Cash & Liquidity Management

The rise of real-time liquidity in an always-on world

Published: Apr 2026

Stephen Randall, Global Head of Liquidity Management Services at Citi, discusses the latest developments in liquidity management, and explains how Citi is using tokenisation and cash optimisation solutions to enable 24/7 transactions globally in a dynamic market environment.

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Stephen Randall, Global Head of Liquidity Management Services at Citi

Stephen Randall

Global Head of Liquidity Management Services
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How are your clients responding to recent geopolitical challenges?

As companies become more global in nature, their treasury functions can increasingly face different challenges – whether that’s the introduction of tariffs, geopolitical developments or changes to their business models.

In the current environment, companies are focusing on visibility over their cash balances. In some industries, treasurers might think they need to hold a bit more cash at present – but first they have to understand where that cash is located.

Citi Services’ business is in nearly 90 countries; we operate in 85 of them, and we allow our clients to move cash across border in approximately 50 countries. This does allow clients to get the visibility they need and bring liquidity together to fund their operations. The alternative is going out and issuing debt or borrowing in the local market, which is likely to be more expensive.

Which strategies are corporates using to optimise cash in this way?

The treasury teams we interact with are trying to make sure they’re as efficient as possible. This means embracing automation and straight through processing, as well as funding their businesses as efficiently as possible.

The first thing we often recommend is to make sure they’ve set up the treasury function correctly, or by setting up an in-house bank. But for companies in the e-commerce space in particular, payments are now moving faster – and as a result, there’s greater demand for cash on a real-time basis.

This demand is giving rise to more sophisticated techniques. For example, instead of sweeping cash balances together at the end of each day, we can allow some programmability. This could mean introducing a rule that says once an account gets down to a certain balance, we’re going to fund it in real-time and top it back up.

How are you harnessing technologies like blockchain and AI in your offerings?

One of the things we went live with approximately three years ago is Citi Token Services for cash, which brings blockchain technology into our suite of traditional capabilities across Hong Kong, Singapore, UK and Ireland, as well as the US.

In an industry first, we’ve taken Citi Token Services for cash, which allow us to move cash across certain key branches and plugged that into our 24/7 clearing. Banks that are part of our clearing process can take advantage of and enable their customers to send payments on a 24/7 basis in the United States.

We’re also using Citi Token Services to give clients real-time capabilities without exposing them to tokens. A lot of clients don’t have a treasury policy that allows them to invest in non-cash items. We can allow them to make real-time payments by using our technology on the backend, while enabling them to use the same front-end interface as usual.

Turning to AI, at Citi we are strategically focused on enhancing client satisfaction, strengthening risk management, boosting value delivery, and significantly improving operational productivity. We are employing AI through various solutions: Tech Assist, which uses AI to improve our technology department, and Ops, as well as Sales Assist, which helps our operations team respond to client queries a lot faster.

Some of our clients are also using AI themselves, although different companies are at different stages on that journey. Some are using it for day-to-day management in order to become more efficient. A few are getting more sophisticated in thinking about building forecasting models using AI.

How can AI support forecasting?

Say that a company is trying to forecast out its euro balance, but it has euro accounts with three different banks. If you go to one of those banks and ask them to forecast the balance, they don’t have the whole picture of what’s moving across every account.

What treasurers can do instead is take all that data and use an AI tool to forecast the account balance. This can be much more sophisticated than looking at the average balance for the last 30 days. AI can be adept at spotting patterns – for example, by identifying that on every third Thursday of each quarter, a large payment goes out to a particular supplier.

Which innovation in liquidity management are you most excited about?

I do think the tokenisation of cash and deposits is a pretty exciting space, because it takes away some of the historical challenges.

In terms of timelines, there are a lot of factors in play, and a lot of stakeholders that will play a role in determining how fast this is adopted. Client adoptability is a consideration – but there are also questions around how fast the industry as a whole can move, including bank participants, regulatory framework and clearing bodies.

But the real question is how clients will actually use this technology. If the cost of being able to make certain treasury payment flows goes down, and clients are able to drive incremental revenue for their businesses without adding risk, then I think we’ll see it being adopted.

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