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Building a new anti-money laundering detection rule has always been slow. A compliance team identifies a risk pattern, writes a business requirement, hands it off to IT for specification, waits for implementation,

Is it possible to radically reduce the Anti-Money Laundering (AML) scenario lifecycle from weeks to days — without sacrificing governance? This was the question our team set out to answer at the 2025 SAS Hackathon. We didn’t just want to build another chatbot; we wanted to solve a structural problem in the financial world: the "translation gap" between compliance policy and technical implementation.

At Consortix, we’ve spent more than ten years helping banks strengthen their defenses against financial crime. During that time, we’ve taken part in more RFIs and RFPs than we can count. The shift in what banks ask for is unmistakable. The conversations today look nothing like they did even a few years ago.

Consortix’s recent “AI and Anti-Financial Crime – Beyond the Hype” event brought together professionals from leading Hungarian financial institutions to discuss how artificial intelligence is transforming compliance and AML operations. From practical frameworks for trustworthy AI to the emergence of agentic systems like Luci, the conversations went beyond theory to focus on real-world adoption, data quality, and the evolving relationship between humans and machines in financial crime prevention.