Proceedings of the 2022 Seventh International Conference on Research in Intelligent and Computing in Engineering

DOI: http://dx.doi.org/10.15439/2022R43

Citation: Proceedings of the 2022 Seventh International Conference on Research in Intelligent and Computing in Engineering, Vu Dinh Khoa, Shivani Agarwal, Gloria Jeanette Rincon Aponte, Nguyen Thi Hong Nga, Vijender Kumar Solanki, Ewa Ziemba (eds). ACSIS, Vol. 33, pages 295–298 (2022)

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Abstract. Nowadays, a bank loan can provide people with cash to fund home improvements or start a business. However, some customers who are accepted with a loan cannot repay or someone usually repays in a delayed time. Therefore, to minimize losses, examining loan applications is particularly evident for the bank. This paper study on bank loan analysis using data mining techniques. We use association rules mining, clustering, and classification techniques on the applicant's profile to help the bank quickly decide for a loan applicant.

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