Case Study: Large Tier 1 Bank reduces false positives and uncovers new AML patterns with ThetaRay

Large Tier 1 Bank - Customer Case Study

Large Tier 1 Bank, a tier 1 APAC corporate banking institution, was struggling with an AML program built on rules-based monitoring that generated more than 75,000 alerts a year, over 95% of which were false positives. The bank also faced alert fatigue, high operational costs, and difficulty detecting previously unknown money laundering and terrorist financing activity. ThetaRay was brought in to help strengthen anti-money laundering detection and compliance.

ThetaRay used its Analytics Platform and unsupervised machine learning to analyze 45 million transactions and multiple customer data sources, clustering anomalies and surfacing suspicious patterns that the legacy system had missed. In just three weeks, ThetaRay helped identify new money laundering cases, reopen previously closed cases, and reduce 4,200 suspicious activities to 48 patterns for triage. The result was a 35% reduction in false positives, 100% of true positives caught, a 4X increase in detection accuracy, 30% lower operational costs, and identification of five new money laundering patterns.