Synthetic data is one of many privacy enhancing technologies that can expand and support data sharing. While it has the potential to address important financial services public policy issues, such as financial crime and fraud, there are still open questions that are being researched.
This report from the UK Financial Conduct Authority focuses on 3 key themes across the data lifecycle:
- data augmentation and bias mitigation system
- testing and model validation
- internal and external data sharing for fraud controls
These themes, illustrated through real-world use cases and the experiences of expert practitioners, provide insights into the opportunities and challenges that can arise from using synthetic data in financial services.
These insights will be of interest to industry participants including financial services, regulators and policymakers internationally. The key findings provide a helpful overview of the steps to consider when creating, using and sharing synthetic data, and the most relevant use cases across financial services.