Credit Card Transactions Fraud Detection using Deep Learning.

This is our Sem 8 ADS (Applied Data Science) Case Study Project

End-to-end fraud detection simulation using Python — featuring Phase 1 (SQLite + Rule-Based Detection) and Phase 2 (Microsoft SQL Server + Advanced Feature Engineering). Built with synthetic banking data using Faker, and enriched with velocity, behavioral, and dormancy features to mimic real-world financial fraud scenarios.

Graph-based analytics and HGT models to identify suspicious transaction networks (fraufulent transaction in fintech and digital wallets)

Credit Card Fraud Detection is a state-of-the-art real-time streaming analytics solution designed to detect fraudulent credit card transactions instantly.

Creditcard Fraud Detection Streamlit Application with ARIMA and LOF

Detect fraudulent transactions and accounts in a vast dataset