Fraud Detection Using a Multinomial Logit Model With Missing Information
Recently, Artís, Ayuso, and Guillén (2002, "Journal of Risk and Insurance" 69: 325-340; henceforth AAG) estimate a logit model using claims data. Some of the claims are categorized as "honest" and other claims are known to be fraudulent. Using the approach of Hausman, Abrevaya, and Scott-Morton (1998 "Journal of Econometrics" 87: 239-269), AAG estimate a modified logit model allowing for the possibility that some claims classified as honest might actually be fraudulent. Applying this model to data on Spanish automobile insurance claims, AGG find that 5 percent of the fraudulent claims go undetected. The purpose of this article is to estimate the model of AAG using a logit model with missing information. A constrained version of this model is used to reexamine the Spanish insurance claim data. The results indicate how to identify misclassified claims. We also show how misclassified claims can be identified using the AAG approach. We show that both approaches can be used to probabilistically identify misclassified claims. Copyright The Journal of Risk and Insurance.
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Volume (Year): 72 (2005)
Issue (Month): 4 ()
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References listed on IDEAS
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- G. Dionne & F. Giuliano & P. Picard, 2002.
"Optimal auditing for insurance fraud,"
THEMA Working Papers
2002-32, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
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- Dionne, G., 1980. "The Effects of Insurance on the Possibilities of Fraud," Cahiers de recherche 8103, Universite de Montreal, Departement de sciences economiques.
- Hausman, J. A. & Abrevaya, Jason & Scott-Morton, F. M., 1998. "Misclassification of the dependent variable in a discrete-response setting," Journal of Econometrics, Elsevier, vol. 87(2), pages 239-269, September.
- Pierre Picard, 2012. "Economic Analysis of Insurance Fraud," Working Papers hal-00725561, HAL.
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