Case Study: Leading Global Bank boosts risk detection and cuts false positives with SymphonyAI SensaAML

Leveraging this Tier-1 bank's existing data, Sensa increased risk detection and decreased false positives dramatically

Leading Global Bank, a Tier-1 retail and corporate bank, needed help overcoming the limitations of its rules-based transaction monitoring system, which was missing significant financial crime risk and creating pressure to meet regulatory SLA requirements for investigatory burndown. The bank turned to SymphonyAI and its SensaAML platform to improve detection of suspicious activity and reduce the false positive burden.

Using anonymized historical data that mirrored the bank’s existing system inputs, SymphonyAI deployed SensaAML in just hours and developed the model in six weeks. The solution identified 263% more Suspicious Activity Reports than the existing system, achieved an 81x improvement in risk-to-alert ratio, and reduced false positives by 77% while still capturing 100% of high-risk alerts with regulatory-grade explainability.