The use cases for artificial intelligence (AI) span a broad range of critical functions of a central bank including data analysis, research, economic forecasting, payments, supervision and banknote production.
The potential risks are wide-ranging and include those around data security and confidentiality, risks inherent to AI models (eg “hallucinations”) and, importantly, reputational risks. The potential risk exposure for central banks can be significant, owing to the criticality and sensitivity of the data they handle as well as their central role in financial markets.
This report on the governance of AI adoption in central banks provides guidance on the implementation of AI at central banks and proposes a governance and risk management framework. A comprehensive risk management strategy can leverage existing risk management models and processes, in particular the well established three lines of defense model.
In incorporating the specific issues around AI and its use cases, risk managers at central banks can make use of the frameworks proposed by a number of international bodies. A good governance framework is key for adopting AI. The report proposes an adaptive governance framework and recommends ten practical actions that central banks may want to undertake as part of their journey in adopting AI.