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A Social Approach to Microfinance Credit Scoring

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  • Carlos Serrano-Cinca
  • Begoña Gutiérrez-Nieto
  • Nydia M. Reyes

Abstract

Microfinance Institutions (MFIs) provide loans to low income individuals. The credit scoring systems of MFIs, if they exist, are strictly financial. Although many MFIs consider the social impact of their loans, they do not incorporate formal systems to estimate this social impact. This paper proposes that their creditworthiness evaluations should be coherent with their social mission and should, accordingly, estimate the social impact of microcredit. Thus, a decision support system to facilitate microcredit granting is proposed, and multicriteria evaluation is used to translate MFI’s social mission into numbers. The assessment of social impact is performed by calculating the Social Net Present Value (SNPV). The system captures credit officers’ experience and addresses incomplete and intangible information. The model has been tested in a microfinance institution. The paper illustrates an example of its use in practice.

Suggested Citation

  • Carlos Serrano-Cinca & Begoña Gutiérrez-Nieto & Nydia M. Reyes, 2013. "A Social Approach to Microfinance Credit Scoring," Working Papers CEB 13-013, ULB -- Universite Libre de Bruxelles.
  • Handle: RePEc:sol:wpaper:2013/140913
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    References listed on IDEAS

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    1. Vogelgesang, Ulrike, 2003. "Microfinance in Times of Crisis: The Effects of Competition, Rising Indebtedness, and Economic Crisis on Repayment Behavior," World Development, Elsevier, vol. 31(12), pages 2085-2114, December.
    2. Wiginton, John C., 1980. "A Note on the Comparison of Logit and Discriminant Models of Consumer Credit Behavior," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 15(3), pages 757-770, September.
    3. Carlos Serrano-Cinca & Begoña Guti鲲ez-Nieto, 2013. "A decision support system for financial and social investment," Applied Economics, Taylor & Francis Journals, vol. 45(28), pages 4060-4070, October.
    4. D. J. Hand & W. E. Henley, 1997. "Statistical Classification Methods in Consumer Credit Scoring: a Review," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 160(3), pages 523-541, September.
    5. Zeller, Manfred, 1998. "Determinants of Repayment Performance in Credit Groups: The Role of Program Design, Intragroup Risk Pooling, and Social Cohesion," Economic Development and Cultural Change, University of Chicago Press, vol. 46(3), pages 599-620, April.
    6. 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.
    7. Beatriz Armendáriz & Ariane Szafarz, 2011. "On Mission Drift in Microfinance Institutions," World Scientific Book Chapters, in: Beatriz Armendáriz & Marc Labie (ed.), The Handbook Of Microfinance, chapter 16, pages 341-366, World Scientific Publishing Co. Pte. Ltd..
    8. Yoram Wind & Thomas L. Saaty, 1980. "Marketing Applications of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 26(7), pages 641-658, July.
    9. Sharma, Manohar & Zeller, Manfred, 1997. "Repayment performance in group-based credit programs in Bangladesh: An empirical analysis," World Development, Elsevier, vol. 25(10), pages 1731-1742, October.
    10. Robert Cull & Asli Demirguç-Kunt & Jonathan Morduch, 2007. "Financial performance and outreach: a global analysis of leading microbanks," Economic Journal, Royal Economic Society, vol. 117(517), pages 107-133, February.
    11. Berger, Allen N. & Black, Lamont K., 2011. "Bank size, lending technologies, and small business finance," Journal of Banking & Finance, Elsevier, vol. 35(3), pages 724-735, March.
    12. Ronald U. Mendoza, 2011. "Why do the poor pay more? Exploring the poverty penalty concept," Journal of International Development, John Wiley & Sons, Ltd., vol. 23(1), pages 1-28, January.
    13. 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.
    14. Joris Van Gool & Wouter Verbeke & Piet Sercu & Bart Baesens, 2012. "Credit scoring for microfinance: is it worth it?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 17(2), pages 103-123, April.
    15. Begoña Gutiérrez Nieto & Carlos Serrano Cinca, 2006. "Factors explaining the rating of Microfinance Institutions," Documentos de Trabajo dt2006-03, Facultad de Ciencias Económicas y Empresariales, Universidad de Zaragoza.
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    Cited by:

    1. Hernandez, Manuel A. & Torero, Maximo, 2018. "A poverty-sensitive scorecard to prioritize lending and grant allocation: Evidence from Central America," Food Policy, Elsevier, vol. 77(C), pages 81-90.

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    Keywords

    microfinance; credit scoring; decision support system; social impact; multicriteria; social finance;
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