Unit21

Chartis just ranked Unit21 THE top vendor for AI in fraud among 40+ vendors evaluated. We're named a Category Leader in both Enterprise Fraud and Payment Fraud Solutions. 2 years ago we made a call: fraud and AML operations needed to be AI-native, not AI as a feature bolted onto a case management or rules engine. Great to see our delivery of a thoughtful approach being recognized by the market. Huge credit to the Unit21 team and to our customers who pushed us to keep raising the bar. #ai #amlcompliance #fraudprevention #fintech

Every vendor in financial crime prevention is "AI-powered" in 2026. Batch processing on 24-hour cycles? AI-powered. String matching against watchlists? AI-powered. ChatGPT wrapper on a rules engine? Definitely AI-powered. The term has been stretched so far it tells you nothing about what the technology actually does. And analyst firms aren't helping, lumping fundamentally different architectures under the same banner. So I wrote a field guide. Four categories, clear definitions, what each one actually looks like in production: ML. Classical AI. Generative AI. Agentic AI. They're not the same technology. They don't do the same things. And the difference between a risk scoring model and an autonomous investigation agent isn't a marketing distinction. It's an architecture distinction with real regulatory consequences. The piece also covers what I think is the most underrated concept in AI right now: context engineering. We've been building with LLMs at Unit21 since 2023, and the biggest lesson has been counterintuitive: giving the model less data often produces better results. The model is the engine, but the harness is the car. If a vendor can't explain how they manage context, they haven't solved the hard problem. Link in the comments. What questions do you ask vendors to cut through the AI marketing? Curious what's working for people evaluating this space.