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Development and validation of credit scoring models

Author

Listed:
  • Dennis Glennon
  • Nicholas M. Kiefer
  • C. Erik Larson
  • Hwan-sik Choi

Abstract

ABSTRACT Accurate credit granting decisions are crucial to the efficiency of the decentralized capital allocation mechanisms in modern market economies. Credit bureaus, and many financial institutions, have developed and used credit scoring models to standardize and automate, to the extent possible, credit decisions. We build credit scoring models for bankcard markets using the Office of the Comptroller of the Currency, Risk Analysis Division (OCC/RAD) consumer credit database (CCDB). This unusually rich data set allows us to evaluate a number of methods in common practice.We introduce, estimate and validate our models, using both out-of-sample contemporaneous and future validation data sets. Model performance is compared using both separation and accuracy measures. A vendor-developed generic bureau-based score is also included in the model performance comparisons. Our results indicate that current industry practices, when carefully applied, can produce models

Suggested Citation

  • Dennis Glennon & Nicholas M. Kiefer & C. Erik Larson & Hwan-sik Choi, . "Development and validation of credit scoring models," Journal of Credit Risk, Journal of Credit Risk.
  • Handle: RePEc:rsk:journ1:2160687
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    References listed on IDEAS

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    1. G. V. Kass, 1980. "An Exploratory Technique for Investigating Large Quantities of Categorical Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 29(2), pages 119-127, June.
    2. Kiefer, Nicholas M. & Larson, C. Erik, 2006. "Specification and Informational Issues in Credit Scoring," Working Papers 06-11, Cornell University, Center for Analytic Economics.
    3. Venkat Srinivasan & Yong H. Kim, 1987. "Note---The Bierman-Hausman Credit Granting Model: A Note," Management Science, INFORMS, vol. 33(10), pages 1361-1362, October.
    4. Harold Bierman, Jr. & Warren H. Hausman, 1970. "The Credit Granting Decision," Management Science, INFORMS, vol. 16(8), pages 519-532, April.
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    Cited by:

    1. Butaru, Florentin & Chen, Qingqing & Clark, Brian & Das, Sanmay & Lo, Andrew W. & Siddique, Akhtar, 2016. "Risk and risk management in the credit card industry," Journal of Banking & Finance, Elsevier, vol. 72(C), pages 218-239.

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    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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