Accenture’s treasury is based on SAP which runs alongside the ERP of the organisation. This has been an important baseline in our digital journey because it has created a single instance data lake or source of truth that we trust and has enabled us to leapfrog into using advanced technologies.

We have begun by developing what we call intelligent cash. This is made of three components, the first of which is a comprehensive dashboard, easily available to everyone in the finance function, which lays out where our cash is and in which currency; with which counterparty or if we have a cash holding that doesn’t align with our guardrails.

The second element comprises forecasting. In the past, forecasting would involve taking historical data and streamlining it. Now we use sophisticated algorithms developed by our own data scientists and consultants applied to each individual cash flow around, say, accounts payable, receivables or tax. The machine learns and evolves its algorithms, and our latest GBP forecast was spot on for the short and medium term – it forecast what actually happened. The machine is so sophisticated it can forecast better than what our people have historically been able to do.

Forecasts lead to the third component where the technology is helping us take business decisions and decide the best course of action. For example, it tells us whether to reduce our holding in a particular currency, taking into consideration its own forecasts and external data sources like the FX rate. The machine does the grunt work and people can spend less time on operations and more on thinking about risks that could happen. It also speeds up the velocity of our cash, and treasurers always need money to move quickly and without friction.

There are already many companies that profess to sell the perfect intelligent cash tool but I haven’t seen a fintech out there yet that can really do this. Tools like SAP can facilitate it, but the risk with using fintech is that treasury ends up tailoring its process to fit their model, rather than the other way around. Treasurers are also mindful of how much data they send to a third party to process on their behalf because fintech and technology like ChatGPT requires putting data in the public domain and this is not the right approach for a corporate treasurer. The technology is also developing so fast, tools are unlikely to keep pace with changes in the market. Still, treasurers can’t integrate AI internally and in isolation because it is complex and they have such a busy day job, so the best approach is to use trusted advisors with a proven track record.

Treasury can’t operate on systems alone; it is a context-based discipline and experts will always be required to make final decisions. What AI gives treasury is an opportunity to upskill people in an environment that is becoming increasingly challenging. Take our growth for example, as the business grows, our exposure to currencies, bank accounts, partners and integration work (Accenture is very acquisitive) makes having the right money in the right place at the right time increasingly challenging.

I envisage a point of time where we can engage with the technology using prose. The machine will suggest courses of action and identify issues and we will also be able to instruct it. Once we have identified risk and interacted with it, we will be able to instruct it to exchange this currency; issue a bank guarantee, downsize debt or increase a bond offering. The tool will carry out the transaction and manage the accounting in the background in a utopia for busy corporate treasurers.

Treasurers need to determine where they stand in terms of technology, conscious that it is fluid and changing so fast that they don’t tie themselves in. My advice is to set out a clear roadmap for how you want to operate in the future and start building towards that goal. AI is a fast-moving space; it will be as impactful to how we operate today as was the loom in the industrial revolution. It is transforming our industry.