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Consumer credit scoring: do situational circumstances matter?

Author

Listed:
  • Robert B. Avery

    (Board of Governors of the Federal Reserve System)

  • Paul S. Calem

    (Board of Governors of the Federal Reserve System - Division of Research)

  • Glenn B. Canner

    (Statistics)

Abstract

Although credit history scoring offers benefits to lenders and borrowers, failure to consider situational circumstances raises important statistical issues that may affect the ability of scoring systems to accurately quantify an individual's credit risk. Evidence from a national sample of credit reporting agency records suggests that failure to consider measures of local economic circumstances and individual trigger events when developing credit history scores can diminish the potential effectiveness of such models. There are practical difficulties, however, associated with developing scoring models that incorporate situational data, arising largely because of inherent limitations of the credit reporting agency databases used to build scoring models.

Suggested Citation

  • Robert B. Avery & Paul S. Calem & Glenn B. Canner, 2004. "Consumer credit scoring: do situational circumstances matter?," BIS Working Papers 146, Bank for International Settlements.
  • Handle: RePEc:bis:biswps:146
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    References listed on IDEAS

    as
    1. Robert M. Hunt, 2002. "The development and regulation of consumer credit reporting in America," Working Papers 02-21, Federal Reserve Bank of Philadelphia.
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    Cited by:

    1. de Andrade, Fabio Wendling Muniz & Thomas, Lyn, 2007. "Structural models in consumer credit," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1569-1581, December.
    2. Evžen Kocenda & Martin Vojtek, 2011. "Default Predictors in Retail Credit Scoring: Evidence from Czech Banking Data," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 47(6), pages 80-98, November.
    3. Leow, Mindy & Crook, Jonathan, 2014. "Intensity models and transition probabilities for credit card loan delinquencies," European Journal of Operational Research, Elsevier, vol. 236(2), pages 685-694.
    4. Miettinen Marika Rosanna & Littunen Hannu, 2013. "Factors Contributing to the Success of Start-Up Firms Using Two-Point or Multiple-Point Scale Models," Entrepreneurship Research Journal, De Gruyter, vol. 3(4), pages 449-481, June.
    5. Souphala Chomsisengphet & Ronel Elul, 2005. "Bankruptcy exemptions, credit history, and the mortgage market," Working Papers 04-14, Federal Reserve Bank of Philadelphia.
    6. Javier Gutiérrez Rueda & Dairo Estrada & Laura Capera, "undated". "Un análisis del endeudamiento de los hogares," Temas de Estabilidad Financiera 061, Banco de la Republica de Colombia.
    7. Dorfleitner, G. & Just-Marx, S. & Priberny, C., 2017. "What drives the repayment of agricultural micro loans? Evidence from Nicaragua," The Quarterly Review of Economics and Finance, Elsevier, vol. 63(C), pages 89-100.
    8. Iulia Iuga & Ruxandra Lazea, 2012. "Study Regarding The Influence Of The Unemployment Rate Over Non-Performing Loans In Romania Using The Correlation Indicator," Annales Universitatis Apulensis Series Oeconomica, Faculty of Sciences, "1 Decembrie 1918" University, Alba Iulia, vol. 2(14), pages 1-18.
    9. Evžen Kocenda & Martin Vojtek, 2011. "Default Predictors in Retail Credit Scoring: Evidence from Czech Banking Data," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 47(6), pages 80-98, November.
    10. Gush, Karon & Scott, James & Laurie, Heather, 2015. "Job loss and social capital: the role of family, friends and wider support networks," ISER Working Paper Series 2015-07, Institute for Social and Economic Research.
    11. repec:kap:ejlwec:v:44:y:2017:i:1:d:10.1007_s10657-014-9436-1 is not listed on IDEAS
    12. repec:pal:jorsoc:v:61:y:2010:i:3:d:10.1057_jors.2009.99 is not listed on IDEAS
    13. He, Ping & Hua, Zhongsheng & Liu, Zhixin, 2015. "A quantification method for the collection effect on consumer term loans," Journal of Banking & Finance, Elsevier, vol. 57(C), pages 17-26.
    14. Rodrigo Alfaro & Natalia Gallardo & Roberto Stein, 2010. "The Determinants of Household Debt Defa," Working Papers Central Bank of Chile 574, Central Bank of Chile.
    15. Khandani, Amir E. & Kim, Adlar J. & Lo, Andrew W., 2010. "Consumer credit-risk models via machine-learning algorithms," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2767-2787, November.
    16. Oh, Joon-Hee & Johnston, Wesley J., 2014. "Credit lender–borrower relationship in the credit card market – Implications for credit risk management strategy and relationship marketing," International Business Review, Elsevier, vol. 23(6), pages 1086-1095.
    17. repec:pal:jorsoc:v:57:y:2006:i:6:d:10.1057_palgrave.jors.2602038 is not listed on IDEAS
    18. Federico Ferretti, 2007. "Consumer credit information systems: a critical review of the literature. Too little attention paid by Lawyers?," European Journal of Law and Economics, Springer, vol. 23(1), pages 71-88, February.
    19. Chomsisengphet, Souphala & Elul, Ronel, 2006. "Bankruptcy exemptions, credit history, and the mortgage market," Journal of Urban Economics, Elsevier, vol. 59(1), pages 171-188, January.
    20. Fabián Enrique Salazar Villano, 2013. "Cuantificación del riesgo de incumplimiento en créditos de libre inversión: un ejercicio econométrico para una entidad bancaria del municipio de Popayán, Colombia," ESTUDIOS GERENCIALES, UNIVERSIDAD ICESI, December.

    More about this item

    Keywords

    Credit scoring; Consumer credit; Credit risk;

    JEL classification:

    • G2 - Financial Economics - - Financial Institutions and Services

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