IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

Selection bias and auditing policies for insurance claims

  • Mercedes Ayuso

    (Universitat de Barcelona)

  • Montserrat Guillén

    (Universitat de Barcelona)

  • Jean Pinquet

    (Department of Economics, Ecole Polytechnique - CNRS : UMR7176 - Polytechnique - X)

Les biais de sélection sont créés par des disparités entre le domaine d'estimation d'un modèle statistique et son domaine d'application. C'est le cas pour les modèles évaluant le risque de fraude, qui sont estimés sur les seuls sinistres audités mais appliqués sur tous les sinistres entrants. Or les sinistres audités sont une minorité, étant choisis suite à une sélection sévère effectuée par des experts. Ce papier présente une approche statistique qui contrebalance le biais de sélection sans recourir à une stratégie d'audit aléatoire. On estime un modéle à deux équations sur l'audit et la fraude (un modèle probit bivarié avec censure), sur une une partie d'une base de sinistres où les experts sont laissés libres de leur décision d'auditer. On corrige ainsi la surestimation attendue du risque de fraude en cas d'estimation d'une seule équation. Les résultats sont proches de ceux obtenus par audit aléatoire, au prix d'une instabilité des résultats par rapport à l'ensemble des composantes de régression. On compare ensuite des politiques d'audit à partir des différentes approches.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://hal.archives-ouvertes.fr/docs/00/24/30/35/PDF/2006-06-13-1458.pdf
Download Restriction: no

Paper provided by HAL in its series Post-Print with number hal-00243035.

as
in new window

Length:
Date of creation: 2007
Date of revision:
Publication status: Published, The Journal of Risk and Insurance, 2007, 74, 2, 425-440
Handle: RePEc:hal:journl:hal-00243035
Note: View the original document on HAL open archive server: http://hal.archives-ouvertes.fr/hal-00243035/en/
Contact details of provider: Web page: http://hal.archives-ouvertes.fr/

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. Dionne, G. & Gane, R. & Vanasse, C., 1995. "Infessing Technological Parameters from Incomplete Panel Data," Cahiers de recherche 9537, Universite de Montreal, Departement de sciences economiques.
  2. Heckman, James J, 1979. "Sample Selection Bias as a Specification Error," Econometrica, Econometric Society, vol. 47(1), pages 153-61, January.
  3. 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.
  4. Steven B. Caudill & Mercedes Ayuso & Montserrat Guillén, 2005. "Fraud Detection Using a Multinomial Logit Model With Missing Information," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 72(4), pages 539-550.
  5. Dionne, G. & St-Michel, P. & Gibbens, A., 1993. "An Economic Analysis of Insurance Fraud," Cahiers de recherche 93010, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  6. El Bachir Belhadji & George Dionne & Faouzi Tarkhani, 2000. "A Model for the Detection of Insurance Fraud*," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan, vol. 25(4), pages 517-538, October.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:hal:journl:hal-00243035. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (CCSD)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.