Credit-Card-Fraud-Detection-Transaction-Analysis

📊 End-to-end credit card transaction analysis with fraud detection, time series insights, and ETL using Pandas & NumPy. Real-world scenario simulation for data analysts.

💳 Credit Card Fraud Detection & Transaction Analysis

This project simulates a credit card transaction dataset and performs comprehensive analysis including fraud detection, time-series aggregation, and financial calculations using Pandas and NumPy.

📊 Features & Operations

✅ Cleaning & Preprocessing

• Remove failed transactions
• Feature engineering: date, hour, GST, USD conversion, normalization

🔍 Transaction Analysis

• Total spend per customer
• Average amount per merchant
• Highest transaction finder
• Count of high-value transactions (> ₹10,000)

🕒 Time-based Trends

• Daily spending
• Hourly patterns
• Customer-level average spend

🚨 Fraud Detection

• Total frauds and ₹ lost
• Fraud by merchant & customer
• Fraud rate calculation
• Output export to CSV

📁 Project Structure

.
├── fraud_detection_analysis.py
├── output/

📦 Libraries Used

• Python 3.x
• Pandas
• NumPy
• Matplotlib (for optional visualizations)

📚 Learning Outcomes

• End-to-end ETL and financial transaction processing
• Time series resampling and analysis
• Risk scoring and fraud detection
• Feature engineering using real-world logic