2012). Claims Reserving in Non-life Insurance: A Fully Bayesian Model. In: Greco, S., Bouchon-Meunier, B., Coletti, G., Fedrizzi, M., Matarazzo, B., Yager, R.R. (eds) Advances in Computational Intelligence. IPMU 2012. Communications in Computer and Information Science, vol 300. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31724-8_15
Download citation
DOI: https://doi.org/10.1007/978-3-642-31724-8_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31723-1
Online ISBN: 978-3-642-31724-8
eBook Packages: Computer ScienceComputer Science (R0)