IDEAS home Printed from
MyIDEAS: Login to save this paper or follow this series

The Impact of Sample Bias on Consumer Credit Scoring Performance and Profitability





This article seeks to gain insight into the influence of sample bias in a consumer credit scoring model. In earlier research, sample bias has been suggested to pose a sizeable threat to predictive performance and profitability due to its implications on either population drainage or biased estimates. Contrary to previous – mainly theoretical – research on sample bias, the unique features of the dataset used in this study provide the opportunity to investigate the issue in an empirical setting. Based on the data of a mail-order company offering short term consumer credit to their consumers, we show that (i) given a certain sample size, sample bias has a significant effect on consumer credit-scoring performance and profitability, (ii) its effect is composed of the inclusion of rejected orders in the scoring model, and the inclusion of these orders into the variable-selection process, and (iii) the impact of the effect of sample bias on consumer credit scoring performance and profitability is modest.

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:
Download Restriction: no

Paper provided by Ghent University, Faculty of Economics and Business Administration in its series Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium with number 04/232.

in new window

Length: 29 pages
Date of creation: Mar 2004
Date of revision:
Handle: RePEc:rug:rugwps:04/232
Contact details of provider: Postal: Hoveniersberg 4, B-9000 Gent
Phone: ++ 32 (0) 9 264 34 61
Fax: ++ 32 (0) 9 264 35 92
Web page:

More information through EDIRC

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. Thomas, L.C. & Ho, J. & Scherer, W.T., 2001. "Time will tell: Behavioural Scoring and the Dynamics of Consumer Credit Assessment," Papers 01-174, University of Southampton - Department of Accounting and Management Science.
  2. Heckman, James J, 1979. "Sample Selection Bias as a Specification Error," Econometrica, Econometric Society, vol. 47(1), pages 153-61, January.
  3. Baesens, Bart & Viaene, Stijn & Van den Poel, Dirk & Vanthienen, Jan & Dedene, Guido, 2002. "Bayesian neural network learning for repeat purchase modelling in direct marketing," European Journal of Operational Research, Elsevier, vol. 138(1), pages 191-211, April.
  4. D. J. Hand & W. E. Henley, 1997. "Statistical Classification Methods in Consumer Credit Scoring: a Review," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 160(3), pages 523-541.
  5. Desai, Vijay S. & Crook, Jonathan N. & Overstreet, George A., 1996. "A comparison of neural networks and linear scoring models in the credit union environment," European Journal of Operational Research, Elsevier, vol. 95(1), pages 24-37, November.
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:rug:rugwps:04/232. 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: (Nathalie Verhaeghe)

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.