The Challenge
Traditional fraud detection systems struggle with sophisticated fraud rings that exploit complex relationships between accounts, devices, and transactions. Legacy databases can't efficiently query multi-hop connections in real-time, leading to delayed fraud detection and significant financial losses.
Modern fraud schemes involve intricate networks of seemingly unrelated entities working together, requiring analysis of:
- Device fingerprinting and shared device networks
- Payment method associations across multiple accounts
- Behavioral patterns and anomaly detection
- Social network analysis for collusion detection
- Transaction velocity and pattern matching
Key Benefits
- Real-time Detection: Identify fraud as it happens with graph traversal queries that execute in milliseconds
- Complex Pattern Matching: Detect sophisticated fraud rings spanning multiple hops in the relationship graph
- Reduced False Positives: Contextual analysis through connected data reduces incorrect fraud flags by up to 70%
- Scalable Analysis: Process billions of transactions without performance degradation