Adam Muhtar and Dragos Gorduza

Imagine a world where machines can assist humans in navigating across complex financial rules. What was once far-fetched is rapidly becoming reality, particularly with the emergence of a class of deep learning models based on the Transformer architecture (Vaswani et al (2017)), representing a whole new paradigm to language modelling in recent times. These models form the bedrock of revolutionary technologies like large language models (LLMs), opening up new ways for regulators, such as the Bank of England, to analyse text data for prudential supervision and regulation.