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Claims Modelling with Three-Component Composite Models

Author

Listed:
  • Jackie Li

    (Department of Econometrics and Business Statistics, Monash University, Melbourne 3800, Australia)

  • Jia Liu

    (Research School of Finance, Actuarial Studies & Statistics, Australian National University, Canberra 0200, Australia)

Abstract

In this paper, we develop a number of new composite models for modelling individual claims in general insurance. All our models contain a Weibull distribution for the smallest claims, a lognormal distribution for the medium-sized claims, and a long-tailed distribution for the largest claims. They provide a more detailed categorisation of claims sizes when compared to the existing composite models which differentiate only between the small and large claims. For each proposed model, we express four of the parameters as functions of the other parameters. We fit these models to two real-world insurance data sets using both maximum likelihood and Bayesian estimation, and test their goodness-of-fit based on several statistical criteria. They generally outperform the existing composite models in the literature, which comprise only two components. We also perform regression using the proposed models.

Suggested Citation

  • Jackie Li & Jia Liu, 2023. "Claims Modelling with Three-Component Composite Models," Risks, MDPI, vol. 11(11), pages 1-16, November.
  • Handle: RePEc:gam:jrisks:v:11:y:2023:i:11:p:196-:d:1279098
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    References listed on IDEAS

    as
    1. Abu Bakar, S.A. & Hamzah, N.A. & Maghsoudi, M. & Nadarajah, S., 2015. "Modeling loss data using composite models," Insurance: Mathematics and Economics, Elsevier, vol. 61(C), pages 146-154.
    2. McNeil, Alexander J., 1997. "Estimating the Tails of Loss Severity Distributions Using Extreme Value Theory," ASTIN Bulletin, Cambridge University Press, vol. 27(1), pages 117-137, May.
    Full references (including those not matched with items on IDEAS)

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