IDEAS home Printed from
   My bibliography  Save this paper

A Scoring Model of the Risk of Costly Arrears at a Microfinance Lender in Bolivia


  • Mark Schreiner

    (Washington University in St. Louis)


Can scoring models help microfinance lenders in poor countries as much as they have helped credit-card lenders in rich countries? I model the probability that loans from a microlender in Bolivia had arrears of 15 days or more. Although arrears in microfinance depend on many factors difficult to include in statistical models, I find that inexpensive data does indeed have some predictive power. In microfinance, computer models will not replace loan officers, but they can flag the highest risks and act as a cross-check on human judgement.

Suggested Citation

  • Mark Schreiner, 2001. "A Scoring Model of the Risk of Costly Arrears at a Microfinance Lender in Bolivia," Development and Comp Systems 0109005, EconWPA.
  • Handle: RePEc:wpa:wuwpdc:0109005
    Note: Type of Document - Adobe Acrobat 3.0; prepared on Windows 98; to print on Adobe Acrobat 3.0; pages: ; figures: Included in pdf file

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Jens Reinke, 1998. "How to lend like mad and make a profit: A micro-credit paradigm versus the start-up fund in South Africa," Journal of Development Studies, Taylor & Francis Journals, vol. 34(3), pages 44-61.
    2. 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.
    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. 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.
    5. Zeller, Manfred, 1996. "Determinants of repayment performance in credit groups," FCND discussion papers 13, International Food Policy Research Institute (IFPRI).
    6. Loretta J. Mester, 1997. "What's the point of credit scoring?," Business Review, Federal Reserve Bank of Philadelphia, issue Sep, pages 3-16.
    7. Peter Kennedy, 2003. "A Guide to Econometrics, 5th Edition," MIT Press Books, The MIT Press, edition 5, volume 1, number 026261183x, January.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    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. Mermelstein, David A., 2006. "Defaults en carteras hipotecarias, macroeconomía y arreglos institucionales: Más allá de los modelos de Credit-Scoring tradicionales
      [Mortgage defaults, macroeconomics, and institutional arrangemen
      ," MPRA Paper 7535, University Library of Munich, Germany.
    3. Mark Schreiner, 2001. "Audit Sampling Microfinance Portfolio-at-Risk," Computational Economics 0109001, EconWPA.
    4. Kuhn, M.E. & Darroch, Mark A.G. & Ortmann, Gerald F., 2000. "Assessing the efficacy of a South African microlender's loan screening mechanism," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 39(4), December.
    5. Rayo Cantón, Salvador & Lara Rubio, Juan & Camino Blasco, David, 2010. "A Credit Scoring Model For Institutions Of Microfinance Under The Basel Ii Normative," Journal of Economics, Finance and Administrative Science, Universidad ESAN, vol. 15(28), pages 89-124.

    More about this item


    Scoring; risk management; credit risk; Bolivia; microfinance;

    JEL classification:

    • O57 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Comparative Studies of Countries
    • O54 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Latin America; Caribbean

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wpa:wuwpdc:0109005. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (EconWPA). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.