Anti-Money Laundering Technology Assessment
The Challenge
Our client wanted to better understand how different technologies can be used to improve anti-money laundering work, and the key obstacles to more collaboration around implementing new ways of detecting money laundering.
The objective was to validate our client’s proof of concept for new ways of combating money laundering using a data-driven approach based on artificial intelligence, machine learning, privacy-enhancing technologies and network analysis.
The Solution
Conducted >10 expert interviews with leaders across various financial institutions, including Banks and FinTechs in the EU, Asia, and North America
Led a team of 2 analysts to evaluate current and planned technology and approaches to combat money laundering, covering challenges to detection across legal, regulatory, technological, operational and data management
The Results
It was found that while new technology like network analysis & generative AI can drive efficiency, low adoption of privacy tools and high integration costs reveal a gap in secure, seamless collaboration across financial institutions. These findings informed our client’s strategy for potential automation, data integration, and regulatory reform.
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This project was delivered in partnership with 10EQS — recognized by the Financial Times and Statista as the UK’s leading consulting network in 2024 for the third consecutive year.
