Editing Ai Finance (section)

== <span style="color: #FFFFFF;">Creating</span> ==
Designing a financial fraud detection system:
# Feature engineering: velocity features (transactions in last 1/6/24 hours), merchant category patterns, geographic anomalies, device fingerprints.
# Model: LightGBM for speed and interpretability; GNN on transaction graph for network-based fraud.
# Score threshold calibration: separate thresholds for block (high score), review (medium), allow (low).
# Real-time serving: sub-50ms scoring via ONNX/LightGBM serving.
# Feedback loop: confirmed fraud labels → retrain weekly.
# Champion/challenger framework: new model gets 10% traffic, promotes if performance ≥ champion after statistical significance reached.

[[Category:Artificial Intelligence]]
[[Category:Machine Learning]]
[[Category:Finance]]
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