As the financial crime and compliance solutions market shifts toward enterprise-wide, platform-led solutions, artificial intelligence (AI), including both generative AI and agentic AI, is the primary force shaping buyers’ priorities. But some vendors are claiming ‘agentic AI’ capabilities that do not, in our opinion, constitute agentic AI.
This research paper, a collaboration with Unit21, provides a tactical framework that buyers of financial crime technology can use to evaluate the maturity of agentic AI. It defines what agentic AI is and what it is not. It defines a maturity spectrum, from basic automation to fully agentic systems, and applies it to five core use cases: AML investigations, network analysis, fraud prevention, sanctions screening and onboarding. Buyers can use this framework to evaluate vendors’ claims with respect to AI, compare capabilities and help them make informed procurement decisions.
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