Optimal Auditing with Scoring: Theory and Application to Insurance Fraud
Abstract
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.Download Info
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Article provided by INFORMS in its journal Management Science.
Volume (Year): 55 (2009)
Issue (Month): 1 (January)
Pages: 58-70
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Web page: http://www.informs.org/
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Related research
Keywords: audit; scoring; insurance fraud; red flags strategy; fraud indicators; suspicion index; moral cost of fraud; deterrence effect; signal manipulation;Other versions of this item:
- Georges Dionne & Florence Giuliano & Pierre Picard, 2005. "Optimal Auditing with Scoring Theory and Application to Insurance Fraud," Working Papers hal-00243026, HAL.
- 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.
- D0 - Microeconomics - - General
- G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies
- C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
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Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- Georges Dionne, 2012. "The Empirical Measure of Information Problems with Emphasis on Insurance Fraud and Dynamic Data," Cahiers de recherche 1233, CIRPEE.
- Jean-Marc Bourgeon & Pierre Picard, 2012. "Fraudulent Claims and Nitpicky Insurers," Working Papers hal-00675106, HAL.
- Matthias Lang & Achim Wambach, 2010. "The fog of fraud – mitigating fraud by strategic ambiguity," Working Paper Series of the Max Planck Institute for Research on Collective Goods 2010_24, Max Planck Institute for Research on Collective Goods.
- Dominic Spengler, 2012. "Endogenising Detection in an Asymmetric Penalties Corruption Game," Discussion Papers 12/20, Department of Economics, University of York.
- Pierre Picard, 2012. "Economic Analysis of Insurance Fraud," Working Papers hal-00725561, HAL.
- 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.
- Georges Dionne & Kili C. Wang, 2011. "Does Opportunistic Fraud in Automobile theft Insurance Fluctuate with the Business Cycle ?," Cahiers de recherche 1121, CIRPEE.
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