Advancement and Approval of Loan Application Using XAI Technique
Alt Text: Advancement and Approval of Loan Application Using XAI Technique
Title: Advancement and Approval of Loan Application Using XAI Technique
Caption: Exploring machine learning techniques for efficient loan application approval.
Description: This paper discusses the challenges in loan approval processes and proposes an XAI-driven approach integrating ensemble machine learning models to improve accuracy and efficiency.
Keywords: Loan Approval, XAI, Machine Learning, Banking Sector, Predictive Analytics
International Journal of Engineering and Techniques – Volume 10 Issue 3, June 2024
M. Lokesh1, P. Nagendhar1, R. Ganga Nandan1, P. Mounika1, Dr. M. Ganesh2
1B.Tech IV Year, Department of IT, Malla Reddy Engineering College, Secunderabad, Telangana, India.
2Professor, Department of IT, Malla Reddy Engineering College, Secunderabad, Telangana, India.
Email: meetlavan78@gmail.com
Abstract
Significant advancements in technology have led to an expansion of people’s needs. In the banking industry, this has resulted in a rise in loan approval requests. Several factors must be considered when selecting a candidate for loan approval to assess the loan’s status. Banks face major challenges in evaluating applications and mitigating risks associated with borrower defaults. This paper proposes an ensemble machine learning approach using Random Forest, Naïve Bayes, Decision Tree, and KNN algorithms to improve loan approval accuracy, achieving an impressive 83.73% accuracy.
Keywords
Safe Customers, Bank Loans, Trained Dataset, Random Forests, KNN, Decision Tree, Naive Bayes
How to Cite
Lokesh, M., Nagendhar, P., Nandan, R.G., Mounika, P., Ganesh, M., “Advancement and Approval of Loan Application Using XAI Technique,” International Journal of Engineering and Techniques, Volume 10, Issue 3, June 2024. ISSN 2395-1303
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