How AI is redefining payment efficiency in banking

This article was written by Carlos Figueredo, Global Head of Payments at SAP Fioneer. 

Outdated payment systems are draining bank resources and failing to meet modern customer demands. While millions are spent annually just to keep legacy infrastructure compliant, these systems still fall short of delivering the speed, transparency and agility today’s customers expect.  

AI is changing that. It’s transforming how banks operate, from dynamic routing and payments reconciliation to liquidity forecasting and fraud detection. With adoption growing at over 30% per year, banks are already seeing tangible benefits from AI like faster settlements and more scalable operations. 

More importantly, AI is helping shift payments from a cost center to a strategic function – one that delivers faster, more transparent experiences for customers and deeper value for the business. 

This article takes a closer look at how AI is reshaping the payments industry and what banks need to do to keep up. 

What is the cost of relying on outdated payment systems? 

Banking’s relationship with payments is changing fast. Customers now expect to send and receive money instantly. Businesses want smoother operations and better liquidity. But many banks are still trying to deliver 21st-century experiences with infrastructure that was built decades ago.  

The cost of this legacy burden is clear: banks are still investing a significant amount of money into keeping systems compliant with initiatives like SEPA, which requires standards such as ISO 20022. More than half of the average IT budget in payments is spent simply on staying operational rather than driving innovation. 

SEPA shows just how high the costs can climb. The total spend on this transition reached £10.2bn, with two-thirds of that tied directly to ISO 20022 XML. It’s a considerable cost for banks, but one they had little choice but to pay — compliance is essential not only to satisfy regulators but also to remain competitive and relevant in the market.  

Hype or help? The truth about AI in payments 

AI is no longer just a buzzword in banking. It’s actively improving core processes like routing, reconciliation, liquidity forecasting, and fraud detection. Banks are actively building AI into the foundation of their operations, not just using it as an add-on.

Historically, the term AI has been used loosely in the financial sector (mainly in payments) without clearly defined or proven use cases. But this is changing due to ongoing industry challenges, new innovations and evolving customer expectations.

Despite years of digital transformation talk, friction remains a persistent problem in payments. Transactions are often slower and more manual than expected, with many systems still relying on fixed routing rules, clunky file formats and batch-based processing. The complexity increases significantly with cross-border payments. Multiple intermediaries, time zones, checks make today’s payment systems feel anything but modern. Worse yet, it ties up capital. According to Oliver Wyman and J.P. Morgan, more than $120 billion per year is spent on cross-border transaction costs, with additional hidden costs from trapped liquidity in the correspondent banking system. This is money that could be working but remains idle due to outdated processes.

The shift towards intelligent payment systems

Some banks are changing how payments move through their systems entirely by using third-party payment platforms. Instead of using fixed routes, AI models dynamically adjust routing based on fees risk exposure, and network performance. In tests and early rollouts, it’s already cutting processing costs by 10-15%. More importantly, it’s offering agility that banks didn’t have before.

Then there’s reconciliation. Matching payments to invoices has long been a pain point in corporate payments. AI now handles this in seconds using machine learning and natural language processing (NLP) techniques. In a recent conversation, one corporate banking team shared with me that they’ve reduced their reconciliation windows from two days to near real-time matching with accuracy over 98%.

That’s not just about efficiency; it frees up working capital and improves the customer experience.

Liquidity forecasting is also moving out of the spreadsheet era. Capital costs are rising, and balance sheet pressure is increasing. As a result, treasury teams are starting to rely on AI models. These models can predict payment volumes with surprising accuracy—up to 85% in some cases. That enables more precise liquidity buffers and reduces excess reserves.

Fraud detection is another area where AI is finally outperforming old systems. Rules-based tools can’t keep up with new fraud patterns, resulting in too many false positives. AI can spot subtle anomalies across millions of transactions and adjust as patterns shift. This results in fewer false alerts, stronger fraud detection, and a smoother customer experience. Still, human oversight remains essential, and no compliance team should assume the machine always gets it right. Third-party payment and core banking applications are now adding their own fraud detection tools. These tools are part of end-to-end solutions designed to further safeguard each payment.

Customer interactions are shifting too. People are already comfortable talking to their bank through a chatbot. That’s not new. What’s changing is that AI is getting better at proactively helping customers. It can nudge them when they’re heading toward an overdraft, suggest better ways to structure payments, or even flag irregular subscription charges. These are small moments, but they build trust. What matters most is giving users control and being transparent about how technology makes decisions. Customer and business experiences have become top priorities in recent years and AI is one aspect helping banks meet rising customer expectations.

Why 30% growth in AI payments signals 3 big wins for banks

Banks are beginning to see real returns from investing in AI. The AI-in-payments market is expected to hit $340 billion by 2028, with a growth rate upwards of 30%. And this isn’t just hype. Banks that have prioritized AI aren’t just seeing cost savings. They’re also achieving:

1. Faster settlements
2. Better data quality
3. More scalable operations

But these leading banks are not just treating AI like a plug-and-play feature. They’re treating it as a long-term infrastructure shift. In some cases, they are working closely with third party payment application providers to embed AI into their core systems.

How to accelerate AI adoption in payments

For AI in payments to reach its full potential, banks need to get three key things right:

1. Data: You can’t run powerful models on unreliable inputs. Clean, structured, accessible data is the foundation. More banks are realizing this, but it’s still a work in progress.
2. Integration: Most core banking systems were built long before real-time APIs or event-driven architecture. Connecting them to modern services takes effort. Middleware can help, but it needs real investment and strong governance to avoid turning into a patchwork.
3. Culture: Technology alone doesn’t guarantee success. If the teams using it don’t trust or understand it, adoption will be slow—or won’t happen at all. Success depends on breaking down silos and building a culture where business, tech and compliance work together on data-drive decision-making.

AI in payments is no longer theoretical

We’re past the point of theory. AI is already shaping how banks move money, manage risk, and serve customers. Payments used to be a cost center. Now they’re becoming a strategic differentiator. And with as much as 80% of digital payments expected to involve AI by the end of 2025, the question isn’t whether to act, it’s how quickly you can. Finding the right reliable payments partner—one that enables easy integration and a seamless go-live—is now a top priority for banks.

Discover the future of payments. Request a demo today.

Many banks still run their payments infrastructure on outdated, disconnected systems—expensive to maintain, slow to scale, and difficult to adapt. In a world of accelerating change, banks need modern technology that is resilient, high-performing, and ready to support complex, real-time demands without disruption.​

SAP Fioneer’s Payment Central helps banks move faster, scale smarter and deliver better payments experiences.

See it in action: https://www.sapfioneer.com/request-a-demo/