Why AFC Professionals Say Trust Comes First

In financial crime management, there are times that call for going above and beyond. For many professionals I’ve spoken to, that moment is now: amid the pressure of facing financial crime threats at a scale and sophistication that outpaces what any team can manage alone. Criminal networks are more adaptive than ever, and every compliance leader I’ve met feels the weight of that reality. When the threat grows faster than your headcount, you must be bold enough to innovate, trust your partners and use AI where it makes the biggest impact.

Right now, the opportunity in front of the industry is agentic AI. In city after city on the Agentic AI Workforce Tour, customers shared their AI-adoption journey, not in theory, but in practice. Across every story, one thing was clear: innovation at this scale does not happen alone. It starts with a trusted partner, close collaboration and measuring what you achieve together. These insights come from the people closest to the work and at the forefront of change.

Why Trust Matters More than Ever

The anti-financial crime landscape is increasingly crowded with foundational AI solutions. Many technologies are positioned as the latest answer to long-standing compliance and fraud challenges, but few are built to operate within the highly regulated environment that financial institutions navigate every day. The right partner should prove they can deliver measurable results while giving institutions confidence in security, governance, auditability and the ability to operate within an existing risk framework.

Nasdaq Verafin is built for this, backed by more than two decades of experience. That foundation matters because AI adoption cannot be separated from the workflows, data permissions and regulatory expectations that surround an anti-financial crime program. We treat AI as an enterprise-wide responsibility, grounded in the same standards that guide innovation across Nasdaq. The true measure of progress is not simply how quickly AI can act, but whether a financial institution can trust, understand and govern actions over time.

That kind of trust does not come from a demo or a roadmap. It is built by working alongside hundreds of institutions and delivering results time after time. The customers who spoke on the Tour showed exactly what that looks like in practice.

FNBO: Trust as the Foundation

At our Omaha stop, Nick Baxter, Chief Risk Officer at FNBO, was direct about what adopting agentic AI meant for his bank: not a leap of faith, but the product of a relationship built over years and tested through shared work. As Baxter explained in FNBO’s published case study, onboarding agentic AI “wasn’t a major leap for us” because Nasdaq Verafin “is a true partner, and I don’t use that term lightly.”

David Dawson, BSA/AML Officer at FNBO, shared a similar perspective on the Tour, one captured in detail in the case study. He described the implementation as two teams building something together, refining the approach based on mutual feedback until they had both technical validation and a team ready to scale. That is what partnership looks like in practice: not a vendor delivering a product and walking away, but two teams staying in the work until both the technology and the people are ready.

The impact was clear: a 50% reduction in time spent on investigative work and up to 50% more investigator capacity redirected to analysis.

Origin Bank: Trust Validated by Proof

Origin Bank took a different path to the same conclusion. If FNBO’s story is about trust as a starting point, Origin Bank’s is about trust validated through measurement.

At the Tour, Jon Robinson, Senior Vice President, Compliance Risk Data and Analytics Director, was clear about where his team stood: they already had a process. The question was not whether they needed one; it was whether AI could execute that process more consistently, more efficiently, and at a scale that would free their team to focus on the work that requires human judgment. As he explained in Origin Bank’s case study, they let the data decide.

And the data was unambiguous. Origin Bank completed 412% more EDD reviews compared to the quarterly average of the previous five quarters, while maintaining the consistency, documentation quality and oversight their program demands. After reviewing 700 sanctions alerts, the Agentic Sanctions Analyst identified 100% of confirmed suspicious activity with zero valid investigative cases missed. These are not projections. They’re proven results. For compliance leaders still searching for a defensible business case for AI, Origin Bank made one, quantifiable in hard dollars.

The human impact was equally significant. Analysts who once spent their days assembling information from scratch are now starting with structured packages (customer information, risk indicators, summarized findings, generated narratives) and spending their time reviewing, validating and making judgment calls rather than gathering data. Promised efficiency is one thing. Delivered efficiency that’s measured and defendable, is something else entirely.

The Broader Consensus

FNBO and Origin Bank are two institutions, two paths, and one shared conclusion: trust and partnership are not optional in this transition. They are what made the difference between evaluating AI and deploying it with confidence.

Both customers were direct about what they would tell peers who have not started yet. As Robinson put it in the case study: “Get started with the Agentic AI Workforce, compare the results against your existing processes and see the outcomes for yourselves. The business case writes itself.”

And from Dawson in the FNBO case study: “To our like-sized peers, I’d say put yourselves out there and seize the opportunity to innovate with agentic AI. With a great partner like Nasdaq Verafin handling the complexity, you can focus on adoption, and the results will follow.”

They were not alone. At every Tour stop, customer after customer stood up and told the same story from their own perspective. Different institutions, different starting points, but the same conclusion: when you trust a partner who understands your world, you deploy faster, measure results sooner, and build a case your board can stand behind. The organizations that lead the next generation of AI will be those that pair innovation with accountability, oversight and proven controls.

The Tour continues. If you’re thinking about AI, I hope you’ll join us and hear these voices directly. Register for the Virtual Agentic AI Workforce Tour here, or reach out to the Nasdaq Verafin team to see the Agentic AI Workforce in action.

FAQs

What is the Agentic AI Workforce, and how is it different from traditional AI tools?

The Agentic AI Workforce is Nasdaq Verafin’s next generation of AI innovation — a set of Agentic AI Analysts designed to autonomously triage alerts, make determinations, and execute end-to-end workflows with full transparency and auditability. Unlike traditional AI tools that assist with isolated tasks, Agentic AI enables systems to make autonomous decisions while explaining the rationale behind each one, with human-in-the-loop oversight and clear audit trails that support regulatory compliance and internal governance.

How long does it take to deploy agentic AI for financial crime management?

Deployment is low friction. For institutions using Nasdaq Verafin, the Agentic AI Workforce is a natural extension of existing processes. There are no new systems or data sources to integrate, data, workflows and permissions remain unchanged, and existing controls stay in place and are continuously monitored. Due diligence and security reviews are also already established and ongoing. The result: a solution that’s ready to provide results as soon as you’re ready to enable it.

What results have customers achieved with the Agentic AI Workforce?

Origin Bank completed 412% more EDD reviews compared to the previous five-quarter average while maintaining documentation quality and oversight. After reviewing 700 sanctions alerts, the Agentic Sanctions Analyst identified 100% of confirmed suspicious activity with zero valid cases missed. FNBO reported a 50% reduction in time spent and up to 50% more investigator capacity redirected to higher-value analysis.

How does the Agentic AI Workforce support human investigators?

The Agentic AI Workforce automates repetitive research, information gathering and documentation tasks, allowing investigators to focus on pattern recognition, risk evaluation and complex decision-making. Human judgment remains at the center of decision-making; no alert is cleared and no case is escalated without human review.

About the Author

Scott Peddle
VP, AML Product Strategy

As Vice President, AML Product Strategy, Scott leads product strategy for the Agentic AI Workforce at Nasdaq Verafin. A Software Engineer by background, Scott has spent years across Nasdaq Verafin’s Software Development, Product Management and Project Management teams, giving him a deep understanding of the full customer experience. He is a passionate public speaker, problem solver, and customer evangelist. His dedication to Nasdaq Verafin’s customers is fueled by a belief that successful customer partnerships and a commitment to working together are key in staying ahead of fraudsters in the world of financial crime.