Solution
Targeted Typology Analytics
Targeted Typology Analytics
Powered by artificial intelligence and consortium insights, Targeted Typology Analytics improve money laundering detection of targeted predicate crimes with low false positive rates, single-digit alert-to-case ratios, and low alert to SAR ratios.
Detecting predicate crimes for money laundering is highly challenging, and often requires significant time and resources.
Remaining compliant is complex and costly. AML/CFT investigators are faced with overwhelming false positives from convention transaction monitoring systems. As well, evolving regulations for preventing predicate crimes places an increased focus on the need for an effective solution.
Nasdaq Verafin’s Targeted Typology Analytics analyze a range of behavioral, transactional, third-party, and consortium insights for more effective detection of specific predicate crimes with fewer false positives and low alert to SAR/STR ratios. Powered by artificial intelligence (AI) and continuously improved through feedback from financial intelligence units, law enforcement, and investigators, our library of Targeted Typology Analytics deliver context-rich insights to help pinpoint potential money laundering activity efficiently and effectively.