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Can Credit-Scoring Models Effectively Predict Microloans Default? Statistical Evidence from the Tunisian Microfinance Bank

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  • Ibtissem Baklouti

    (Faculty of Economics and Management, University of Sfax, Tunisia)

  • Abdelfettah Bouri

    (Faculty of Economics and Management, University of Sfax, Tunisia)

Abstract

No abstract received.

Suggested Citation

  • Ibtissem Baklouti & Abdelfettah Bouri, 2013. "Can Credit-Scoring Models Effectively Predict Microloans Default? Statistical Evidence from the Tunisian Microfinance Bank," Global Credit Review (GCR), World Scientific Publishing Co. Pte. Ltd., vol. 3(01), pages 57-69.
    • Handle: RePEc:wsi:gcrxxx:v:03:y:2013:i:01:n:s2010493613500050
    DOI: 10.1142/S2010493613500050
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    References listed on IDEAS

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    1. Laibson, David I. & Agarwal, Sumit & Driscoll, John C. & Gabaix, Xavier, 2009. "The Age of Reason: Financial Decisions over the Life-Cycle with Implications for Regulation," Scholarly Articles 4554335, Harvard University Department of Economics.
    2. Marguerite S. Robinson, 2001. "The Microfinance Revolution," World Bank Publications - Books, The World Bank Group, number 28956.
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    Cited by:

    1. Ibtissem Baklouti, 2014. "A Psychological Approach To Microfinance Credit Scoring Via A Classification And Regression Tree," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 21(4), pages 193-208, October.

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