Case Study: Absa reduces false positives and boosts risk detection with SymphonyAI

Absa finds an ally in AI, reducing false positives by 77%

Absa, one of Africa’s largest banks, partnered with SymphonyAI to strengthen anti-financial crime compliance as regulations grew more complex and criminals increasingly used AI to probe bank processes. To test a modern, forward-looking approach, Absa looked at applying SymphonyAI’s Sensa Risk Intelligence to its transaction monitoring environment to improve alert quality, risk detection, and productivity.

SymphonyAI ran proof-of-concepts on masked data and built new AI models and features to enhance risk detection and alert handling while preserving detection of suspicious activity. The results were strong: SymphonyAI cut false positives by 77%, identified 21 new risks, and achieved a 10.5% hit rate for new risk detection, while also retaining all suspicious activity found by the existing rules-based system.

Absa

Nic Swingler

Head of Financial Crime