This paper describes the efforts of a team of researchers to develop a federated AML model for the UK Financial Conduct Authority’s Global Anti-Money-Laundering and Financial Crime Tech sprint. The model was trained on data from several financial institutions and outperformed a conventional AML model in detecting potentially suspicious activity by 20%.