New project to tackle money laundering launched by Plenitude, Alan Turing Institute, Napier AI and FCA

🔍 The Challenge

Developing innovative AML solutions has long been hindered by the lack of realistic, high-quality data to train and test models. This project bridges that gap by creating a fully synthetic dataset derived from anonymised financial transactions, enriched with a wide range of money laundering typologies.

🚀 The Solution

The synthetic dataset will be available next year in the FCA’s Digital Sandbox, offering firms a secure and controlled environment to:

• Test and demonstrate advanced detection techniques.
• Move beyond traditional rule-based systems to AI-driven solutions.
• Evaluate and improve the robustness of AML tools.

💡 Key Benefits

Innovation: Demonstrates that synthetic data can be used for the testing and training of new and emerging AML approaches (including AI), and will provide a platform to demonstrate that these new approaches can result in significant benefits when it comes to the detection of money laundering. 

Privacy: Protects sensitive information while mimicking real-world scenarios.

Impact: Aligns with the goals of the UK Economic Crime Act and FCA’s Business Plan, to create a more competitive and dynamic market for money laundering detection solutions and increase the ability and the efficacy of retail banks to detect and prevent money laundering.

This project aims to overcome barriers in innovation by providing a secure and realistic environment for AML advancements.

💡 Firms exploring innovative solutions for AML challenges should review this initiative to understand how synthetic data can drive secure and effective model development.