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Realizing AI’s true potential in financial services

06.27.2025

A discussion on how financial institutions are using AI to transform anti-money laundering (AML) and fraud detection efforts 

Raj Shukla, CTO, SymphonyAI sat down with R “Ray” Wang, Chairman, Founder and Principal Analyst at Constellation Research to talk about how financial institutions are using predictive and generative AI in their payment fraud and AML software 

Featuring real-world results, the discussion outlines how leading banks are reducing false positives, uncovering missed threats, and accelerating regulatory reporting, all while boosting compliance confidence and operational resilience. 

Topics covered 

End-to-end financial crime detection with AI: 

  • Overview of predictive and generative AI applications in AML products. 
  • How AI enhances data contextualization, orchestration, and governance. 
  • Unified platforms enabling streamlined risk response. 

Absa bank case study: 

  • How South African bank Absa replaced legacy rules-based AML systems with predictive AI. 
  • Achieved >70% reduction in false positives. 
  • Detected 10% additional fraud cases missed by traditional systems. 

Operational gains through generative AI: 

  • Accelerated investigative workflows for compliance teams. 
  • Reduced investigation time by 40–50%. 
  • Improved accuracy and efficiency across end-to-end case lifecycle. 

Transforming risk and compliance strategies: 

  • How AI delivers measurable resilience and accuracy. 
  • Examples of full-cycle fraud detection from alert to regulator-ready reporting. 
  • Aligning modern tech stacks with audit readiness and defensibility.

Related resources: 

  • SymphonyAI: Advanced platform for financial crime prevention that uses predictive AI, generative AI, and agentic AI. 
  • Absa case study: A partnership demonstrating AI-driven AML transformation and measurable risk reduction. Winner of an ICA Compliance Award. 

Want to find out more about AI in the AML process? Download our guide to AI in action. 

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