Analyze financial activity across risk dimensions to flag suspicious behavior, triggering alerts based on your custom rules, thresholds, and compliance strategy
A scoring framework that evaluates customer risk from onboarding through ongoing due diligence, combining static and dynamic behaviors
An AI model that scores multi-factor patterns to catch anomalies missed by rigid rules, reducing false positives and complementing existing defenses with understandable analysis
Use typology blueprints tuned to your data, providing personalized protection and high accuracy with deployment in just a few days
This supervised AI prioritizes high-quality alerts by filtering rule noise, reducing fatigue so Fraud/AML teams focus on significant cases over insignificant alerts
A centralized environment to build, refine, and oversee your AI model lifecycle, bridging data science and domain expertise in a single pane of glass
Boost existing monitoring systems by scoring and prioritizing alerts to reduce false positives and highlight real risks without changing the core platform