Financial crime doesn't sleep, and neither does our Risk Operations Center. We sat down with Priya Patel, our Chief Compliance Officer, and the Trust & Safety team to understand how they protect millions in transactions every day.
"We monitor over 12,000 risk events per minute," explains Priya. "Everything from login attempts to large transactions flows through our risk scoring engine. The key is identifying genuine threats without creating friction for legitimate users."
The team uses a combination of rule-based systems and machine learning models to detect suspicious patterns. Each transaction receives a risk score based on dozens of factors: transaction amount, velocity, geographic patterns, device fingerprinting, and behavioral analysis.
When a high-risk event is detected, it triggers one of our automated playbooks. These playbooks guide analysts through investigation steps, pull relevant data automatically, and suggest actions based on historical patterns.
The AI systems are trained on millions of historical transactions, learning to distinguish between normal business patterns and potential fraud. The models are continuously updated as new fraud patterns emerge.
"The human element is crucial," Priya emphasizes. "AI surfaces the suspicious activity, but experienced analysts make the final decisions. We're augmenting human judgment, not replacing it."
The team also works closely with law enforcement and other financial institutions to share threat intelligence. This collaborative approach helps the entire industry stay ahead of evolving threats.
Recent improvements include real-time biometric verification for high-risk transactions and behavioral analytics that detect account takeover attempts before any money moves.
