Conditioning factors of default in microcredit operations
Abstract
This paper aims to identify and analyze the factors that influence the default in loans granted by two microfinance institutions, the BLUSOL of Santa Catarina and the Banco do Empreendedor do Maranhão (BEM). The quantitative research was based on information extracted from 20,033 (data universe) credit contracts awarded between 2003 and 2009. The Binary Logistic Regression Model was used for data analysis. The statistically significant variables that contribute to the reduction of default are: higher educational level, female, married, longer existence and informality of the business; contract of credit renewal and amount of credit. The statistical model was effective in achieving the proposed objectives, with a rate of 83.68% of probability of correct prediction. We conclude that, despite the specificities of microfinancing, it is possible to use statistical models as instruments to support the process of credit granting and risk assessment and of decision making.
Key words: credit, credit risk, microcredit, default.
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