Fraud Detection ML Dashboard

Real-time monitoring and management of fraud detection systems

Active Models

3

/ 3

Detection Rules

3

/ 3

Blocked Cases

0

/ 0

Avg Fraud Score

0.0%

ML Detection Models

3 Models
🚀

XGBoost - Primary Fraud Detector

Primary Model

XGBoost is our champion fraud detector—fast, accurate, and battle-tested. It handles complex patterns like a pro and rarely misses suspicious activity. This is the model we trust most for real-time decisions.

Trust Score95%

Precision

94.0%

Recall

91.0%

F1-Score

92.5%

Accuracy

96.0%

🌲

Random Forest - Reliable Benchmark

Secondary Benchmark

Random Forest is our steady, reliable backup. It's excellent at handling known fraud patterns and provides a sanity check against XGBoost. Think of it as your second opinion doctor.

Trust Score88%

Precision

89.0%

Recall

87.0%

F1-Score

88.0%

Accuracy

93.0%

🔍

Isolation Forest - Anomaly Hunter

Anomaly Detection

Isolation Forest is our wild card—it catches the weird stuff nobody's seen before. Unlike other models trained on fraud examples, this one simply knows what 'normal' looks like and flags anything bizarre.

Trust Score79%

Precision

82.0%

Recall

76.0%

F1-Score

79.0%

Accuracy

88.0%

Fraud Cases

No fraud cases found. This is good news! 🎉