EBAday 2026 brought leaders in the payments space to Copenhagen for two days, and we came along to soak it up. From keynote discussions from prominent experts to in-depth discussions with European banks one thing is clear:

Under SEPA instant payments, liquidity risk is changing faster than the industry’s ability to manage it.

But why does this matter? Let’s go into more detail.

Funding plans had almost always been modelled on an end-of-day basis, but today, real-time is quickly becoming the new standard. Institutions now need to work in real time, as instant is the new baseline. They must build around this new norm.

Payments start with liquidity. When payments are instant, they’re harder to track and predict. This is demanding more from treasurers. And they need the tools and technology to forecast and plan liquidity needs.

In short, when liquidity fails, payments fail.

Now the scene is set, here are the three things we learned:

1. Liquidity behaviour is becoming harder to understand

Instant payments are scaling, but growth is unpredictable and uneven. For scheme participants who work across multiple countries, some geographies are adopting instant payments faster than others. Some banks are also seeing their commercial customers adopt instant payments with high-value transactions, such as property and vehicle purchases.

These nuances add complexity, making it hard to know where to focus and to understand where future growth will come from.

Banks are seeing these new patterns emerge across SEPA Instant. As the scheme attracts adoption and matures, but with limited historical data, there’s still uncertainty on how this will evolve. Institutions are experiencing a rise in high-value requests, too. If this trend continues, the pressure on liquidity management will be considerable.

2. Traditional forecasting approaches are no longer sufficient

Treasury teams are being asked to predict liquidity in an increasingly volatile environment. Customer behaviours are still forming – payment values and volumes are increasing. This is true for both commercial and retail customers. Payment flows are also increasingly event-driven. Requests no longer have the luxury of clearing over days, but in seconds, to comply with SEPA Instant standards. This expectation will change the culture of payments in the years to come; instant will become the new norm.

For funding models to work, banks need access to timely and accurate data. But the question we heard repeatedly was simple: “How can banks forecast with confidence when the data doesn’t yet exist?”

Data is also at the heart of the problem.

3. Operating models are struggling to keep pace

Data aside, banks are struggling from a basic operational perspective. Many institutions still rely on manual monitoring, static thresholds and conservative pre-funding strategies.

This setup is not instant payment-ready. Incumbent systems assume an end-of-day approach to liquidity risk management, and now that payments are being managed 24/7 in real time, their capabilities are no longer fit for purpose.

Operating models need to reliably position liquidity ahead of demand and to act in an unconstrained way, outside of traditional funding windows and methodologies.

What’s striking is that, while the industry is actively analysing these challenges, this is not a future problem.

Liquidity risk is rising in instant payments now. Gladly, it’s already being solved.

But some banks have moved beyond this early-stage uncertainty. These banks are:

• Monitoring liquidity in real-time across instant payment systems,
• Identifying emerging risks as they develop, not after they materialise,
• Applying forward-looking, adaptive AI models to anticipate liquidity demand,
• Operating with automated alerting, removing the need for constant manual oversight.

These capabilities are in operation today and are helping treasury teams manage real-time liquidity with confidence.

The conversation at EBAday focused on how payments are evolving. The reality we’re seeing is a state where liquidity management needs to evolve just as quickly.

Banks need to move from static monitoring to continuous prediction and control. And for a growing number of institutions, that shift is already underway.