UN MODELE DE “CREDIT SCORING” POUR UNE INSTITUTION DE MICRO-FINANCE AFRICAINE: LE CAS DE NYESIGISO AU MALI

Boubacar Diallo ()
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Boubacar Diallo: LEO - Laboratoire d'économie d'Orleans [2008-2011] - UO - Université d'Orléans - CNRS - Centre National de la Recherche Scientifique

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Abstract: The aim of this research is to develop a scoring model using logistic regression and multivariate discriminant analysis applied to 269 individual loans of Nyèsigiso in Mali. The results have shown the importance of long term relationship, interest rate, transaction costs and credit rationing in the prediction of loan default. Overall, the model developed correctly predicts more than 70% of cases. A more conservative setting of the cut off point (from 0.5 to 0.4) significantly improves the predictive power for bad loans. The research points out the great importance of some variables related to transactions costs and long term relationship for the prediction of the likelihood to default. The rejection inference analysis has shown the consistency of the model's prediction with the institution rejection decision.

Keywords: Micro-finance; Credit Scoring; Régression logistique; Probabilité de défaut (search for similar items in EconPapers)
Date: 2006-05-16
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00069163
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Citations: View citations in EconPapers (6)

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