THE FINTECH INTERVIEW
C had Hetherington’ s perspective on AI in financial services is shaped by a simple premise: intelligence must serve measurable business outcomes, not technology for its own sake. As Global Head of Product at NICE Actimize, his role centres on addressing the technology evolution across financial services organisations, targeting complex requirements in anti-money laundering, enterprise fraud and payments, trade surveillance, case management, and more.
He says:“ I have a specific focus on the delivery and deployment of enterprise grade solutions, and I’ m responsible for developing and overseeing the execution of NICE Actimize’ s company strategy, which has led to significant company growth over the last several years.”
That strategy positions NICE Actimize as a global leader in AI-powered solutions for financial crime prevention, compliance and risk management. As part of NICE, the firm helps banks, payment providers, insurers and other financial institutions detect fraud, combat money laundering, manage regulatory obligations, and protect customers through intelligent automation and advanced analytics. Its cloud-native platform enables organisations to make faster, more informed decisions, accelerate investigations, strengthen regulatory compliance, and deliver trusted digital financial experiences.
“ Trust is the currency on which the financial system runs”
Chad Hetherington Global Head of Product NICE Actimize
Why some AI programmes scale – and others stall Asked what separates companies that successfully operationalise AI at scale from those stuck in endless pilot programmes, Chad points to three starting points: trusted data, clearly defined business outcomes and strong governance.
“ In financial services, AI creates the greatest value when institutions understand where operational friction exists and apply intelligence to measurable business challenges,” he says, citing examples such as reducing fraud losses, accelerating investigations, improving customer onboarding, or strengthening regulatory compliance.
Institutions that remain in pilot mode, by contrast, often lack a clear data strategy or operational roadmap, he adds.
“ AI initiatives deliver lasting value only when they are embedded into enterprise workflows and measured against business and regulatory outcomes,” Chad explains.
28 October 2026