Payment Processor: $240M Fraud Detection

The Challenge

A major payment processor was facing increasingly sophisticated fraud attempts that traditional rule-based systems couldn’t detect. False positive rates were high, causing customer friction while real fraud was slipping through.

Key challenges included:

• Sophisticated fraud patterns evading detection
• High false positive rates causing customer friction
• Manual review processes unable to scale
• Need for real-time detection at massive scale

Our Approach

Our advisor developed advanced AI-powered fraud detection:

Graph Neural Networks

• Built graph-based models to detect network patterns
• Identified relationships between transactions and entities
• Created systems to detect coordinated fraud rings

Real-Time Infrastructure

• Built low-latency scoring infrastructure
• Implemented streaming analytics for instant decisions
• Created scalable architecture for payment volume

Operational Integration

• Integrated with existing fraud operations
• Built investigator tools and case management
• Created feedback loops for model improvement

Results

The AI-powered fraud detection delivered exceptional results:

• $240M in fraud identified through advanced detection
• 68% reduction in false positives
• Industry benchmark for payment security
• Scalable system processing massive volume

Key Takeaways

This engagement showed how advanced AI techniques can transform fraud prevention. By combining data and AI expertise with risk management leadership, the processor achieved detection capabilities that became the industry standard.