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How Altery uses explainable AI to investigate complex ownership structures

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From Banking to AI: Tim Khamzin on Transforming Compliance

Vivox AI Founder & CEO Tim Khamzin recently joined Tom Fox on the Innovation in Compliance podcast to discuss the future of AI in financial crime operations, the importance of explainability in compliance technology, and how AI agents are reshaping AML and KYB workflows across financial institutions.

In a recent episode of the Innovation in Compliance podcast hosted by Tom Fox, Tim Khamzin shared his perspective on the next generation of AI infrastructure for compliance teams and the operational challenges financial institutions continue to face today.

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Drawing from his background in banking automation and large-scale digital transformation, Tim discussed how recent advances in large language models are making it possible to automate complex, unstructured compliance workflows without the need for extensive model training or rigid rule-based systems.

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The conversation explored some of the core pain points across AML, KYC and financial crime operations today, including:

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  • heavy manual investigative workloads
  • fragmented systems and repetitive analyst tasks
  • operational backlogs
  • false positive fatigue
  • resistance to technology adoption within compliance functions

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A major focus of the discussion was the importance of explainability and trust in AI systems deployed in regulated environments.

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Tim explained how Vivox AI approaches explainability through transparent workflows, repeatable investigations, audit logs and evidence trails designed to mirror how human analysts operate. He also highlighted the importance of maintaining human oversight and ensuring institutions clearly understand both the capabilities and limitations of AI systems.

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The episode also introduced Vivox AI’s compliance analyst agent, “Rachel”, a collaborative AI system designed to support onboarding, customer due diligence and financial crime investigations through human-in-the-loop feedback and continuous operational learning.

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The discussion further explored evolving regulatory expectations around AI governance, including the EU AI Act, FCA engagement and emerging guidance from jurisdictions such as Singapore, with a particular focus on auditability, transparency and defensible AI deployment practices.

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Looking ahead, Tim shared his view that AI agents will increasingly become embedded across compliance operations, while human analysts evolve into higher-value oversight and investigative roles, including the emergence of “compliance engineers” responsible for configuring, supervising and evaluating AI-driven workflows.

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Listen to Tim Khamzin on Innovation in Compliance: Apple podcasts
Watch the full conversation here

Conclusion

As financial institutions continue to navigate increasing regulatory complexity and operational pressure, the conversation highlights a broader industry shift toward explainable, auditable and human-supervised AI systems.

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