Most fraud systems lose context after the transaction decision is made. Graph intelligence preserves the relationships behind every alert, turning detection, investigation, and compliance into a continuous intelligence loop.

Fraud does not happen in isolation. Accounts, devices, merchants, mule networks, and synthetic identities are all connected - yet most fraud systems treat each transaction like a standalone event.

In this webinar, discover how graph technology helps financial institutions connect the entire fraud life cycle:

• Real-time fraud detection in milliseconds
• Investigator-led case review and network analysis
• Explainable evidence for compliance and SAR workflows
• Continuous model improvement powered by confirmed fraud outcomes

You’ll learn why leading banks are moving beyond disconnected tooling and adopting a shared graph model that compounds intelligence at every stage.

What You’ll Learn

• Why connected data changes fraud detection accuracy
• How graph enrichment fits inside the 200ms transaction window
• The difference between traditional alerts and graph-enriched alerts
• How investigators uncover mule networks and synthetic identities faster
• Why explainability matters for SR 11-7 and model governance
• How feedback loops improve future fraud detection automatically
• Real production benchmarks from large-scale banking deployments

Proof at Scale

• +200% fraud detection improvement
• 10ms production query latency
• 250M nodes in production
• 2.2B relationships managed at scale

Join us for a practical walkthrough of how graph intelligence powers the complete fraud life cycle — from transaction scoring to investigator workflows and continuous model improvement. See how graph-powered fraud intelligence transforms every stage of the fraud life cycle.