OECD – Publishing – December 2023

AI deployment in finance has been increasing in recent years (OECD, 2021). While traditional AI models have been predominantly used for pattern identification, classification and prediction, GenAI models are able to create ‘original’ output.

The use of GenAI presents immense opportunities for efficiencies across sectors, including in finance, but comes with important risks that warrants the attention, and possible action of policy makers. Such considerations are likely to become increasingly important as the deployment of AI becomes ubiquitous across markets and its pace of development increases.

Advanced use cases of AI in financial markets involving full end-to-end automation remain largely at development phase. AI in production use cases are mostly used for process automation, as a way to improve productivity at the back-office (operations) and middle-office (compliance and risk management) of financial service providers.

In the future GenAI advances are expected to increasingly support production and deployment of additional front-end use cases and applications and to further accelerate the existing use of such tools at the operational level.

Policy makers may need to consider reinforcing policies and strengthening defences against risks emerging from, or exacerbated by, the use of all AI classes in finance, focusing on strengthening of data governance and promoting accountability mechanisms.

Given the transformative effect of AI there is a need for a safe AI deployment.. Support for interoperability among burgeoning AI risk management and accountability frameworks will also be critical given the global nature of financial products and services.