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Claims Run-Off Uncertainty: The Full Picture

Author

Listed:
  • Michael Merz

    (University of Hamburg)

  • Mario V. Wuthrich

    (RiskLab, ETH Zurich)

Abstract

The aim of this contribution is to revisit, clarify and complete the picture of uncertainty estimates in the chain-ladder (CL) claims reserving method. Therefore, we consider the conditional mean square error of prediction (MSEP) of the total prediction uncertainty (using Mack’s formula) and the one of the one-year prediction uncertainty (using the Merz-Wüthrich formula). We discuss and compare these two formulas and we derive the missing pieces that close the gap between the one-year and total run-off uncertainty view.

Suggested Citation

  • Michael Merz & Mario V. Wuthrich, 2014. "Claims Run-Off Uncertainty: The Full Picture," Swiss Finance Institute Research Paper Series 14-69, Swiss Finance Institute.
    • Handle: RePEc:chf:rpseri:rp1469
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    File URL: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2524352
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    Cited by:

    1. Gao, Guangyuan & Meng, Shengwang & Shi, Yanlin, 2021. "Dispersion modelling of outstanding claims with double Poisson regression models," Insurance: Mathematics and Economics, Elsevier, vol. 101(PB), pages 572-586.

    More about this item

    Keywords

    Claims reserving; chain-ladder method; gamma-gamma Bayesian chain-ladder model; conditional mean square error of prediction; claims development result; one-year uncertainty; run-off uncertainty; Mack’s formula; Merz- Wüthrich formula; risk margin; R package ChainLadder;
    All these keywords.

    JEL classification:

    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • D46 - Microeconomics - - Market Structure, Pricing, and Design - - - Value Theory

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