International Journal of Advanced Engineering and Technology

International Journal of Advanced Engineering and Technology


International Journal of Advanced Engineering and Technology
International Journal of Advanced Engineering and Technology
Vol. 3, Issue 3 (2019)

Machine learning application to identify good credit customers


Carol Anne Hargreaves

In this paper, we focus on the application of machine learning algorithms to identify credit risk customers. The main objective is to firstly, identify the most important factors that may be associated with “good credit” customers, and to compare good credit customers with bad credit customers. The logistic regression model was used to score customers on their likelihood of being a “good credit” customer. The logistic regression model was highly accurate in predicting credit risk with a sensitivity and specificity of 74% and 75% respectively. Therefore, by following the classifications of the logistics regression model results, the bank was able to minimize losses of -$88 000 to a profit of $26 000.
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How to cite this article:
Carol Anne Hargreaves. Machine learning application to identify good credit customers. International Journal of Advanced Engineering and Technology, Volume 3, Issue 3, 2019, Pages 31-35
International Journal of Advanced Engineering and Technology International Journal of Advanced Engineering and Technology