AI-Based Fraud Detection & Financial Risk Analysis System

This project builds a production-grade fraud detection system using ensemble machine learning methods to identify suspicious financial transactions with high accuracy and low false-positive rates. The system processes transaction data in real-time, applies trained ML models to compute fraud probability scores, and provides explainable AI (XAI) insights to help analysts understand why a transaction was flagged. **Industry Relevance:** Fraud detection is a core use case in fintech and banking. This project demonstrates data science, ML engineering, and explainability skills valued by companies like PayTM, Razorpay, and major banks.