How are bank treasury priorities evolving

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How are bank treasurers adapting to regulatory reform, market volatility, and the rise of agentic AI? This article looks at how treasury and asset-liability management (ALM) functions evolve to strengthen balance sheet resilience, manage liquidity risk, and prepare for digital assets such as stablecoins, while maintaining governance, efficiency, and competitiveness in an evolving financial landscape. 

This article was written by Moorad Choudhry, Founder, at Bank Treasury Risk Management (BTRM), with contribution from Andre Pereira, Product Manager, Bank Treasury, Enterprise Risk Solutions at Bloomberg. 

If ever there was a time when bank treasury functions operated in a stable, uncontroversial environment, that time passed many years ago. Today, treasurers and asset-liability management (ALM) desks are faced with a myriad of challenges, which paradoxically also present opportunities for gaining competitive advantage.  

In an industry experiencing regulatory complexity, new fintech entrants and a volatile rates cycle, banks able to achieve an optimised balance sheet structure – addressing the requirements of all stakeholders – will be ahead of the game. 

How are regulation and digital assets reshaping bank treasury strategy? 

Regulation provides the baseline compliance requirement for all Treasury teams. The Basel post-crisis reforms first published in 2010 remain to be fully implemented in all jurisdictions. The banking landscape has already undergone significant transformation during this period; will it be time for “Basel V” by then?  

In addition, the emergence of “digital” asset classes, particularly stablecoins, is an area that banks must prepare a strategy for sooner rather than later.  

Some are already there: the announcement last month by nine banks in the eurozone that they were launching a EUR-denominated stablecoins was instructive. Currently, 99% of all stablecoins are backed by USD assets. Given that regulators have not issued detailed guidance yet on how such assets should be treated on the balance sheet for ALM-related purposes adds to the challenge for banks. 

The perennial issue of liquidity risk management is just that – perennial. As the bank failures of 2023 showed, it’s still possible for banks to fail because of mismanagement of liquidity risk exposure (and of course, interest-rate risk exposure). But what will the next stress event look like?

This is a classic “unknown unknown”: will bank liquidity risk processes be up to handling it? Silicon Valley Bank and First Republic Bank were classic examples of failure for what the UK regulator termed “Pillar 2 liquidity”. Their balance sheets exhibited extreme concentration. This concentration manifested itself in three ways: 

1. Concentration by customer type;
2. Concentration by product type; 
3. Concentration by contractual tenor. 

In the absence of any forewarning of the likely form of the next stress scenario, what banks can (and should) do is to remain conservative in their funding risk management outlook and structure the balance sheet accordingly. That is one risk type where the appetite for exposure must be low. 

There is also another structural consideration on the horizon. With the evolution of stablecoins into potential central bank digital currencies (CBDCs), the traditional deposit base could gradually migrate to central bank balance sheets. This could reshape the liability side of the commercial bank balance sheet entirely.  

How will agentic AI transform ALM decision-making? 

Another consideration is the rise of AI which is set to impact banks and Bank Treasury teams as much as any other industry, and likely more than most. As experts during recent Bloomberg Enterprise Tech & Data Summit in New York stated, AI is already changing the way investment research companies operate.  

Zooming in on bank treasury, what can we expect the core ALM process to look like once systems capable of autonomously perceiving, reasoning, and taking actions to achieve goals known as agentic AI, becomes mainstream?  

AI is already in use across varied applications in the finance industry. We expect that those employed in Treasury and ALM disciplines will see, or are seeing now, the following changes: 

• Some banks have adopted agentic AI already, in processes including fraud detection and know your customer (KYC) onboarding.  

• Use of agentic AI in additional areas such as customer experience and product origination will reduce costs, and, theoretically at least, increase efficiency.  

• Most consequential, is the point at which banks begin delegating strategic-level decisions to AI. 

This has significant implications for Treasury, and crucially the bank’s ALM Committee (ALCO). As Bloomberg Intelligence analysis shows governance is one of the central themes of banks shifting towards agentic AI.”. From the ALCO perspective, accurate and up-to-the-minute balance sheet reporting will always remain paramount: to enable effective decision making on ALM-related matters requires real-time ALM risk reporting and touch-of-a-button stress testing. We expect that for those banks that adopt it for these purposes, agentic AI will be a game changer. 

Notably, the implications for ALM go far beyond automation. The very foundation of Treasury analytics (behavioral modelling of non-amenable positions and dynamic balance sheet projections for net interest income) relies on regression and statistical inference.

Agentic AI is uniquely suited to elevate this by uncovering complex, non-linear relationships within macroeconomic and market data that humans may not easily discern. In time, this could enable continuous, on-demand balance sheet optimisation and more precise scenario forecasting, transforming ALM into a genuinely adaptive and predictive discipline.

Balancing innovation and governance in treasury risk management 

 Today there are a large number of issues and risks for Treasury to manage, and it can be difficult to know where to start. There are the more technical topics such as Pillar 2 liquidity and interest-rate risk in the banking book (IRRBB); there are also areas where the industry is evolving so quickly that it may be more advantageous to eschew “first mover advantage” and observe how things develop.

The traditional pillars of sound risk management remain essential. Good governance, underpinned by the ALCO framework, and a good risk culture will, ultimately, prevail in an environment of market uncertainty and geopolitical tension. 

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