In early 2025, industry experts predicted that adopting AI agents in AML and KYC operations would soon become standard practice.
At the time, many banks and financial institutions (FIs) faced a key decision: build AI agents internally or buy pre-built, regulatory-ready ones. That debate has since shifted decisively.
According to WorkFusion, 10 of the world’s top 20 banks have chosen to purchase AI agents for AML and countering the financing of terrorism (CFT) operations, instead of building their own.
This trend is now filtering down to FinTechs, regional banks, and non-traditional financial players. A June 2025 Boston Consulting Group (BCG) report noted that FinTech revenues surged 21% year-over-year in 2024, up from 13% the year before. Banks are also setting more ambitious growth targets for new products and digital services. “Technology resources should be allocated away from cost avoidance initiatives and toward projects that improve new features, enhance integrations, etc.,” said BCG. The implication is clear: engineering and development teams should focus on innovation, not internal cost-heavy builds.
Engineering teams within banks and FinTechs know that creating AI agents from scratch is a costly, time-intensive process that rarely meets expectations. Even if technically feasible, such projects often fail to deliver regulatory-grade performance or ROI. When pre-built AI agents are already available for compliance workflows, building internally makes little sense. Moreover, designing an in-house AI agent capable of managing customer satisfaction, regulatory compliance, and operational efficiency is a massive undertaking—one that stretches technical and compliance resources thin.
WorkFusion argues that buying AI agents doesn’t just offer faster ROI—it drives geometric value growth. To illustrate, a multiplicative progression (2, 4, 6, 8, 10) grows linearly, while a geometric progression (2, 4, 8, 16, 32) multiplies value at each stage. That’s the difference between incremental improvement and transformative impact.
By deploying a pre-built WorkFusion AI Agent, compliance teams instantly gain a foundation for efficiency gains across key areas including operational scalability, information accuracy, regulatory reporting, and AI explainability. These improvements compound as additional AI agents are integrated across business lines.
At a top 25 US bank, WorkFusion’s AI agents helped launch new revenue-generating payment products while maintaining compliance—without increasing headcount. By standardising processes across divisions, the bank achieved consistent reporting and eliminated operational bottlenecks.
Similarly, a top 10 US investment bank deployed WorkFusion’s AI agent, Tara, in its payment sanctions screening process. After witnessing Tara’s accuracy, the bank reused the same agent to support a new Banking-as-a-Service (BaaS) offering requiring high-speed compliance checks. The result: 1.5m alerts processed annually with an error rate of just 0.03%, and 0% unexplainable results. Achieving that level of precision with an internally built tool would have been virtually impossible.
Ultimately, pre-built AI agents like those from WorkFusion don’t just save time and money—they unlock new opportunities for scalable, compliant innovation. The value they create is not only measurable but exponential in its organisational impact.
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