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Optimal auditing with scoring: theory and application to insurance fraud


  • Dionne, Georges
  • Giuliano, Florence
  • Picard, Pierre


This article makes a bridge between the theory of optimal auditing and the scoring methodology in an asymmetric information setting. Our application is meant for insurance claims fraud, but it can be applied to many other activities that use the scoring approach. Fraud signals are classified based on the degree to which they reveal an increasing probability of fraud. We show that the optimal auditing strategy takes the form of a “Red Flags Strategy” which consists in referring claims to a Special Investigative Unit (SIU) when certain fraud indicators are observed. The auditing policy acts as a deterrence device and we explain why it requires the commitment of the insurer and how it should affect the incentives of SIU staffs. The characterization of the optimal auditing strategy is robust to some degree of signal manipulation by defrauders as well as to the imperfect information of defrauders about the audit frequency. The model is calibrated with data from a large European insurance company. We show that it is possible to improve our results by separating different groups of insureds with different moral costs of fraud. Finally, our results indicate how the deterrence effect of the audit scheme can be taken into account and how it affects the optimal auditing strategy.

Suggested Citation

  • Dionne, Georges & Giuliano, Florence & Picard, Pierre, 2009. "Optimal auditing with scoring: theory and application to insurance fraud," MPRA Paper 18374, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:18374

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    References listed on IDEAS

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    Cited by:

    1. Georges Dionne, 2012. "The Empirical Measure of Information Problems with Emphasis on Insurance Fraud and Dynamic Data," Cahiers de recherche 1233, CIRPEE.
    2. Konrad, Kai A. & Lohse, Tim & Qari, Salmai, 2014. "Deception choice and self-selection – The importance of being earnest," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PA), pages 25-39.
    3. Hisashi Nakamura & Koichiro Takaoka, 2014. "A Continuous-Time Optimal Insurance Design with Costly Monitoring," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 21(3), pages 237-261, September.
    4. Jean-Marc Bourgeon & Pierre Picard, 2014. "Fraudulent Claims and Nitpicky Insurers," American Economic Review, American Economic Association, vol. 104(9), pages 2900-2917, September.
    5. Lang, Matthias & Wambach, Achim, 2013. "The fog of fraud – Mitigating fraud by strategic ambiguity," Games and Economic Behavior, Elsevier, vol. 81(C), pages 255-275.
    6. 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).
    7. Dionne, Georges & Harrington, Scott, 2017. "Insurance and Insurance Markets," Working Papers 17-2, HEC Montreal, Canada Research Chair in Risk Management.
    8. 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.
    9. John E. Murray, 2011. "Asymmetric Information and Countermeasures in Early Twentieth‐Century American Short‐Term Disability Microinsurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 78(1), pages 117-138, March.
    10. Mahito Okura, 2013. "The relationship between moral hazard and insurance fraud," Journal of Risk Finance, Emerald Group Publishing, vol. 14(2), pages 120-128, February.
    11. Georges Dionne & Kili Wang, 2013. "Does insurance fraud in automobile theft insurance fluctuate with the business cycle?," Journal of Risk and Uncertainty, Springer, vol. 47(1), pages 67-92, August.
    12. Lohse, Tim & Konrad, Kai A. & Qari, Salmai, 2014. "Deception Choice and Audit Design - The Importance of Being Earnest," Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100577, Verein für Socialpolitik / German Economic Association.
    13. Chu-Shiu Li & Chwen-Chi Liu & Sheng-Chang Peng, 2013. "Expiration Dates in Automobile Insurance Contracts: The Curious Case of Last Policy Month Claims in Taiwan," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 38(1), pages 23-47, March.
    14. 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.
    15. Jing Ai & Patrick L. Brockett & Linda L. Golden & Montserrat Guillén, 2013. "A Robust Unsupervised Method for Fraud Rate Estimation," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 80(1), pages 121-143, March.
    16. John Bone & Dominic Spengler, 2014. "Does Reporting Decrease Corruption?," Journal of Interdisciplinary Economics, , vol. 26(1-2), pages 161-186, January.
    17. Spengler Dominic, 2014. "Endogenous Detection of Collaborative Crime: The Case of Corruption," Review of Law & Economics, De Gruyter, vol. 10(2), pages 1-17, July.
    18. Dominic Spengler, 2012. "Endogenising Detection in an Asymmetric Penalties Corruption Game," Discussion Papers 12/20, Department of Economics, University of York.
    19. Pierre Picard, 2012. "Economic Analysis of Insurance Fraud," Working Papers hal-00725561, HAL.
    20. Samohyl, Robert, 2012. "Audits and logistic regression, deciding what really matters in service processes: a case study of a government funding agency for research grants," MPRA Paper 41557, University Library of Munich, Germany.
    21. Laitinen, Erkki K. & Laitinen, Teija, 2015. "A probability tree model of audit quality," European Journal of Operational Research, Elsevier, vol. 243(2), pages 665-677.
    22. Georges Dionne & Kili C. Wang, 2011. "Does Opportunistic Fraud in Automobile theft Insurance Fluctuate with the Business Cycle ?," Cahiers de recherche 1121, CIRPEE.

    More about this item


    Audit; scoring; insurance fraud; red flags strategy; fraud indicators; suspicion index; moral cost of fraud; deterrence effect; signal manipulation.;

    JEL classification:

    • D0 - Microeconomics - - General
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics

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