CREDIT SCORING MODELS FOR MICROCREDITS: A LITERATURE REVIEW

The provision of microcredits has been considered to have an active role in reducing poverty and promoting economic growth for small entrepreneurs. Many academics have referred to the topic of introducing credit scoring models for managing borrowers' credit risk. These models have the aim to discriminate between good and bad borrowers, aiding the microfinance institutions in lowering their costs and the timing of the credit granting process as well as enhancing their outreach. Over the last decades, these investigations have covered microfinance institutions from all over the world, focusing on developing countries. Some have the objective of predicting the probability of default of any microcredit, while others refer to attrition or the possibility that microcredits may generate a certain spell of arrears. Microfinance institutions that use credit scoring models appear to be more productive at lower costs, increasing their small business loan portfolio, providing geographically diversified loans and expanding the availability of credit. Since the first credit scoring model for microfinance, there has been an intense development in the literature, regarding the type of explanatory variables considered in the models, the different statistical tools applied and the kind of risks predicted. Currently, innovative approaches in the implementation of credit scoring methodology to microfinance institutions are coming to light. The aim of this paper is to present a literature review of the state-of-the-art on credit scoring models for microcredits, pointing their factors in common, evaluating them critically and establishing the topics of future research.