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Why do insurers fail? A comparison of life and non-life insolvencies using a new international database

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Listed:
  • George Overton

    (EconomiX - EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique)

  • Olivier de Bandt

    (EconomiX - EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique)

Abstract

Plantin & Rocher (2016) document how insurers often engage in risk-shifting years before the materialization of a failure. This paper empirically examines this claim by testing the mechanisms of insurance insolvency, using a first-of-its-kind international database assembled by the authors which merges data on balance sheet and income statements together with information on impairments over the last 30 years. Employing different fixed effects logistic specifications and parametric survival models, the paper presents evidence, on top of the role of profitability as a leading indicator of failures, of the intrinsic asymmetries between the life and non-life insurance sectors. In the life sector, asset mix is highly significant in predicting an impairment, while operating efficiency plays no role. In the non-life sector, the opposite proves true.

Suggested Citation

  • George Overton & Olivier de Bandt, 2020. "Why do insurers fail? A comparison of life and non-life insolvencies using a new international database," Working Papers hal-04159696, HAL.
    • Handle: RePEc:hal:wpaper:hal-04159696
    Note: View the original document on HAL open archive server: https://hal.science/hal-04159696
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    References listed on IDEAS

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    1. Darrell Leadbetter & Suela Dibra, 2008. "Why Insurers Fail: The Dynamics of Property and Casualty Insurance Insolvency in Canada," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 33(3), pages 464-488, July.
    2. David T. Russell & Stephen G. Fier & James M. Carson & Randy E. Dumm, 2013. "An Empirical Analysis of Life Insurance Policy Surrender Activity," Journal of Insurance Issues, Western Risk and Insurance Association, vol. 36(1), pages 35-57.
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    5. Eling, Martin & Jia, Ruo, 2018. "Business failure, efficiency, and volatility: Evidence from the European insurance industry," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 58-76.
    6. Cummins, J. David & Harrington, Scott E. & Klein, Robert, 1995. "Insolvency experience, risk-based capital, and prompt corrective action in property-liability insurance," Journal of Banking & Finance, Elsevier, vol. 19(3-4), pages 511-527, June.
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    8. Shumway, Tyler, 2001. "Forecasting Bankruptcy More Accurately: A Simple Hazard Model," The Journal of Business, University of Chicago Press, vol. 74(1), pages 101-124, January.
    9. Li Zhang & Norma Nielson, 2015. "Solvency Analysis And Prediction In Property–Casualty Insurance: Incorporating Economic And Market Predictors," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 82(1), pages 97-124, March.
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    Cited by:

    1. Eric Monnet, & Angelo Riva, & Stefano Ungaro., 2021. "The Real Effects of Bank Runs. Evidence from the French Great Depression (1930-1931) [Les effets réels des ruées bancaires : l’exemple de la Grande Dépression en France (1930-1931)]," Débats économiques et financiers 37, Banque de France.
    2. Subramanian, Ajay & Wang, Jinjing, 2021. "Capital, aggregate risk, insurance prices and regulation," Insurance: Mathematics and Economics, Elsevier, vol. 100(C), pages 156-192.

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    More about this item

    Keywords

    Insurance; insolvency prediction; leading indicators; financial crises;
    All these keywords.

    JEL classification:

    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • G01 - Financial Economics - - General - - - Financial Crises
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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