Banks are leveraging GenAI for a variety of uses, from fraud detection to portfolio management, and across various functions from IT to wealth management. McKinsey Global Institute estimates that across the global banking sector, GenAI could add between US$200 billion and US$340 billion in value annually.
The treasury function in banks also stands to benefit from this GenAI wave. The traditional treasury system was designed to provide the treasurer with tools to manage liquidity, funding, and risk. They have faced new and more complex challenges in recent years, such as more volatile financial markets requiring instantaneous liquidity and risk computations, new instruments and markets enabling more complex structures that stress existing treasury system capabilities and innovations which have enabled faster trading and delivery cycles for flow instruments. Today, this treasury system faces another new inflexion point, the rapid rise of GenAI.
Earlier iterations of AI involved pattern recognition and taking over repetitive functions. GenAI, however, introduces levels of cognition and intelligence that can comprehend context, analyse complex data, and support instantaneous, data-driven decision making. This evolution, known as agentic AI, heralds a new milestone in treasury management. Much like how electronic trading transformed market execution, blockchain revolutionised payments, and the cloud redefined operational agility across technology stacks, GenAI is poised to become a strategic partner for the modern treasury function.
From automation to augmentation
The traditional treasury management system has automated the fundamental functions of a treasury. These include tracking positions and limits during trading hours, executing payments, aggregating balances, and reconciling transactions. GenAI takes these activities to a new level. By deriving insights from structured and unstructured data across multiple systems, GenAI helps treasurers interpret dynamic market fluctuations, assess liquidity exposures, or forecast funding needs in real time.
Instead of making sense of dashboards or spreadsheets, a treasurer could simply input the following question into a GenAI-powered LLM platform – “How would a 25-basis-point rate cut impact my short-term liquidity position?”, and receive an instant, data-driven response. In this, GenAI evolves the treasury system from a technological tool to a trusted strategic advisor able to synthesise information, make tailored recommendations, and even execute routine actions within pre-set risk parameters.
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An example of GenAI being deployed within a treasury function is Kondor Assistant, an AI-powered chatbot that simplifies complex tasks and enhances user experience by providing intuitive and efficient access to financial data. It helps treasury professionals interact with complex financial data via a seamless and interactive GenAI-powered interface with natural language, simplifying access to insights and generating detailed reports.
Responsible AI for a regulated world
The transformative potential of GenAI within the treasury function comes with an equally important responsibility: to build and deploy it safely. Treasury operates within one of the most tightly regulated environments in BFSI, where data privacy, compliance, and operational resilience are paramount.
GenAI systems must adhere to stringent governance, transparency, and security frameworks. Every AI-generated insight must be explainable; every data access must be authorised and auditable. Treasury functions looking to deploy GenAI must ensure that data privacy controls, human oversight, and compliance-by-design principles are baked into every stage of development and eventual deployment.
Regulators in the region are already cognisant of this. The Monetary Authority of Singapore (MAS) has undertaken Project Mindforge to examine risks associated with AI, and developed a toolkit to promote the fair, ethical, accountable and transparent use of AI in Singapore’s financial sector. Hong Kong’s Financial Services and Treasury Bureau (FSTB) also laid out guidelines when it comes to BFSIs deploying AI. Against the backdrop of these regulations, treasury teams must ensure their deployments are adherent to them.
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The treasury function’s new paradigm
GenAI is a game-changer in how treasurers manage complexity. As agentic AI systems mature, they are increasingly embedded across the treasury value chain, from cash and liquidity management to risk analytics and regulatory reporting.
It enables the sales trader to understand their customer better and manage order flows. The risk manager can focus on the limit exceptions and alerts identified by their assistant rather than trawling through reams of data. The operations user is able to quickly make sense of a complex trade record.
GenAI is more than automating treasury; it is augmenting it. The future belongs to treasurers who see AI not as a back-office tool but a strategic extension of their team. GenAI could help set treasury functions on a path toward a more intelligent, responsible, and proactive style of treasury management.
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