Generative AI agents can replicate key cash-management tasks - even without specialised training, according to a Bank for International Settlements working paper.
As banks spend billions bringing artificial intelligence to huge swathes of their operations, BIS has looked into how GenAI can assist in managing cash and liquidity in real-time gross settlement (RTGS) payment systems.
Researchers used prompt-based experiments with ChatGPT's reasoning model to evaluate whether an AI agent can perform high-level intraday liquidity management in a wholesale payment system.
This involved simulating payment scenarios with liquidity shocks and competing priorities to test the agent's ability to maintain precautionary liquidity buffers, dynamically prioritise payments under tight constraints, and optimise the trade-off between settlement speed and liquidity usage.
Even without domain-specific training, the AI agent closely replicated key prudential cash-management practices, issuing calibrated recommendations that preserve liquidity while minimising delays.
"These findings suggest that routine cash-management tasks could be automated using general-purpose large language models, potentially reducing operational costs and improving intraday liquidity efficiency," says BIS.