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Bank Lending Policy, Credit Scoring and the Survival of Loans

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  • Roszbach, Kasper

    () (Dept. of Economics, Stockholm School of Economics)

Abstract

To evaluate loan applicants, banks use a large variety of systems. The objective of such credit scoring models typically is to minimize default rates or the number of incorrectly classified loans. Thereby they fail to take into account that loans are multiperiod contracts. From a utility maximizing perspective it is not only important to know if but also when a loan will default. In this paper a Tobit model with a variable censoring threshold and sample selection effects is estimated for (1) the decision to provide a loan or not and (2) the survival of granted loans. The model is shown to be an affective tool to separate applicants with short survival times from those with long survivals The bank´s loan provision process is shown to be inefficient. Loans are granted in a way that conflicts with both default risk minimization and survival time maximization. There is thus no trade-off between higher default risk and higher return in the policy of banks.

Suggested Citation

  • Roszbach, Kasper, 1998. "Bank Lending Policy, Credit Scoring and the Survival of Loans," SSE/EFI Working Paper Series in Economics and Finance 261, Stockholm School of Economics.
  • Handle: RePEc:hhs:hastef:0261
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    References listed on IDEAS

    as
    1. Jacobson, Tor & Roszbach, Kasper, 2003. "Bank lending policy, credit scoring and value-at-risk," Journal of Banking & Finance, Elsevier, vol. 27(4), pages 615-633, April.
    2. Stephen D. Williamson, 1987. "Costly Monitoring, Loan Contracts, and Equilibrium Credit Rationing," The Quarterly Journal of Economics, Oxford University Press, vol. 102(1), pages 135-145.
    3. Dionne, Georges & Artis, Manuel & Guillen, Montserrat, 1996. "Count data models for a credit scoring system," Journal of Empirical Finance, Elsevier, vol. 3(3), pages 303-325, September.
    4. 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.
    5. 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.
    6. 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.
    7. Townsend, Robert M, 1982. "Optimal Multiperiod Contracts and the Gain from Enduring Relationships under Private Information," Journal of Political Economy, University of Chicago Press, vol. 90(6), pages 1166-1186, December.
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    More about this item

    Keywords

    Banks; lending policy; credit scoring; survival; loans.;
    All these keywords.

    JEL classification:

    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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