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Microcredit Scoring with Fuzzy Logic Model

R. Aboulaich, F. I. Khamlichi, M. Kaicer


In this paper, emphasis is put on learning machines, in particular, fuzzy logic model due to its played role in several utilities that can certainly be represented in credit scoring. To go more specific, such utilities can be clearly seen in Mircocredit scoring for MFIs (Micro Finance Institution).

The collected data examines a microcredit loan that is most of the time at the risk of not being refunded; the data major findings are carefully selected and supported by the ARDI Moroccan foundation of Microcredits. It represents borrower’s characteristics that can be our main criterion to make the study reach its ends.

In this work a fuzzy model for credit scoring is proposed in order to help the MFI’s to take decisions, the model plays here a major role as it predicts the borrower’s behavior so that it is offering us a significant tool in minimizing the risk of not refunding a loan, consequently, by the reported specifications of the borrower’s behavior. This model can successfully state individuals rather than groups to be or not to be offered the loan.


Microcredit, Fuzzy model, Credit scoring

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