Issues in Claims Reserving and Credibility: A Semiparametric Approach with Mixed Models

34 Pages Posted: 5 Aug 2008

See all articles by Katrien Antonio

Katrien Antonio

KU Leuven; University of Amsterdam

Jan Beirlant

Catholic University of Leuven (KUL)

Abstract

Using the statistical methodology of semi-parametric regression and its connection with mixed models, this article revisits smoothing models for loss reserving and credibility. Apart from the flexibility inherent to all semiparametric methods, advantages of the semiparametric approach developed here are threefold. First, a Bayesian implementation of these smoothing models is relatively straightforward and allows simulation from the full predictive distribution of quantities of interest. Second, because the constructed models have an interpretation as (generalized) linear mixed models ((G)LMMs), standard statistical theory and software for (G)LMMs can be used. Third, more complicated data sets, dealing, for example, with quarterly development in a reserving context, heavy tails, semi-continuous data, or extensive longitudinal data, can be modeled within this framework.

Suggested Citation

Antonio, Katrien and Beirlant, Jan, Issues in Claims Reserving and Credibility: A Semiparametric Approach with Mixed Models. Journal of Risk & Insurance, Vol. 75, Issue 3, pp. 643-676, September 2008. Available at SSRN: https://ssrn.com/abstract=1202446 or http://dx.doi.org/10.1111/j.1539-6975.2008.00278.x

University of Amsterdam ( email )

Roetersstraat 11
Amsterdam, 1018 WB
Netherlands

Jan Beirlant

Catholic University of Leuven (KUL) ( email )

W. de Croylaan 54
Leuven, B-3001
Belgium

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