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Transaction Fraud Detection

38% less fraud, 72% fewer false positives

Client Context

A European payment processor handling 2M+ daily transactions across debit, credit, and digital wallet channels.

The Challenge

Rule-based fraud systems generated excessive false positives (blocking legitimate transactions) while missing sophisticated fraud patterns. Organised fraud rings adapted to rules within weeks of deployment. Customer complaints about blocked legitimate transactions were damaging retention.

Our Approach

We deployed graph neural networks that detect fraud ring patterns invisible to traditional rule-based systems, combined with real-time transaction scoring that evaluates 200+ features per transaction in under 50ms. The system adapts to new fraud patterns continuously.

Timeline: 20 weeks

The Results

  • Fraud losses reduced 38%
  • False positives reduced 72%
  • Fraud ring patterns detected that were invisible to previous systems
  • Legitimate transaction approval rate improved 12%

Facing a similar challenge?

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