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A head office in another country ordered an expensive compliance system just to prove something to regulators. Sven Stumbauer explains why banks build, buy, and merge compliance teams for reasons that have little to do with catching money laundering.

Sven Stumbauer has worked in financial crime since 2003, across more than 150 institutions in 60 countries, and now heads the Americas practice at Forward Global. He raised the pattern in conversation with the hosts of The Conductors, the AI Against Financial Crime podcast, for its second episode: banks are running the same script with artificial intelligence (AI) that they ran with transaction-monitoring systems two decades ago.

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.