Is AI Improving Cash Forecasting Yet? J.P. Morgan Payments on Data First

Quick Summary

Mali Bartlett, Managing Director, Liquidity & Account Solutions at J.P. Morgan Payments, says client interest in AI across treasury is high, but adoption is still uneven. Some companies are already well on their way using AI and machine learning in forecasting and operational efficiency, while others are still putting their data foundations in place. Once those foundations exist, AI can help treasury teams spot patterns, analyse large volumes of information quickly and make decisions faster.

Is AI genuinely improving cash forecasting yet?

Bartlett's answer is balanced. There is a lot of interest from clients in AI across treasury, but she describes adoption as slightly uneven. Some companies are well on their way, using AI and machine learning in areas such as forecasting and operational efficiency. Others are still on the journey, and their focus is on getting the basics right first.

Why do data foundations come first?

For forecasting in particular, Bartlett calls the data foundation paramount. Forecasting across multiple entities and currencies has so many moving parts, and that is what makes it so difficult. Without well-organised data underneath, there is little for an AI model to work with.

What can AI do once the data is in place?

With the foundation there, Bartlett says AI can help treasury teams spot patterns and analyse large amounts of information very quickly, and focus attention where it matters most. The direction of travel, on both the client side and the bank side, is to help make decisions faster so that liquidity can be moved and monitored where it needs to be, when it needs to be there.

She adds that this becomes more important as the speed of payments increases across markets.

FF NEWS TAKE:

A refreshingly measured answer to a question that usually attracts hype. Bartlett does not claim that AI has solved forecasting. Her message is about sequencing: get the data foundations right, then use AI to find patterns and point attention in the right place. With payments moving faster, the treasurers who invest in data first are likely to be the ones who can act on what AI tells them.