The Bank for International Settlements (BIS) has urged central banks to embrace artificial intelligence (AI) in anticipation of its transformative effects on the economy and financial system. Central banks are encouraged to harness AI within their operations to enhance financial and price stability. Widespread AI adoption could significantly impact inflation dynamics, among other economic factors.
The financial sector stands to gain substantially from AI, with improvements in lending and payments, but it also faces heightened risks such as sophisticated cyber attacks. The importance of data in the AI revolution necessitates increased cooperation among central banks.
According to a special chapter of the BIS Annual Economic Report 2024, AI will influence the financial system, labor markets, productivity, and economic growth. Central banks must prepare for these changes and leverage AI to improve their analytical tools. AI’s potential to enable faster price adjustments in response to macro-economic changes could affect inflation dynamics, directly impacting central banks’ roles as economic stewards.
Central bank use cases for AI include enhancing nowcasting by using real-time data to better predict inflation and other economic variables, and identifying financial system vulnerabilities. AI’s reliance on vast amounts of data makes it a crucial resource for central banks aiming to improve risk management and economic predictions.
“New generation AI models have captured our collective imagination through their uncanny abilities, but they also have a direct bearing on how central banks do their jobs,” said Hyun Song Shin, Head of Research and Economic Adviser at the BIS. “Vast amounts of data could provide us with faster and richer information to detect patterns and latent risks in the economy and financial system. All this could help central banks predict and steer the economy better.”
The BIS report highlights that the effects of AI on demand and inflationary pressures will depend on the speed at which displaced workers find new employment and whether households and firms anticipate future gains from AI. Initially, supply might outpace demand, potentially lowering inflationary pressures, but this could reverse as demand catches up with higher incomes. Central banks need to monitor these dynamics closely in their monetary policy.
In the financial sector, AI promises to improve efficiencies and reduce costs in payments, lending, insurance, and asset management. However, it also poses risks, such as new cyber attack methods and the potential amplification of existing risks like herding, runs, and fire sales.
The BIS Innovation Hub is actively testing AI’s capabilities in collaboration with central bank partners. “Central banks were early adopters of machine learning and are therefore well-positioned to make the most of AI’s ability to impose structure on vast troves of unstructured data,” noted Cecilia Skingsley, Head of the BIS Innovation Hub. “For example, Project Aurora explores how to detect money laundering activities from payments data, and Project Raven uses AI to enhance cyber resilience.”
