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

Gian Paolo Clemente, Carnevale Giulio Ercole

Research output: Contribution to journalArticlepeer-review

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.
Original languageEnglish
Pages (from-to)1-20
Number of pages20
JournalRisks
Volume2020
Publication statusPublished - 2020

Keywords

  • Bayesian models
  • Claims development result
  • Stochastic Claim Reserving

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