AI Governance in Financial Services with Dave Trier

In this episode of the Converge podcast, Dave Trier, Vice President of Product at ModelOp, joined the conversation to unpack the critical role of AI governance in financial services. With over two decades of experience in emerging technologies and more than ten years in model and AI governance, Dave offers a candid, practical perspective on how enterprises can innovate with AI while managing risk and meeting regulatory demands.

Defining AI Governance as an Enabler

Dave challenges the perception that governance slows innovation, framing it instead as an enabler. Effective AI governance provides a clear blueprint for how AI can be used responsibly across the enterprise—removing ambiguity, streamlining reviews, and ensuring the right people and processes are engaged at the right time.

Why It’s Mission-Critical in Financial Services

In regulated industries, AI is essential for competitiveness—but also inherently risky due to its probabilistic nature. Governance mitigates:

• Financial risk from faulty outcomes
• Regulatory risk from non-compliance
• Brand and reputational risk from public failures
  

Common Barriers to AI at Scale

Drawing from ModelOp’s AI Governance Benchmark Report, Dave identifies why many AI initiatives stall:

• Manual, ad-hoc processes (emails, spreadsheets) without enforceable governance frameworks
• Complex technology stacks and fragmented systems
• Late-stage compliance surprises that can delay production by months
  

The result? While 80% of enterprises have dozens of generative AI use cases in the pipeline, few make it to production—especially in highly regulated sectors.

Minimum Viable Governance (MVG)

Dave introduces MVG—a “Goldilocks” approach to governance that’s just enough to enable innovation without over-burdening teams. Key steps include:

1. Visibility into all AI systems and their risk levels
2. Automation of reviews, documentation, and controls
3. Continuous assurance to monitor performance, stability, and compliance
   

This approach replaces manual methods with scalable, automated processes—opening the door to faster, safer innovation.

From Roadblocks to Results

Dave draws on real-world financial services examples—from projects stalled by overlooked data risks to global banks racing to comply with the EU AI Act—to show how governance and innovation can work together. By replacing slow, manual processes with automated, auditable workflows, enterprises can scale AI faster, meet global regulatory demands, and reduce operational and reputational risk. Looking ahead, Dave spotlights Agentic AI as the next major frontier, with a parallel focus on cost optimization to ensure advanced AI capabilities deliver real business value.

Key Takeaways for Leaders

• View governance as an enabler, not a blocker
• Start small with minimum viable governance, then iterate
• Replace manual processes with automation for scalability
• Maintain continuous oversight to adapt to evolving risks

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