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Does reject inference really improve the performance of application scoring models?

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  • Crook, Jonathan
  • Banasik, John

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  • Crook, Jonathan & Banasik, John, 2004. "Does reject inference really improve the performance of application scoring models?," Journal of Banking & Finance, Elsevier, vol. 28(4), pages 857-874, April.
    • Handle: RePEc:eee:jbfina:v:28:y:2004:i:4:p:857-874
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    References listed on IDEAS

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    1. James J. Heckman, 2001. "Micro Data, Heterogeneity, and the Evaluation of Public Policy: Nobel Lecture," Journal of Political Economy, University of Chicago Press, vol. 109(4), pages 673-748, August.
    2. J Banasik & J Crook & L Thomas, 2003. "Sample selection bias in credit scoring models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(8), pages 822-832, August.
    3. Reichert, Alan K & Cho, Chien-Ching & Wagner, George M, 1983. "An Examination of the Conceptual Issues Involved in Developing Credit-scoring Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(2), pages 101-114, April.
    4. 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.
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