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Claims reserving in the presence of excess-of-loss reinsurance using micro models based on aggregate data

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  • Margraf, Carolin
  • Elpidorou, Valandis
  • Verrall, Richard

Abstract

This paper addresses a new problem in the literature, which is how to consider reserving issues for a portfolio of general insurance policies when there is excess-of-loss reinsurance. This is very important for pricing considerations and for decision making regarding capital issues. The paper sets out how this is currently often tackled in practice and provides an alternative approach using recent developments in stochastic claims reserving. These alternative approaches are illustrated and compared in an example using real data. The stochastic modelling framework used in this paper is Double Chain Ladder, but other approaches would also be possible. The paper sets out an approach which could be explored further and built on in future research.

Suggested Citation

  • Margraf, Carolin & Elpidorou, Valandis & Verrall, Richard, 2018. "Claims reserving in the presence of excess-of-loss reinsurance using micro models based on aggregate data," Insurance: Mathematics and Economics, Elsevier, vol. 80(C), pages 54-65.
  • Handle: RePEc:eee:insuma:v:80:y:2018:i:c:p:54-65
    DOI: 10.1016/j.insmatheco.2018.03.001
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    References listed on IDEAS

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    1. England, Peter & Verrall, Richard, 1999. "Analytic and bootstrap estimates of prediction errors in claims reserving," Insurance: Mathematics and Economics, Elsevier, vol. 25(3), pages 281-293, December.
    2. Miranda, María Dolores Martínez & Nielsen, Jens Perch & Verrall, Richard, 2012. "Double Chain Ladder," ASTIN Bulletin, Cambridge University Press, vol. 42(1), pages 59-76, May.
    3. England, P.D. & Verrall, R.J., 2002. "Stochastic Claims Reserving in General Insurance," British Actuarial Journal, Cambridge University Press, vol. 8(3), pages 443-518, August.
    4. Miranda, María Dolores Martínez & Nielsen, Bent & Nielsen, Jens Perch & Verrall, Richard, 2011. "Cash Flow Simulation for a Model of Outstanding Liabilities Based on Claim Amounts and Claim Numbers," ASTIN Bulletin, Cambridge University Press, vol. 41(1), pages 107-129, May.
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    Cited by:

    1. Eduardo Ramos-P'erez & Pablo J. Alonso-Gonz'alez & Jos'e Javier N'u~nez-Vel'azquez, 2020. "Stochastic reserving with a stacked model based on a hybridized Artificial Neural Network," Papers 2008.07564, arXiv.org.

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