A Django-based Credit Approval System that intelligently determines loan eligibility and offers real-time insights based on past loan data and customer profiles using PostgreSQL.
MLOps Loan Approval Prediction System
Built and deployed a Flask-based machine learning system to predict loan default risk using customer demographics and financial indicators. Applied advanced ensemble models like XGBoost and LightGBM to achieve ~99% accuracy. Designed a full-stack solution with real-time prediction capabilities, enabling faster, smarter loan decisions in banking.
💳 Manage customer loans and credit approvals easily with this Django-based REST API, featuring automated calculations and loan eligibility checks.
Loan approval prediction means using credit history data of the loan applicants and algorithms to build an intelligent system that can determine loan approvals.
This project predicts whether a loan application will be approved by analyzing key financial and personal factors. It helps simulate realistic decision-making in lending and offers insights into responsible credit evaluation.
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