Abstract
The demand for scalable, secure, and intelligent loan processing systems has grown as a result of the financial technology industry's fast expansion. This study introduces SmartLoanAI, an AI-powered framework intended to automate risk assessment and loan eligibility determination in an online banking setting. In order to examine applicant characteristics including income, credit score, work type, age, and loan amount, the suggested system incorporates supervised machine learning techniques like Random Forest, Decision Trees, and Logistic Regression. To guarantee robustness and generalization, the model construction process includes data pre-treatment, feature selection, cross-validation, and performance tuning. In comparison to traditional rule-based systems, experimental study shows increased classification accuracy and decreased erroneous approval rates. To guarantee data security and scalability, the system architecture uses a modular multi-tier design with RESTful APIs, secure JWT-based authentication, and role-based access control. Effective administration of structured and document-based records is made possible by hybrid database support utilizing MySQL and MongoDB. The suggested approach greatly lowers manual involvement, improves decision transparency, and offers a solid basis for the future integration of cutting-edge fintech services like real-time credit verification and fraud analytics.
Keywords
Artificial Intelligence; Loan Eligibility Prediction; Machine Learning; Fintech Automation; Secure Banking Systems
Citations
IRE Journals:
Rajani Kodagali, Narne Rishith, Neppala Hema Sai, Neha Salla, Nithin Kumar P. "SmartLoanAI: An Intelligent Framework for Automated Loan Decision Systems" Iconic Research And Engineering Journals Volume 9 Issue 9 2026 Page 3153-3159 https://doi.org/10.64388/IREV9I9-1715799
IEEE:
Rajani Kodagali, Narne Rishith, Neppala Hema Sai, Neha Salla, Nithin Kumar P.
"SmartLoanAI: An Intelligent Framework for Automated Loan Decision Systems" Iconic Research And Engineering Journals, 9(9) https://doi.org/10.64388/IREV9I9-1715799
About IRE Journals
IRE Journals is an open access online journals established with an aim to publish high quality of research work in various diciplines. We have more than 6 years in publications. Over 2500+ papers already published.
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