A neuro-symbolic fraud detection system uses a symbolic rule layer to detect concept drift before F1 scores drop, without requiring labels. The key insight: the MLP path compensates for gradual drift in feature-fraud relationships, but the symbolic rule layer cannot adapt, making it a sensitive early-warning signal. A FIDI
Table of contents
TL;DR: What You Will Get From This ArticleThe Story So FarThree Ways Fraud Can ChangeThe Problem With the First Three MetricsThe Metrics: Building a Label-Free Drift Detection SystemResults: What Each Metric DidThe Alert Demo: Window 3Why FIDI Z-Score Sees It Before F1 DoesWhat This System Cannot DoResults SummaryBuilding ItV14: Three Articles, One FeatureWhat to Do With ThisThree Things That Will Catch You Using This Concept Drift Early Warning SystemClosingSeriesDisclosureReferencesSort: