Fraud Detection at Scale: A 99% Accuracy Case Study
Real-time Financial Surveillance with Graph-Based AI
Company Profile
A leading global fintech with millions of daily transactions.
Industry
Finance & Banking
Region
Global
About the Client
Detection Accuracy
Inference Latency
Annual Losses Prevented
Challenge
Fraudsters have moved beyond simple stolen cards; they now use complex networks of synthetic identities and circular transactions. The client's existing systems lacked the "social" context of transactions.
The challenge was to analyze trillion-scale relationship graphs in real-time.
The outdated surveillance infrastructure resulted in critical vulnerabilities:
- High false-positive rates causing customer friction.
- Inability to detect networked or circular fraud patterns.
- Legacy systems unable to handle sub-15ms latency requirements.
- Massive operational costs for manual fraud investigation.
The organization needed a paradigm shift from transactional analysis to relational intelligence.
The Solution
Real-time Graph-AI Surveillance
The Outcome
Global Security & Compliance
Reduction in False Positives
Fraud Prevented Annually
Operational Cost Savings
"WebbyButter has set a new standard for security in our organization. We finally have a system that is as smart as the threats we face."
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