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Can Bonus‐Malus Allieviate Insurance Fraud?

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  • Ignacio Moreno
  • Francisco J. Vázquez
  • Richard Watt

Abstract

Traditionally, insurance companies attempt to reduce (or even eliminate) fraud via audit strategies under which claims may be investigated at some cost to the insurer, with a penalty imposed upon insureds who are found to report claims fraudulently. However, it is also clear that, in a multiperiod setting, bonus‐malus contracts (increases in subsequent premiums whenever a claim is presented) also provide an incentive against fraud. In this article, we consider a model in which, conditional upon the client renewing his contract, the only mechanism used to combat fraud is bonus‐malus. In this way, our model provides the opposite pole to the pure audit model. We show that in our simplified setting there exists a bonus‐malus contract that will eliminate all fraud in all periods, while guaranteeing nonnegative expected profits to the insurer and participation by the insured. We also consider the dynamics of the solution, the effect of an increase in risk aversion on the solution, and the welfare implications.

Suggested Citation

  • Ignacio Moreno & Francisco J. Vázquez & Richard Watt, 2006. "Can Bonus‐Malus Allieviate Insurance Fraud?," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 73(1), pages 123-151, March.
  • Handle: RePEc:bla:jrinsu:v:73:y:2006:i:1:p:123-151
    DOI: 10.1111/j.1539-6975.2006.00168.x
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    References listed on IDEAS

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    1. Keith J. Crocker & John Morgan, 1998. "Is Honesty the Best Policy? Curtailing Insurance Fraud through Optimal Incentive Contracts," Journal of Political Economy, University of Chicago Press, vol. 106(2), pages 355-375, April.
    2. Pierre Picard, 2012. "Economic Analysis of Insurance Fraud," Working Papers hal-00725561, HAL.
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    Cited by:

    1. Dionne, Georges, 2012. "The empirical measure of information problems with emphasis on insurance fraud and dynamic data," Working Papers 12-10, HEC Montreal, Canada Research Chair in Risk Management.
    2. Francesca Barigozzi & Renaud Bourlès & Dominique Henriet & Giuseppe Pignataro, 2017. "Pool size and the sustainability of optimal risk-sharing agreements," Theory and Decision, Springer, vol. 82(2), pages 273-303, February.
    3. Michael Ludkovski & Virginia R. Young, 2010. "Ex Post Moral Hazard and Bayesian Learning in Insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 77(4), pages 829-856, December.
    4. Kerstin Fiederling & Jörg Schiller & Frauke von Bieberstein, 2018. "Can we Trust Consumers’ Survey Answers when Dealing with Insurance Fraud?," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 70(2), pages 111-147, May.
    5. Pierre Picard, 2012. "Economic Analysis of Insurance Fraud," Working Papers hal-00725561, HAL.
    6. Katja Müller & Hato Schmeiser & Joël Wagner, 2016. "The impact of auditing strategies on insurers’ profitability," Journal of Risk Finance, Emerald Group Publishing, vol. 17(1), pages 46-79, January.
    7. Lammers, Frauke & Schiller, Jörg, 2010. "Contract design and insurance fraud: An experimental investigation," FZID Discussion Papers 19-2010, University of Hohenheim, Center for Research on Innovation and Services (FZID).
    8. Frauke von Bieberstein & Jörg Schiller, 2018. "Contract design and insurance fraud: an experimental investigation," Review of Managerial Science, Springer, vol. 12(3), pages 711-736, July.

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