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TLDR Fraud analysts want to use AI for investigations. Compliance teams want assurances about what data AI can access. That…
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TLDR Getting started: Projects build on top of skills. If you haven’t built your first skill yet, start with How…
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TLDR: You connected SEON’s MCP server to your AI tool, set up your persistent context and ran a few test…
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Most organizations are thinking about AI in fraud prevention the wrong way: they treat it as a magic black box…
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For the past two years, organizations have raced to integrate generative models and machine learning capabilities into their environments, driven…
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TLDR: As a fraud or AML analyst, you’ve probably run this workflow a dozen times. You paste a batch of…
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TLDR: Your first few AI queries probably felt flat. You asked something like “show me declined transactions from the last…
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TLDR: Most skills take two or three iterations to get right — with this guide, you’ll have something useful by…
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TLDR: Teams across fraud and anti-money laundering (AML) are adopting AI faster than any other technology shift in history, and…
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Fraud analysts are using AI, but fragmented data means they’re missing the signals that matter most. Here’s the fix.
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More teams are discovering that they are fighting the same underlying risk using three different vocabularies — and it is…
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Learn how automated SAR reporting supports AML compliance, what can be automated, and why human oversight is still essential.
AI & Machine Learning
Learn from industry peers, practical how-to guides and engaging videos to stay up to date on fraud trends and the latest prevention strategies.
