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The link between classical reserving and granular reserving through double chain ladder and its extensions

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  • Hiabu, M.
  • Margraf, C.
  • Martínez-Miranda, M. D.
  • Nielsen, J. P.

Abstract

The relationship of the chain ladder method to mathematical statistics has long been debated in actuarial science. During the 1990s it became clear that the originally deterministic chain ladder can be seen as an autoregressive time series or as a multiplicative Poisson model. This paper draws on recent research and concludes that chain ladder can be seen as a structured histogram. This gives a direct link between classical aggregate methods and continuous granular methods. When the histogram is replaced by a smooth counterpart, we have a continuous chain ladder model. Re-inventing classical chain ladder via double chain ladder and its extensions introduces statistically solid approaches of combining paid and incurred data with direct link to granular data approaches. This paper goes through some of the extensions of double chain ladder and introduces new approaches to incorporating and modelling incurred data.

Suggested Citation

  • Hiabu, M. & Margraf, C. & Martínez-Miranda, M. D. & Nielsen, J. P., 2016. "The link between classical reserving and granular reserving through double chain ladder and its extensions," British Actuarial Journal, Cambridge University Press, vol. 21(1), pages 97-116, March.
    • Handle: RePEc:cup:bracjl:v:21:y:2016:i:01:p:97-116_00
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    Cited by:

    1. Andrea Gabrielli & Mario V. Wüthrich, 2018. "An Individual Claims History Simulation Machine," Risks, MDPI, vol. 6(2), pages 1-32, March.
    2. Francis Duval & Mathieu Pigeon, 2019. "Individual Loss Reserving Using a Gradient Boosting-Based Approach," Risks, MDPI, vol. 7(3), pages 1-18, July.

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