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Bank Lending Policy, Credit Scoring, and the Survival of Loans

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  • Kasper Roszbach

    (Sveriges Riksbank)

Abstract

To evaluate loan applicants, banks increasingly use credit scoring models. The objective of such 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, for which reason it is important for banks not only to know if but also when a loan will default. In this paper a bivariate 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 time of granted loans. The model proves to be an effective tool to separate applicants with short and with long survival times. 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 lending policy. © 2004 President and Fellows of Harvard College and the Massachusetts Institute of Technology.

Suggested Citation

  • Kasper Roszbach, 2004. "Bank Lending Policy, Credit Scoring, and the Survival of Loans," The Review of Economics and Statistics, MIT Press, vol. 86(4), pages 946-958, November.
    • Handle: RePEc:tpr:restat:v:86:y:2004:i:4:p:946-958
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    1. 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.
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    More about this item

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • E51 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Money Supply; Credit; Money Multipliers

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