Evolving corporate treasuries: Preparing for a Gen AI-fuelled leap of faith

On the cusp of change: Treasuries poised to harness Gen AI-enabled transformation

Around the world, businesses are facing down numerous challenges that are injecting uncertainty into the global economy – from geopolitical tensions and tariff wars to climate change, a mixed interest rate outlook and fears of a downturn.

These factors also go a long way towards explaining why corporate treasuries are moving up the internal value chain of their organisations, says Craig Windsor, Head Liquidity & Balance Sheet – Payments and Cash Management, Institutional, ANZ. Their widening role sees treasuries help the C-suite streamline operations manage risk and deliver growth, all by working to hone their day-to-day liquidity management and cashflow forecasting skills.

"Companies don't expect their treasurers to know everything. What they do expect is that they put forward various 'What if' scenarios," says Windsor. "Better forecasting capabilities help leadership to plan their investments and their expansions, and give them a strategic advantage over their competitors. It allows them to be nimble and grasp opportunities as they present themselves without fear of jumping into the unknown."

Corporate treasuries can now help their C-suite make this leap by using cutting-edge technologies to overcome the challenge of fragmented cash visibility, deploy improved scenario planning to navigate volatility and meet the growing complexities of compliance.

New tools of the trade

While a range of innovations – such as Application Programming Interfaces (APIs), virtual accounts and the seamless integration of financial services into non-financial platforms through embedded finance – have proven effective over time, two emerging technologies in particular – Generative AI (Gen AI) and tokenisation – must be understood and embraced for their ability to drive transformative change, says Hari Janakiraman, Head of Industry & Innovation, Transaction Banking – Institutional, ANZ.

Consider Gen AI-enabled treasury management systems (TMS): These systems not only enable companies to process payments and monitor liquidity and cash positions in real time, but when combined with tokenisation, they can empower customers to access banking services seamlessly and on demand – integrated directly into their financial journey.

"So, if you’re a treasurer sitting in a regional treasury centre in Singapore and want to access your money or send money to, say, New Zealand, at 4pm local time, you should be able to do it," Janakiraman says.

Such a seamless system – long a feature of retail banking – is now increasingly prevalent in corporate settings as more organisations, payment systems and regulatory frameworks adopt real-time solutions to the point where ‘anytime-anywhere’ operational capabilities become the norm.

While the availability of multiple real-time payment rails helps to ensure sufficient liquidity on a daily basis, treasurers can also enhance their ability to peer into the future using Gen AI. Of particular interest is its ability to source and synthesise data fast, and its natural language processing (NLP) capabilities – and design models that can better predict cash flow requirements and optimise crucial metrics like the cash conversion cycle.

The second technology to watch, says Janakiraman, is tokenisation, which holds enormous potential to affect how financial markets could function in future. Stablecoins, for instance, could transform global trade and payments with instantaneous, transparent and low-cost transactions – particularly following the Trump administration’s latest legislation governing these digital instruments and once existing interoperability gaps across the global financial system are addressed.

Meanwhile, stablecoin transactions have continued to grow thanks to the efforts of pilot projects worldwide, including Project Acacia, which is led by the Reserve Bank of Australia and the Digital Finance Cooperative Research Centre.  ANZ is involved and leading use cases for tokenised trade payables and tokenised bonds to support the development of wholesale tokenised asset markets in Australia.

Hurdles along the way

While Gen AI use cases are on the rise and more treasuries are embracing the technology, notes Louise Clayton, Head of Data Science, Wholesale Digital, Institutional, ANZ, companies must get one crucial ingredient right for Gen AI-powered innovations to fulfil their potential: data.

"Many corporates still use Excel spreadsheets even though they know there are more sophisticated technologies available because they trust in tried and tested methods. Another big driver of this trend is data fragmentation – they don't have access to data, even basic information like who their suppliers are. You'd be surprised at how opaque information can still be," says Clayton.

