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Ten-year evolution on credit risk research: a systematic literature review approach and discussion
Diez años de evolución en la investigación de riesgo de crédito: un enfoque y discusión de revisión sistemática de literatura
DOI:
https://doi.org/10.15446/ing.investig.v40n2.78649Keywords:
Credit Risk Assessment, Machine Learning, systematic literature review (en)Evaluación de Riesgo de Crédito, aprendizaje automático, Revisión sistemática de la literatura (es)
Given its importance in financial risk management, credit risk analysis, since its introduction in 1950, has been a major influence both in academic research and in practical situations. In this work, a systematic literature review is proposed which considers both “Credit Risk” and “Credit risk” as search parameters to answer two main research questions: are machine learning techniques being effectively applied in research about credit risk evaluation? Furthermore, which of these quantitative techniques have been mostly applied over the last ten years of research? Different steps were followed to select the papers for the analysis, as well as the exclusion criteria, in order to verify only papers with Machine Learning approaches. Among the results, it was found that machine learning is being extensively applied in Credit Risk Assessment, where applications of Artificial Intelligence (AI) were mostly found, more specifically Artificial Neural Networks (ANN). After the explanation of each answer, a discussion of the results is presented.
Dada su importancia en la gestión del riesgo financiero, el análisis del riesgo crediticio, desde su introducción en 1950, ha tenido una gran influencia tanto en investigaciones académicas como en situaciones prácticas. En este trabajo se propone una revisión bibliográfica sistemática que considere “Credit Risk” y “Credit risk” como parámetros de búsqueda para responder dos preguntas de investigación principales: ¿se están aplicando efectivamente las técnicas de aprendizaje automático en las investigaciones sobre la evaluación del riesgo de crédito? Incluso, ¿cuáles de estas técnicas cuantitativas se han aplicado mayoritariamente en los últimos diez años de investigación? Se siguieron diferentes pasos para seleccionar los artículos para el análisis, así como los criterios de exclusión para verificar solo los artículos con enfoques de aprendizaje automático. Entre los resultados, se encontró que el aprendizaje automático se está aplicando ampliamente en la Evaluación de Riesgo de Crédito, donde en su mayoría se encontraron aplicaciones de Inteligencia Artificial (AI), más específicamente, de Redes Neuronales Artificiales (ANN). Después de la explicación de cada respuesta, se presenta una discusión sobre los resultados.
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