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🏦 Credit Scoring and Fraud Detection with Machine Learning

A live 3D risk-scoring landscape where simulated transactions are scored, routed to approve / review / decline gates, and explained with SHAP-style feature contributions.

AI & Machine Learning3DAdvanced60 FPS

A 3D risk-scoring landscape where the model's learned fraud probability is rendered as terrain height and colour, and live transaction spheres are scored and routed to approve, manual-review, or decline gates in real time.

🔬 What It Demonstrates

The teal-to-red surface is the model's decision function over transaction amount and spending velocity. A translucent threshold plane and a manual-review band show exactly how a probability score becomes a real business decision.

🎮 How to Use

Adjust the decision threshold, fraud attack intensity, feature weight and review band, then watch approvals, reviews and declines update live. Flagged transactions populate a SHAP-style explanation panel showing which features drove the score.

💡 Did You Know?

Most production fraud models score in under 100ms and pair a gradient-boosted classifier with a SHAP explainer so analysts and regulators can see exactly why a specific transaction was declined.

⚙ Under the hood

A live 3D risk-scoring landscape where simulated transactions are scored, routed to approve / review / decline gates, and explained with SHAP-style feature contributions.

machine learningfraud detectionrisk scoringcredit analysisdata scienceartificial intelligenceThree.js

3D · Three.js / WebGL renderer · 60 FPS target · runs fully client-side, no install