Customer Loan Approval Classification by Supervised Learning Model
K. Gana Sai Prasad1, P. Vamsi Sai Chidvilas2, V. Vijay Kumar3
1K. Gana Sai Prasadstudent at the department of Computer Science and Engineering at K L Educational foundation, deemed to be University, Vaddeswaram, and Andhra Pradesh.
2P. Vamsi Sai Chidvilas student at the department of Computer Science and Engineering at K L Educational foundation, deemed to be University, Vaddeswaram, and Andhra Pradesh.
3Vijay Kumar Vasanthamisan assistant professor at the department ofComputer Science and Engineering at K L Educational foundation, deemedto be University, Vaddeswaram, and Andhra Pradesh.
Manuscript received on November 19, 2019. | Revised Manuscript received on November 29 2019. | Manuscript published on 30 November, 2019. | PP: 9898-9901 | Volume-8 Issue-4, November 2019. | Retrieval Number: D9275118419/2019©BEIESP | DOI: 10.35940/ijrte.D9275.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The loan is one of the most important schemes of bank. Usually the Banks are willing to give loans to the customers based on their requirements. However, unfortunately there are some customers who delay the payment of loan or unable to pay the loans due to financial status. In order to solve this problem, banks need to use thehelp of some techniques in predicting the loan repayment status. Machine Learning models are known to have a high accuracy on prediction problems, so in this paper we use some of the machine learning models in default loan prediction.
Keywords: Banking, Loan, Prediction, Classification.
Scope of the Article: Classification.