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A Quantitative Theory of Credit Scoring

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  • Xuan Tam

    (Cambridge University)

  • Eric Young

    (University of Virginia)

  • Kartik Athreya

    (Federal Reserve Bank of Richmond)

Abstract

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.

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Bibliographic Info

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

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Date of creation: 2013
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Handle: RePEc:red:sed013:382

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  1. 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.
  2. Kartik Athreya, 2008. "A Quantitative Theory of Information and Unsecured Credit," 2008 Meeting Papers 68, Society for Economic Dynamics.
  3. 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.
  4. In-Koo Cho & David M. Kreps, 1997. "Signaling Games and Stable Equilibria," Levine's Working Paper Archive 896, David K. Levine.
  5. 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.
  6. Banks, Jeffrey S. & Sobel, Joel., 1985. "Equilibrium Selection in Signaling Games," Working Papers 565, California Institute of Technology, Division of the Humanities and Social Sciences.
  7. Mas-Colell, Andreu & Whinston, Michael D. & Green, Jerry R., 1995. "Microeconomic Theory," OUP Catalogue, Oxford University Press, number 9780195102680, September.
  8. 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.
  9. 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.
  10. 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.
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