Abstract
Financial inclusion is a social need that is gaining more and more strength in developing countries. Microcredit is an effective way to enable financial inclusion, but it represents a challenge in portfolio management. This work applies data analytics and machine learning techniques to predict the behavior of the loan default in a non-financial entity. Decision trees have shown the best prediction performance to determine whether a loan will be paid or become irrecoverable after running five predictive models.
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Herrera Román, J.S., Branch, J.W., Arango-Serna, M.D. (2021). Data Analytics in Financial Portfolio Recovery Management. In: Zapata-Cortes, J.A., Alor-Hernández, G., Sánchez-Ramírez, C., García-Alcaraz, J.L. (eds) New Perspectives on Enterprise Decision-Making Applying Artificial Intelligence Techniques. Studies in Computational Intelligence, vol 966. Springer, Cham. https://doi.org/10.1007/978-3-030-71115-3_16
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