AML Watcher Information

Five years ago, we made a decision to fix something nobody wanted to admit was broken. 90% of AML alerts were false positives. Not an edge case, the industry ran at a 9:1 noise-to-signal ratio, where analysts spent their days filing financial crime instead of stopping it. The problem wasn’t the software. It was the data underneath it. Legacy tools ran on inherited gaps missing jurisdictions, missing entities, and missing context. So we built the data layer ourselves. Hundreds of researchers. A decade of sourcing. Every country, state, and territory. 66% of records carry enriched DOBs and nationalities, backed by the world’s largest face repository of AML risk individuals. Name matching trained on 80+ languages, not retrofitted for them. In head-to-head POC testing on name screening, AML Watcher consistently outperforms legacy systems in reducing false positives and false negatives. Entity screening across 3,500+ watchlists, 215+ sanction regimes, 50,000+ adverse media sources, and PEP due diligence from 100,000+ data sources plus transaction monitoring calibrated to regional behavioral patterns, screening billions of transactions through 150+ pre-built AML typologies and 10,000+ customizable rules built for regulator-mandated scenarios. Then came TruRisk. Our AI compliance agent reasons through matches not just flags them with auditable justification for every confirmed hit. Clean data without intelligent decisioning produces backlogs. Agentic AI without trustworthy data just automates the wrong answers faster. The two have to work together. 95% fewer false positives. 70–80% less manual review. Review time cut from hours to minutes. AML Watcher: Proven to outperform all FinCrime compliance challenges.