Global AML specialist Napier has announced the appointment of its chief data scientist, Dr Janet Bastiman, to the Financial Conduct Authority (FCA)’s newly created Synthetic Data Expert Group, a sub-group of the Innovation Advisory Group (IAG). The IAG, created in March 2023, aims to deepen Innovation’s engagement with industry and to inform the FCA’s forward-looking work programme, including alternate approaches to future TechSprints. 

The new group has been formed to examine the role synthetic data has to play in protecting consumers and encouraging beneficial innovation in financial services through the use of its enhanced capabilities. The group assembles diverse and experienced professionals representing technology and data vendors, regulated firms, consultancies, and public sector organisations. It aims to identify relevant use cases and clarify key issues in the theory and practice of synthetic data in the UK financial market, and create an established framework for collaboration across industry, regulators, academia, and the wider civil society on issues related to synthetic data. 

The appointment comes hot on the heels of Bastiman’s appointment to chair of the Royal Statistical Society’s Data Science and AI Section.  

“It’s a great honour to be appointed by the FCA to the Synthetic Data Expert Group and I’m looking forward to bringing my extensive experience and expertise in data and ethics to help formulate best practices for the UK financial sector” she says. “It’s another amazing tool with huge potential in the armoury of financial crime fighters. Closer working relationships with regulators and law enforcement agencies can only strengthen our response to global money laundering.” 

Bastiman has spent more than 20 years in the industry, pushing the boundaries of data science in telecommunications, marketing, and the financial services sector, where she has helped both start-ups and established businesses implement and improve their AI offering. She regularly speaks at conferences on topics in AI including explainability, testing, efficiency, and ethics.