Loan Approval Prediction Using Machine Learning

K, PRADEEPA; M, PARKAVI; K, HARINI; K, KEERTHIKA

doi:https://doi.org/10.55041/ijcope.v2i4.996

Volume 02, Issue 05

Published on: May 2026

LOAN APPROVAL PREDICTION USING MACHINE LEARNING

PRADEEPA K PARKAVI M HARINI K KEERTHIKA K

Department of Computer Science and Engineering E.G.S.Pillay Engineering College Nagapattinam Tamilnadu India

DOI:https://doi.org/10.55041/ijcope.v2i4.996

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Abstract

The process of loan approval in banks is a critical task that involves evaluating multiple factors such as income, credit history, employment status, and financial background. Traditional methods are manual, time-consuming, and prone to human bias. This paper proposes a Machine Learning-based loan approval prediction system that automates the decision-making process. The system analyzes applicant data and predicts whether a loan should be approved or rejected. Various Machine Learning algorithms such as Logistic Regression, Decision Tree, and Random Forest are used for classification. The proposed system improves accuracy, reduces processing time, and enhances decision-making efficiency in financial institutions.

Keywords — Machine Learning, Loan Prediction, Classification, Banking System, Data Analysis

How to Cite this Paper

K, P., M, P., K, H. & K, K. (2026). Loan Approval Prediction Using Machine Learning. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(05). https://doi.org/10.55041/ijcope.v2i4.996

K, PRADEEPA, et al.. "Loan Approval Prediction Using Machine Learning." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 05, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i4.996.

K, PRADEEPA,PARKAVI M,HARINI K, and KEERTHIKA K. "Loan Approval Prediction Using Machine Learning." International Journal of Creative and Open Research in Engineering and Management 02, no. 05 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i4.996.

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References

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[5] N. R. and V. B. R., “Predictive Analytics and Feature Importance in Loan Approval and Risk Assessment,” SAGE Journals, 2025.

[6] F. G. Adewumi et al., “Loan Approval Prediction using Machine Learning Techniques,” Computer Science & IT Research Journal, vol. 6, no. 7, 2025.

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•All submissions are screened under plagiarism detection.
•Review follows editorial policy.
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•Peer Review Type: Double-Blind Peer Review
•Published on: May 02 2026

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