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

A Quantitative Theory of Credit Scoring

  • Xuan Tam

    (Cambridge University)

  • Eric Young

    (University of Virginia)

  • Kartik Athreya

    (Federal Reserve Bank of Richmond)

Starting in the early 1990s credit scoring became widespread and central in credit granting decisions. Credit scores are scalar representations of default risk. They are used, in turn, to price credit, and as a result alter household borrowing and default decisions. We build on recent work on defaultable consumer credit under asymmetric information to develop a quantitative theory of credit scores. We construct and solve a rich and quantitatively-disciplined lifecycle model of consumption in which households have access to defaultable debt, and lenders are asymmetrically informed about household characteristics relevant to predicting default. We then allow lenders to keep record of inferences on the hidden type of a borrower, as well as a binary 'flag' indicating a past default. These inferences arise endogenously from a signalling game induced by borrowers' need to obtain loans. We show how lenders’ inferences evolve over the lifecycle as a function of household behavior in a way that can be naturally interpreted as 'credit scores.' In particular, we first show that lenders' assessments that a household has relatively low default risk matter significantly for the interest rates households pay. We then show that such assessments rise most sharply an d interest rates paid by borrowers fall most sharply (on the order of 5-6 percentage points) when the bankruptcy flag is removed, consistent with work of Musto (2005). Lastly, we compare allocations across information regimes to provide a measure of the social value of credit scores, and the dependence of these measures on lenders' ability to observe borrower characteristics.

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 Society for Economic Dynamics in its series 2013 Meeting Papers with number 382.

in new window

Date of creation: 2013
Date of revision:
Handle: RePEc:red:sed013:382
Contact details of provider: Postal: Society for Economic Dynamics Marina Azzimonti Department of Economics Stonybrook University 10 Nicolls Road Stonybrook NY 11790 USA
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. Fay, S. & Hurst, E. & White, M.J., 1998. "The Bankruptcy Decision: Does Stigma Matter?," Papers 98-01, Michigan - Center for Research on Economic & Social Theory.
  2. Hellwig, Martin, 1989. "Asymmetric information, financial markets, and financial institutions Where are we currently going?," European Economic Review, Elsevier, vol. 33(2-3), pages 277-285, March.
  3. Banks, Jeffrey S & Sobel, Joel, 1987. "Equilibrium Selection in Signaling Games," Econometrica, Econometric Society, vol. 55(3), pages 647-61, May.
  4. Mas-Colell, Andreu & Whinston, Michael D. & Green, Jerry R., 1995. "Microeconomic Theory," OUP Catalogue, Oxford University Press, number 9780195102680.
  5. Kartik Athreya & Xuan S. Tam & Eric R. Young, 2012. "A Quantitative Theory of Information and Unsecured Credit," American Economic Journal: Macroeconomics, American Economic Association, vol. 4(3), pages 153-83, July.
  6. David B. Gross & Nicholas S. Souleles, 2001. "An Empirical Analysis of Personal Bankruptcy and Delinquency," NBER Working Papers 8409, National Bureau of Economic Research, Inc.
  7. In-Koo Cho & David M. Kreps, 1997. "Signaling Games and Stable Equilibria," Levine's Working Paper Archive 896, David K. Levine.
  8. Athreya, Kartik & Sánchez, Juan M. & Tam, Xuan S. & Young, Eric R., 2012. "Bankruptcy and delinquency in a model of unsecured debt," Working Papers 2012-042, Federal Reserve Bank of St. Louis, revised 30 Jan 2014.
  9. David K. Musto, 2004. "What Happens When Information Leaves a Market? Evidence from Postbankruptcy Consumers," The Journal of Business, University of Chicago Press, vol. 77(4), pages 725-748, October.
  10. Juan M. Sánchez, 2010. "The IT revolution and the unsecured credit market," Working Papers 2010-022, Federal Reserve Bank of St. Louis.
  11. Borghan Nezami Narajabad, 2012. "Information Technology and the Rise of Household Bankruptcy," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 15(4), pages 526-550, 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:red:sed013:382. 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: (Christian Zimmermann)

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.