In most boardrooms, “risk and compliance” are still viewed through the narrow lens of being an expense; a cost of doing business, a regulatory burden, a drag on innovation. But that mindset is outdated and increasingly dangerous. In today’s hyperconnected financial ecosystem, institutions that treat compliance merely as a defensive play are missing the opportunity to turn it into a strategic growth engine.
Artificial intelligence (AI) is shifting this paradigm. Done right, AI-enabled risk and compliance tools can do more than detect suspicious activity. They can drive revenue. They can unlock faster customer onboarding, enable safer cross-border expansion, and improve customer segmentation. In short, they can help banks and fintechs grow smarter.
This is not theoretical. Banks in emerging markets are using AI to leapfrog legacy infrastructure and reimagine onboarding timelines from weeks to days. Global financial institutions are deploying cognitive machine learning models that detect suspicious behavior across payment networks, jurisdictions, and languages. These same insights are also being used to identify new customer patterns, enter confidently into high-risk markets, and launch targeted products. In regions where financial crime is deeply entangled with geopolitical complexity, AI can reveal network-level threats and opportunities that human analysts alone cannot uncover.
Consider customer onboarding. Traditional know-your-customer (KYC) processes are often slow and error-prone, particularly for cross-border clients or those with limited credit history. By leveraging AI to analyze transaction behavior rather than static documentation, financial institutions can bring new customers into the system quickly and confidently. That speed directly translates into revenue.
Or take transaction segmentation. AI does more than flag suspicious activity. It can detect nuanced patterns in transactional data that point to high-growth customer segments: small businesses that are underserved by traditional banks, diaspora remittance flows, or fintech partners operating in complex payment corridors. With the right intelligence, banks can safely say yes to more customers while maintaining strong risk controls. That is a foundation for scalable, sustainable growth.
Of course, none of this is possible without trust. AI must be explainable, auditable, and compliant. Black-box models do not belong in a regulated environment. Nor do tools that focus solely on remediation while ignoring the needs of investigators, regulators, or internal reporting. Financial institutions need end-to-end AI platforms that support the full compliance lifecycle, and which can align seamlessly with broader business strategy.
I’ve witnessed this shift firsthand. ThetaRay’s partners use our Cognitive AI not only to monitor hundreds of millions of transactions each year, but to enter new markets, accelerate onboarding, and strengthen customer trust. This is not just about technology. It is a mindset change. The same tools built to detect illicit activity can also identify untapped opportunity and unlock new value.
In an increasingly evolving risk environment, financial crime compliance is no longer a back-office concern. It is a front-line growth lever. The challenge for compliance leaders is to move beyond containment and embrace enablement. Cognitive AI provides the visibility to do just that. But the real transformation happens when insights become action — when institutions stop using AI just to reduce risk and start using it to create value.
Jeff Otten is the Chief Revenue Officer of ThetaRay, a provider of Cognitive AI financial crime compliance technology.
