A Bayesian Internal Model for Reserve Risk: An Extension of the Correlated Chain Ladder

Carnevale Giulio Ercole and Clemente Gian Paolo
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Carnevale Giulio Ercole: PartnerRe, Hardstrasse 301, 8005 Zürich, Switzerland
Clemente Gian Paolo: Department of Mathematics for Economic, Financial and Actuarial Sciences, Università Cattolica del Sacro Cuore, Largo Agostino Gemelli 1, 20123 Milan, Italy

Risks, 2020, vol. 8, issue 4, 1-20

Abstract: The goal of this paper was to exploit the Bayesian approach and MCMC procedures to structure an internal model to quantify the reserve risk of a non-life insurer under Solvency II regulation. To this aim, we provide an extension of the Correlated Chain Ladder (CCL) model to the one-year time horizon. In this way, we obtain the predictive distribution of the next year obligations and we are able to assess a capital requirement compliant with Solvency II framework. Numerical results compare the one-year CCL with other traditional approaches, such as Re-Reserving and the Merz and Wüthrich formula. One-year CCL proves to be a legitimate alternative, providing values comparable with the more traditional approaches and more robust and accurate risk estimations, that embed external knowledge not present in the data and allow for a more precise and tailored representation of the risk profile of the insurer.

Keywords: Bayesian models; stochastic claims reserving; claims development results (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2020
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