"So, for a treasury or finance team to model, forecast and make decisions around that, all the data needs to be clean and reliable, and integrated in one place. Data is fundamental to predictive analytics because the AI system will rely on that information to give you insights."

Other key steps include adopting agile, API-driven platforms, leveraging virtual accounts (which have been around for a long time) for efficiency and compliance, and staying abreast of regulatory, environmental, social and governance (ESG), and digital currency trends.

Additionally, as corporates struggle with breaking down silos around legacy systems and creating a unified set of clean, reliable data for their Gen AI applications, they must also manage this transition – which is not easy.

"There is a high barrier to change and one of the reasons for that is explainability. You need to be able to explain the decision-making process of any model, in a way that customers can trust in what the output is providing them," says Clayton. "With any of these tools, treasury and finance teams will want to know why things are being modelled a certain way and where the information the systems are using is coming from."

As companies seek to overcome resistance to these new technologies, while also training and upskilling employees in their use, they are faced with a dual cost that can make the transition an expensive proposition and likely prompt them to wait and watch until adoption picks up.

"Getting people along for the journey is going to be the bigger challenge based on this cost trade-off," says Balaji Natarajan, Head of Strategic Sales – Payments and Cash Management, International – Institutional at ANZ.

One way to get around this, says Clayton, is to get help, and of the right kind.

"A company's leaders are not necessarily going to be across every aspect, so they need to partner with the right people who understand AI and data, including their own tech team, their bank and other service providers," Clayton says.

Help is also available in the form of tools typically offered by financial service providers. ANZ’s Transactive Global and Fileactive, for instance, provide solutions including the ability to directly integrate ERP and TMS systems, analyse transactions and schedule emails.

Balance and transaction reporting like this is available in multiple jurisdictions and, more recently, ANZ has also launched Transaction Analysis, helping Australian customers in-channel understand their cash flow trends and historical balances over a 24-month period – information that can help project future cash needs with greater accuracy.^disclaimer

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Source: Example data in ANZ’s Transaction Analysis dashboard

Dashboards like these provide visibility into cash and liquidity metrics in real-time while Gen AI empowers treasury teams to better analyse the data, improve their forecast accuracy, and make faster and smarter decisions. This is a key benefit for treasurers as they increasingly focus on scenario-planning and risk-modelling in their evolution from a transactional operation to a strategic value centre, says Windsor.

"Gen AI is not just about automation; it's about augmentation," he adds. "The technology also enables natural-language and voice-enabled interfaces, which do away with the need for, say, structured commands in spreadsheet software; users can just ask a question in plain English. And by doing so, Gen AI can democratise access to insights and reduce the dependency on specialist analysts."

Futuristic finance

Further along from Gen AI is Agentic AI, which some companies are experimenting with. From a corporate treasury perspective, says Natarajan, Agentic AI can help companies do more with fewer resources, including taking automation to the next level.

Agentic AI can fully automate certain functions, he says. For instance, a customer service agent can communicate with an agentic AI tool to instantaneously generate the information sought by a client, such as term deposit rates. From a treasury perspective, treasurers can use agentic AI for tasks including expediting FX trading by modelling currency risk across scenarios, handling compliance reporting and initiating warning systems for limit breaches.

"We are still some time away from fully exploiting this technology and the real impact will come when [agentic AI tools] become sharper, more mature and developed, and can sense the same reality as a human would," Natarajan says.

If that is not futuristic enough, quantum AI is another transformative technology waiting in the wings. With the potential to optimise portfolios and simulate thousands of market scenarios in seconds, it could be a game-changer, says Janakiraman.

"It's still seven to 10 years away, but it can make a profound impact in terms of its ability to crunch a lot more data, and how AI can use that data to make itself even better."

Ultimately, deploying Gen AI-based technologies successfully will enhance the corporate treasury by supporting its role as a strategic driver of value beyond its traditional offerings of cash flow, liquidity and risk management. Businesses that invest in and embrace these technologies will be rewarded with more incisive forecasting capabilities and insights, which they can use to gain a crucial edge over their competition.