Abstract :

Loan Approval Is A Critical Process In The Banking And Financial Sector, Requiring Accurate Evaluation Of Applicant Eligibility To Reduce Financial Risk. Traditional Loan Approval Systems Rely Heavily On Manual Verification And Rule-based Decision Making, Which Can Be Time-consuming And Prone To Human Bias. This Project Proposes A Machine Learning– Based Loan Approval Prediction System That Analyzes Applicant Data Such As Income, Credit History, Loan Amount, And Employment Status To Predict Loan Approval Outcomes. By Training Models On Historical Loan Data, The System Improves Decision Accuracy, Ensures Faster Processing, And Enhances Fairness. The Proposed System Helps Financial Institutions Automate Loan Decisions While Minimizing Default Risks.it Is Very Useful In Real Time Applications.

Published:

31-7-2026

Issue:

Vol. 26 No. 7 (2026)

Page Nos:

1452 - 1459

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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