Advanced Search
MyIDEAS: Login

Count data models for a credit scoring system

Contents:

Author Info

  • Dionne, Georges
  • Artis, Manuel
  • Guillen, Montserrat

Abstract

Credit scoring systems created for the evaluation of new applications are based on the available statistical information which is related to the behaviour of former clients with credit. Usually, financial institutions apply discriminant analysis techniques to create these systems but they lack of good properties due, for example, to the presence of non-normal variables. As an alternative, the future repayment behaviour is predicted by means of the expected number of unpaid instalments. The use of this latter variable suggests that appropriate models might be of interest, in which some covariant exogenous variables are included in order to specify the expected level of debt. At this point, prepayment is not explicitly considered. These models should be used as explanatory tools when evaluating the level of risk involved in personal credit transactions. Negative Binomial Distribution models are suitable when heterogeneity is taken into account. Some results related to prediction performance are shown for different model specifications in the case of data from a Spanish bank.

(This abstract was borrowed from another version of this item.)

Download Info

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://www.sciencedirect.com/science/article/B6VFG-3VTYSVD-3/2/533860652ef12df30cf25cbbf3d7865d
Download Restriction: Full text for ScienceDirect subscribers only

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Bibliographic Info

Article provided by Elsevier in its journal Journal of Empirical Finance.

Volume (Year): 3 (1996)
Issue (Month): 3 (September)
Pages: 303-325

as in new window
Handle: RePEc:eee:empfin:v:3:y:1996:i:3:p:303-325

Contact details of provider:
Web page: http://www.elsevier.com/locate/jempfin

Related research

Keywords:

Other versions of this item:

References

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. Jerry A. Hausman & Bronwyn H. Hall & Zvi Griliches, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," NBER Technical Working Papers 0017, National Bureau of Economic Research, Inc.
  2. Fenn, Paul T, 1981. "Sickness Duration, Residual Disability, and Income Replacement: An Empirical Analysis," Economic Journal, Royal Economic Society, vol. 91(361), pages 158-73, March.
  3. Stiglitz, Joseph E & Weiss, Andrew, 1981. "Credit Rationing in Markets with Imperfect Information," American Economic Review, American Economic Association, vol. 71(3), pages 393-410, June.
  4. Cameron, A Colin & Trivedi, Pravin K, 1986. "Econometric Models Based on Count Data: Comparisons and Applications of Some Estimators and Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 1(1), pages 29-53, January.
  5. Dionne, Georges & Doherty, Neil A, 1994. "Adverse Selection, Commitment, and Renegotiation: Extension to and Evidence from Insurance Markets," Journal of Political Economy, University of Chicago Press, vol. 102(2), pages 209-35, April.
  6. Boyd, J.h. & Smith, B.D., 1991. "The Equilibrium Allocation of Investment Capital in the Presence of Adverse Selection and Costly State Verification," RCER Working Papers 289, University of Rochester - Center for Economic Research (RCER).
  7. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Applications to Poisson Models," Econometrica, Econometric Society, vol. 52(3), pages 701-20, May.
  8. Boyes, William J. & Hoffman, Dennis L. & Low, Stuart A., 1989. "An econometric analysis of the bank credit scoring problem," Journal of Econometrics, Elsevier, vol. 40(1), pages 3-14, January.
  9. Gourieroux Christian & Monfort Alain & Trognon A, 1981. "Pseudo maximum likelihood methods : theory," CEPREMAP Working Papers (Couverture Orange) 8129, CEPREMAP.
  10. Steenackers, A. & Goovaerts, M. J., 1989. "A credit scoring model for personal loans," Insurance: Mathematics and Economics, Elsevier, vol. 8(1), pages 31-34, March.
  11. Mullahy, John, 1986. "Specification and testing of some modified count data models," Journal of Econometrics, Elsevier, vol. 33(3), pages 341-365, December.
  12. Dionne, G. & Gagne, R. & Gagnon, F. & Vanasse, C., 1993. "Debt, Moral Hazard and Airline Safety : An Empirical Evidence," Cahiers de recherche 9309, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  13. Crocker, Keith J & Snow, Arthur, 1986. "The Efficiency Effects of Categorical Discrimination in the Insurance Industry," Journal of Political Economy, University of Chicago Press, vol. 94(2), pages 321-44, April.
  14. Rose, Nancy L, 1990. "Profitability and Product Quality: Economic Determinants of Airline Safety Performance," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages 944-64, October.
  15. Jaffee, Dwight M & Russell, Thomas, 1976. "Imperfect Information, Uncertainty, and Credit Rationing," The Quarterly Journal of Economics, MIT Press, vol. 90(4), pages 651-66, November.
  16. Fourgeaud Claude & Gourieroux Christian & Pradel Jacqueline, 1990. "Sélection de clientèle et tarification de prêt bancaire," CEPREMAP Working Papers (Couverture Orange) 9004, CEPREMAP.
  17. Grogger, J T & Carson, Richard T, 1991. "Models for Truncated Counts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(3), pages 225-38, July-Sept.
Full references (including those not matched with items on IDEAS)

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. Roszbach, Kasper, 2003. "Bank Lending Policy, Credit Scoring and the Survival of Loans," Working Paper Series 154, Sveriges Riksbank (Central Bank of Sweden).
  2. Artis, Manuel & Ayuso, Mercedes & Guillen, Montserrat, 1999. "Modelling different types of automobile insurance fraud behaviour in the Spanish market," Insurance: Mathematics and Economics, Elsevier, vol. 24(1-2), pages 67-81, March.
  3. Santos Silva, J.M.C. & Murteira, J.M.R., 2009. "Estimation of default probabilities using incomplete contracts data," Journal of Empirical Finance, Elsevier, vol. 16(3), pages 457-465, June.
  4. Yaldız Hanedar, Elmas & Broccardo, Eleonora & Bazzana, Flavio, 2014. "Collateral requirements of SMEs: The evidence from less-developed countries," Journal of Banking & Finance, Elsevier, vol. 38(C), pages 106-121.
  5. Elmas Yaldiz Hanedar & Eleonora Broccardo & Flavio Bazzana, 2012. "Collateral Requirements of SMEs:The Evidence from Less–Developed Countries," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 12111, Universita di Modena e Reggio Emilia, Facoltà di Economia "Marco Biagi".
  6. 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.
  7. Ulrich Kaiser & Andrea Szczesny, 2000. "Einfache oekonomische Verfahren fuer die Kreditrisikomessung," CoFE Discussion Paper 00-28, Center of Finance and Econometrics, University of Konstanz.
  8. Murray Smith, 2003. "On dependency in double-hurdle models," Statistical Papers, Springer, vol. 44(4), pages 581-595, October.
  9. Woo, Mi-Ja & Sriram, T.N., 2007. "Robust estimation of mixture complexity for count data," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4379-4392, May.
  10. 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.
  11. Marshall, Andrew & Tang, Leilei & Milne, Alistair, 2010. "Variable reduction, sample selection bias and bank retail credit scoring," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 501-512, June.
  12. Carling, Kenneth & Jacobson, Tor & Roszbach, Kasper, 2001. "Dormancy risk and expected profits of consumer loans," Journal of Banking & Finance, Elsevier, vol. 25(4), pages 717-739, April.

Lists

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

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:eee:empfin:v:3:y:1996:i:3:p:303-325. 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: (Zhang, Lei).

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.