SecureCard-AI
Credit Card Fraud Detection System
A high-performance machine learning system achieving 99.97% accuracy in credit card fraud detection
Personal Project
Project Overview
SecureCard-AI is a machine learning project that implements a high-performance credit card fraud detection system. Using advanced techniques and real transaction data, the model achieves an exceptional accuracy rate of 99.97%, making it a reliable tool for identifying fraudulent transactions.
Project Goals
- Develop a highly accurate fraud detection system
- Achieve optimal balance between precision and recall
- Create an interpretable and maintainable solution
- Provide comprehensive documentation and analysis
Technical Details
Python
Scikit-learn
Pandas
NumPy
Matplotlib
Dataset Information
Dataset Overview
- Source: Kaggle Credit Card Fraud Detection Dataset 2023
- Size: 57,000+ transactions
- Balance: 50% fraud, 50% non-fraud
- Features: Transaction amount, time, and anonymized features (V1-V28)
Model Performance
Accuracy Metrics
- 99.97% Overall Accuracy
- Only 18-19 errors per 57,000 transactions
- Cross-validation scores: [0.9996 - 0.9997]
Complete Implementation Details
Below is the complete implementation of the credit card fraud detection system, including data processing, model architecture, training, and evaluation.