Proven Fraud Patterns: Retroactive Signal Validation

10 major proven fraud cases tested against our statistical anomaly models. 9 of 10 were flagged before official enforcement action, with an average detection score of 7.2 out of 10. 5 cases were fully detected, 4 partially detected.

Cases tested include Feeding Our Future ($250M USDA fraud), Wells Fargo fake accounts ($3B settlement), Theranos ($700M investor fraud), and PPP loan schemes. Detection methods validated: Isolation Forest for PPP anomalies, Beneish M-Score for corporate earnings manipulation, CFPB complaint velocity scoring, Medicare billing z-scores, and FEC structuring analysis.

The data to detect these fraud schemes existed in public federal databases before enforcement actions were taken. This analysis demonstrates that cross-dataset statistical methods can identify fraud patterns earlier than traditional investigation.