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Variable reduction, sample selection bias and bank retail credit scoring

Author

Listed:
  • Marshall, Andrew
  • Tang, Leilei
  • Milne, Alistair

Abstract

This paper investigates the effect of including the customer loan approval process to the estimation of loan performance and explores the influence of sample selection bias in predicting the probability of default. The bootstrap variable reduction technique is applied to reduce the variable dimension for a large data-set drawn from a major UK retail bank. The results show a statistically significant correlation between the loan approval and performance processes. We further demonstrate an economically significant improvement in forecasting performance when taking into account sample selection bias. We conclude that financial institutions can obtain benefits by correcting for sample selection bias in their credit scoring models.

Suggested Citation

  • Marshall, Andrew & Tang, Leilei & Milne, Alistair, 2010. "Variable reduction, sample selection bias and bank retail credit scoring," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 501-512, June.
  • Handle: RePEc:eee:empfin:v:17:y:2010:i:3:p:501-512
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    References listed on IDEAS

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    1. Santos Silva, J.M.C. & Murteira, J.M.R., 2009. "Estimation of default probabilities using incomplete contracts data," Journal of Empirical Finance, Elsevier, vol. 16(3), pages 457-465, June.
    2. Sharpe, Steven A, 1990. " Asymmetric Information, Bank Lending, and Implicit Contracts: A Stylized Model of Customer Relationships," Journal of Finance, American Finance Association, vol. 45(4), pages 1069-1087, September.
    3. 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.
    4. 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.
    5. Machauer, Achim & Weber, Martin, 1998. "Bank behavior based on internal credit ratings of borrowers," Journal of Banking & Finance, Elsevier, vol. 22(10-11), pages 1355-1383, October.
    6. 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.
    7. Thomas, Lyn C., 2000. "A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers," International Journal of Forecasting, Elsevier, vol. 16(2), pages 149-172.
    8. Francis Vella, 1998. "Estimating Models with Sample Selection Bias: A Survey," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 127-169.
    9. 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.
    10. Blochlinger, Andreas & Leippold, Markus, 2006. "Economic benefit of powerful credit scoring," Journal of Banking & Finance, Elsevier, vol. 30(3), pages 851-873, March.
    11. Dinh, Thi Huyen Thanh & Kleimeier, Stefanie, 2007. "A credit scoring model for Vietnam's retail banking market," International Review of Financial Analysis, Elsevier, vol. 16(5), pages 471-495.
    12. Greene, William, 1998. "Sample selection in credit-scoring models1," Japan and the World Economy, Elsevier, vol. 10(3), pages 299-316, July.
    13. Kanatas, George, 1987. "Commercial paper, bank reserve requirements, and the informational role of loan commitments," Journal of Banking & Finance, Elsevier, vol. 11(3), pages 425-448, September.
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    Cited by:

    1. Tsukahara, Fábio Yasuhiro & Kimura, Herbert & Sobreiro, Vinicius Amorim & Zambrano, Juan Carlos Arismendi, 2016. "Validation of default probability models: A stress testing approach," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 70-85.
    2. repec:bap:journl:170404 is not listed on IDEAS
    3. Gabriela Kuvikova, 2015. "Loans for Better Living: The Role of Informal Collateral," CERGE-EI Working Papers wp541, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    4. Bücker, Michael & van Kampen, Maarten & Krämer, Walter, 2013. "Reject inference in consumer credit scoring with nonignorable missing data," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 1040-1045.

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