Traditionally, loan officers use different credit scoring models to complement judgmental methods to classify consumer loan applications. This study explores the use of decision trees, AdaBoost, and support vector machines (SVMs) to identify potential bad loans. Our results show that AdaBoost does provide an improvement over simple decision trees as well as SVM models in predicting good credit clients and bad credit clients. To cross-validate our results, we use k-fold classification methodology.
Malhotra, D.K., Malhotra, K. and Malhotra, R. (2020), "Evaluating Consumer Loans Using Machine Learning Techniques", Lawrence, K.D. and Pai, D.R. (Ed.) Applications of Management Science (Applications of Management Science, Vol. 20), Emerald Publishing Limited, pp. 59-69. https://doi.org/10.1108/S0276-897620200000020004Download as .RIS
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