Synthetic digital data in global finance: great expectations, what realizations?

Abstract

Synthetic data are artificially generated data sets that aim to replicate the patterns and structures found in real-world data. This chapter assesses the great expectations placed on synthetic data in the early 2020s, focusing on their integration in finance. We provide two key findings. Firstly, despite substantial enthusiasm from both industry and regulatory actors, the actual adoption of synthetic data in global finance remains limited. Secondly, where implementation has occurred, it has been inconsistent and largely driven by regulatory initiatives rather than by financial institutions themselves. The growing interest in synthetic data signals a broader transformation in financial governance. Technology start-ups and multinational tech firms—once relegated to back-office roles—are becoming increasingly central players in shaping regulatory and operational standards. These new dynamics, particularly as synthetic data firms collaborate more closely with banks and regulators, introduce a range of risks that we examine across national, regional, and global levels.