The Central Bank of Nigeria (CBN) has introduced a mandatory standard requiring banks and fintechs to implement automated anti-money laundering (AML) systems. In a fast-moving payments ecosystem where millions of transactions are processed in milliseconds, the regulator’s directive goes beyond simple compliance, indicating that manual processes are no longer sufficient to manage complex financial crime.
Brad Levy, CEO of fintech software and data analytics firm, ThetaRay, in an interview with Business A.M’s Onome Amuge, dwells on how this development is set to transform both operational priorities and strategic risk management and its impact on the country’s overall financial crime prevention landscape. Excerpts:
How significant is the Central Bank of Nigeria’s new baseline standard mandating automated AML systems for financial institutions?
It’s a watershed moment. We are seeing a global shift where technological capability and legal obligations are becoming inseparable. By mandating automation, the CBN is effectively saying that manual processes are no longer a defensible way to manage risk in a high-speed, digital economy. This isn’t just a new rule; it’s a commitment to financial integrity that will make the Nigerian market more attractive to global partners.
Why do you think the CBN chose this moment to formalise automation in AML compliance?
Because the industry has moved past the era where “real-time” was a luxury; in 2026, it is a regulatory and consumer mandate. Nigeria’s new National Payment Stack (NPS) has already demonstrated the ability to process live transactions between banks and fintechs in just a few milliseconds. When funds settle that fast, the window for manual intervention vanishes. You cannot defend a millisecond-speed payment rail with a day-long manual compliance check. The CBN is formalising automation now because they know that for Nigeria to maintain its status as a maturing instant payment system — the first in Africa to reach that level — its security must move at the same velocity as its money.
How do you see this regulatory development affecting Nigeria’s overall financial crime prevention ecosystem?
It moves the ecosystem from “check-the-box” compliance to “effectiveness-driven” outcomes. In the past, you were compliant if you followed the steps. In this new era, you are compliant if you actually find the crime. This will force a massive upgrade in data quality and technical literacy across the board, ultimately making Nigeria a leader in African financial security.
From an operational perspective, what will Nigerian banks and fintechs need to do to comply with these new standards?
The clock is officially ticking. If you aren’t already automating, you’re late. The CBN’s June 10, 2026 deadline for an implementation roadmap is less than three months away. For many FIs [financial institutions], the “waiting game” ended the moment the National Payment Stack began processing transactions in milliseconds.
Operationally, this means three things:
Gap analysis now: Immediately auditing current manual processes against the CBN’s 12 baseline standards to see where they fall short.
The 18 to 24-month sprint to unify data: Moving away from fragmented systems. The CBN now mandates that KYC/KYB data must be integrated directly into transaction monitoring to provide a “unified customer view”.
Layer, Don’t Rebuild: The biggest mistake “late” FIs make is attempting a multi-year “rip and replace” of their core systems. The smart move is to layer “plug-and-play” AI overlays on top of their existing systems to meet the deadline without operational downtime.
And I’ll add one more thing.
Submit the roadmap early: The June 10 deadline is a transparency test. FIs that show a sophisticated, AI-first plan early will signal to the regulator, and global correspondent banks, that they are serious about staying off the Grey List.
How does AI-powered transaction monitoring, like the solutions ThetaRay provides, detect complex financial crime patterns in ways traditional systems
cannot?
Traditional systems are built on “if-then” logic—they only find what you tell them to look for. Our Cognitive AI is different; it looks for subtle anomalies in behaviour. It identifies the “hidden signatures” of crime that don’t fit a baseline pattern. It’s the difference between a security guard at a door and a satellite view of the entire city. One sees the person; the other sees the network.
What are the main challenges institutions might face when implementing AI-driven AML systems, and how can they be addressed?
The biggest challenge is “trust in the black box.” Regulators and boards need to know why an AI made a decision. We address this through explainability — turning complex math into a clear alert with more than 30 risk factors and a case narrative that an investigator can actually use. The second challenge is data silos. You can’t fight networked crime with siloed data. Banks must integrate their risk views across all risk data, from customer screening to risk scoring and transaction monitoring, across payment corridors.
How has automation in AML moved from being a competitive advantage to a regulatory requirement?
Volume. You simply cannot hire enough humans to monitor millions of transactions per second manually. In the past, better tech gave you an edge. Today, without it, you are effectively blind. When the regulator says you must be able to see, the tool you use to see becomes a requirement, not a choice.
In your experience working with Nigerian organisations, what measurable improvements have you seen once AI-based AML solutions are deployed?
We see two things immediately: from 70 to 89 percent reduction in “noise” (false positives) and a massive increase in the speed of investigations, in some cases from months to minutes. When you stop wasting time on 9 out of 10 alerts that mean nothing, your team can focus on the one alert that actually matters. That’s how you go from being a cost center to a strategic asset for the bank or the growing fintech, while ensuring that payments that may well be a lifeline to millions of people, move as fast as they should.
How do you expect Nigeria’s AML automation mandate to influence compliance standards across other African markets?
Nigeria is a critical benchmark for the continent’s financial evolution. While the headlines often debate GDP rankings between South Africa, Egypt, and Nigeria, the real story is in the velocity of transaction volumes and the sophistication of the fintech ecosystem. When a market with this much scale and digital complexity mandates AI-driven AML, the rest of the continent — from Kenya to Egypt — takes note. We expect a ‘domino effect’ where these automated standards become the foundational infrastructure for the African Continental Free Trade Area (AfCFTA), ensuring that cross-border trade isn’t just fast, but fundamentally secure.”
What role do you see AI playing in shaping the future of financial crime prevention globally, especially in emerging markets like Nigeria?
AI is becoming the foundational infrastructure of trust, but its impact in emerging markets is unique because it enables a massive technological leapfrog. Much like how Africa skipped landlines for mobile and moved to encrypted chips while the U.S. lagged with magnetic strips, Nigeria is now bypassing the “landline era” of compliance. While Western institutions struggle to patch rigid, 1990s-era legacy systems, the CBN’s mandate allows Nigerian firms to move straight to a “mobile-first,” AI-driven model.
In this sense, AI is the great equaliser. It allows Nigeria to build a financial system that is inherently more secure and transparent than many older, established markets. Beyond catching up, Nigeria is building a 21st-century financial laboratory that is most importantly, open for safe, high-velocity global trade.
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