Raunak Ghawghawe
Data Scientist
Real-Time Credit Card Fraud Detection
Advanced ML system using ensemble methods and explainable AI.
⚠️ Educational Simulation
Uses completely synthetic data and simulated ML processes. No real customer information is used.
Advanced ML Models
Ensemble of Logistic Regression + Random Forest
Real-Time Processing
Sub-second fraud detection with explainable AI
Business Impact
Reduces fraud losses while protecting members
Live Fraud Detection Simulator
Start the simulation to generate transactions in real-time. Click any transaction to view detailed ML analysis.
50%Fraud Detection Threshold (Higher = fewer false alarms, may miss some fraud)
0
Total
0
Actual Fraud
0
Detected
0
False Positives
0.0%
Accuracy
Live Transaction Stream
Real-time fraud detection results
Start the simulation to see live transactions
Analysis
Click a transaction to analyze
Select a transaction to analyze
How This ML System Works
Feature Engineering
- • Amount Z-Score normalization
- • Merchant risk scoring
- • Geographic risk assessment
- • Time-based patterns
- • Feature interactions
ML Architecture
- • Logistic Regression model
- • Random Forest ensemble
- • 60% logistic + 40% RF
- • Configurable thresholds
- • Real-time scoring
Business Value
- • $10M+ potential savings
- • Improved member experience
- • Regulatory compliance
- • Reduced false positives
- • Scalable architecture