| Link(s): | Research Note: Synthetic Data and Anti-Money Laundering – Project Report | FCA Research Note: Synthetic Data and Anti-Money Laundering – Project Report |
Context
The FCA has published a report presenting the findings of its Synthetic Data and Anti‑Money Laundering project. The report summarises the work it has done, jointly with the Alan Turing Institute, Plenitude Consulting and Napier AI, to generate a synthetic data set that will be used to foster innovation in the detection of money laundering whilst safeguarding privacy.
Key points to note and next actions
- Progress in combatting money laundering depends on access to detailed financial data, but legal and privacy constraints often restrict sharing of such information.
- This project aims to tackle these challenges by collaborating to create a fully synthetic dataset created using real data from UK retail banking, enhanced with realistic synthetic money laundering scenarios observed in financial markets.
- The report sets out the context and methodology of the project work, and explores:
- testing and evaluation;
- limitations and challenges; and
- risks and next steps.
- The FCA will make this dataset available through the Digital Sandbox as part of the upcoming Synthetic Data AML Solution Sprint, inviting firms to take part to demonstrate how new technologies such as AI can help in the fight against money laundering. Participants will use the data throughout the sprint and reconvene to share insights on how synthetic data can support innovation in the fight against financial crime.
- Further details for firms that wish to apply for the Data Sprint can be found here – applications close on 26 April 2026.
- The FCA hopes this project will show that synthetic data can help regulators and firms work together, supporting beneficial innovation in the detection of money laundering.