Vendor evaluation checklist

The agentic AI vendor evaluation checklist for financial crime

Every vendor now claims some version of agentic AI. Very few agree on what it means, and fewer still can back it up under direct questioning. One framework to bring into any vendor call, RFP, or POC scoping conversation.

The agentic AI vendor evaluation checklist for financial crime

What you'll learn

  • The universal questions to ask any vendor across six dimensions: design, context, control and oversight, tool and model fit, feedback and evaluation, and governance and safety
  • Eight red flags that signal the “agent” is not actually agentic, from unscoped context to synthetic evaluation data to all-or-nothing autonomy
  • Use-case supplements with targeted questions for AML investigation, fraud prevention, sanctions screening, entity onboarding, and network analysis and consortium intelligence
  • A four-stage maturity spectrum and scorecard for classifying every vendor claim from rule-based to fully autonomous, and scoring each workflow 1–4 before it costs you a budget cycle

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About this checklist

Agentic AI is now the default claim in financial crime software. The gap between a platform that has genuinely automated investigative work and one that has repackaged an existing model with new marketing is almost never visible in a demo. It shows up in how a vendor answers specific questions about context, autonomy, evaluation data, and audit trails.

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This checklist is those questions. It gives you a universal set that applies to any agentic workflow, supplements for five specific use cases, practical steps for running the evaluation, and a scorecard to track vendors against.

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Score each workflow separately. A vendor can be a Level 3 on AML investigation and a Level 1 on sanctions screening, and most of the ones you are looking at will be.

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