Risk of refunding default in micro-finance institution by Bayesian networks : case of Tunisia

Abstract

The objective of this paper is twofold: measuring credit of institution microstructure and studying Enda inter-arab Tunisia by bayesian networks. After the data gathering characterizing of the customers requiring of the micro loans, this approach consists initially with the samples collected, then the setting in works about it of various network architectures and combinations of functions of activation and training and comparison between the results got and the results of the current methods used. To address this problem we will try to create a graph that will be used to develop our credit scoring using Bayesian networks as a method. After, we will bring out the variables that affect the credit worthiness of the beneficiaries of microcredit. Therefore this article will be divided so the first part is the theoretical side of the key variables that affect the rate of reimbursement and the second part a description of the variables, the research methodology and the main results.