Abstract: This project present an Loan Approval Prediction Using Machine Learning designed to automate and enhance the traditional loan eligibility evaluation process using machine learning and artificial intelligence. Conventional loan approval systems are time consuming, require physical branch visits, and lack transparency in decision-making. To overcome these limitations, the proposed system provides an intelligent, web-based solution that delivers instant loan eligibility predictions without requiring user login. The system evaluates loan applications using a hybrid decision approach, combining rulebased logic and machine learning models to ensure accurate, unbiased, and explainable decisions. Users input basic financial details such as income, loan amount, credit score, and existing liabilities, after which the system calculates EMI, debt-to-income ratio, and generates an approval or rejection result with clear explanations. In addition to loan eligibility prediction, the platform integrates an AI-powered chatbot that assists users with eligibility checks, EMI calculations, branch information, and support queries. A real-time branch locator using map services helps users identify nearby bank branches and obtain navigation directions, improving accessibility and user convenience. The application follows a privacy-first design, ensuring secure handling of data and eliminating unnecessary authentication requirements. The project demonstrates the practical application of machine learning, AI-based automation, and modern web technologies in the banking domain. It provides a scalable foundation for future enhancements such as integration with real banking APIs, document verification, multilingual support, and mobile application deployment, making it suitable for real-world digital banking environments.

Keywords: Loan Approval Prediction, Machine Learning, Artificial Intelligence, Digital Banking, EMI Calculation, Credit Risk Assessment, AI Chatbot, Financial Automation, Banking Assistant, Loan Eligibility System, User-Centric Design, Explainable AI.


Downloads: PDF | DOI: 10.17148/IJARCCE.2026.15120

How to Cite:

[1] UMME KULSUM, SWETHA T, M MAHIMA RANI , "LOAN APPROVAL PREDICTION USING MACHINE LEARNING," International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2026.15120

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