Case Study: Global Correspondent Bank achieves stronger AML and fraud discovery with SymphonyAI Sensa

Correspondent banking AML and fraud discovery

Global Correspondent Bank, a correspondent banking institution, needed stronger AML and fraud discovery to address rising financial crime risks, including money laundering and terrorist financing. The bank wanted to improve detection within its existing transaction monitoring environment while maintaining regulatory confidence and minimizing false alerts.

SymphonyAI implemented SymphonyAI Sensa to uncover hidden risks using behavioral analytics, anomaly detection, graph machine learning, temporal analysis, and expert-driven rules, while integrating with the bank’s current data and workflows. The result was a 120% increase in L3 discovery, a 500% increase in operational productivity, low false positive and false negative ratios of 5:1 versus a 35:1 market norm, and a successful 6-month SLA-based deployment with no differences from existing TMS data.