The modernization imperative: drivers and opportunities for banks and payment companies

Modernization of IT systems has long been an aspiration for banks and payment companies. But now a series of factors, including technology change and the advent of artificial intelligence (AI) has accelerated the need for modernization to move to the top of the board agenda.

So what are the steps that financial institutions need to take today to respond, and what are the opportunities that their actions today will open up for the future?

Mike Wear, CEO of BlankFactor, says that new drivers mean it’s more important than ever for organizations to be able to respond to change: “They need to have the capability to launch new products and services for their customers, but also to align with regulatory requirements, which have seen a tremendous amount of upheaval over the last three years in banks and payments.”

This means that modernization is no longer optional for financial institutions that want to compete through innovation.

From a payments perspective, there are several trends driving the industry, explains Rick Foresta, Chief Product Officer for Lending at Finastra. He agrees that regulatory change is one of the most important.

“Regulatory change has been fast and furious over the last couple of years and it’s going to continue to be the case,” he says. “It’s eating away a lot of technology capacity and bandwidth - leaving little room for innovation.”

The second trend is that requirements for real-time payments mean technology stacks need to be more resilient, 24x7, 365 days a year. Banks also face a constant increase in the cost of ownership of legacy payment platforms.

Looking externally, corporate customers expect better experiences similar to those they are used to in their lives as retail consumers, Rick says. “If I can carry out retail banking transactions on my mobile phone, why can’t I do the same with transactions for my corporate banking? Banks are also trying to figure out how to use new alternative payment models, such as stable coins, which customers are interested in accessing.”

These factors, together with the wider trend to seek operational efficiencies with AI, are leading banks and payment companies to modernize their technology stacks so they can adapt their business models to be forward compatible, adds Rick.

How to avoid pitfalls when approaching modernization

One of the biggest mistakes organizations make when addressing their need to modernize technology platforms is to see it as a one-time initiative, says Sarah Maleka, Chief Technology Officer for Lending at Finastra.

“Then they try to do the lot with a big bang approach, versus taking a more incremental approach focusing on the quick wins that can add the most value to customers as early as possible,” she says.

Mike adds that organizations underestimate how difficult modernization programs can be, and that it takes commitment to stay with them over time. “That’s why it’s so important to deliver incrementally so your leadership, customers and in some cases your investors, can stay motivated,” he observes.

A second factor is to frame programs so they are grounded in very clear, easy to understand business outcomes that have buy-in from everyone in the business, including product engineering, but also within sales, customer service and operations – people who will be selling change to customers.

Radha Suvarna, Chief Product Officer for Payments at Finastra, says that there are a number of other factors to be aware of. “One is chasing the latest, greatest technologies instead of crafting a specific playbook relevant to their organization, based on their internal technology stack but also the client segments that they serve.”

It’s also important to remember that there is no “one-size-fits-all” modernization approach, and that any program should deliver value progressively, whether the value is better customer experience or efficiency improvement. “It’s a continuous journey that relies on a culture of being always ready to transform: that’s the new mantra,” Radha adds.

Where should organizations begin the journey?

While financial institutions have invested heavily in modernizing client-facing experiences, they have delayed making changes to core banking and payment processing. The overriding attitude was that if a core banking system wasn’t broken there was no need to fix it.

Now many organizations have reached a point where this approach is becoming something of an impediment in terms of customer experience and making platforms forward compatible.

The place to start is with ‘sequencing modernization’, explains Sarah. “How you sequence and what you focus on first really depends on the state of the organization’s tech stack and operations.

“For lending specifically, I would start with integration with a very lightweight platform foundation. That’s because it’s within the integration layer that we are able to decouple the back end from how customers connect to systems. The goal then is to simplify the integration layer and then continue to with modernization of the back end.”

Mike agrees that this is the right sequence to follow: “In our business what used to be the largest work stream in any modernization initiative would involve getting off the mainframe and COBOL to a modern technology like Java. It would take hundreds of people working for months or years to convert legacy jobs.

“With AI tools that work stream is completely different. The upfront work is to define the components, define the architecture and patterns across your business, then leverage modern tools to generate those jobs in a lot less time.

The same goes for the front end, Mike adds. “In many banks you’re going to have several thousands more front-end screens than your customers or your operational staff use. Rewriting all those screens is almost certainly going to take more time than your leadership team is willing to give you. So by definition, you have to identify what is reusable and how you can use modern tools to do a lot of grunt work as quickly as possible – in some cases eight to 10 times faster.”

The growing role of AI in modernization

AI is now influencing how organizations modernize and how to think about modernization efforts. According to Radha, there are three key areas to look at from a payments perspective in particular.

“The first is the software development lifecycle from gathering requirements through code displacement to testing and development,” she explains. “The second is customer deployment and migration. In one case, we have developed tools that can shrink a process such as a gap analysis from four months down to a few weeks.”

Perhaps the most important example is in client facing solutions, Radha adds. “In payments, 98% of transactions go straight through without anybody touching them. But 2% go into pinned mode and have to be dealt with by payment operations personnel, who have to click through a bunch of screens. It can take six to 10 minutes for each transaction to be fixed.”

In response, Finastra has developed a tool called Operator Assist that simplifies and takes instructions through natural language, shaving up to 30% off each transaction.

Sarah adds that Finastra is also bringing AI-led innovation to product development and engineering productivity in lending, including code to generate test cases and building automation for faster release cycles.

AI is therefore a force multiplier and accelerator, not a complete replacement, and a huge amount of human labor would be needed to achieve the same results in the past, says Mike.

“Even with AI you still need human labor, but the right tools can refactor systems even better than people – because finding experts in COBOL and some of those older technologies is getting more and more challenging,” he says. “It represents a big area of cost savings and efficiency.

“It’s also important to recognize that customer expectations are changing fast – they expect to be able to interact with their financial lives just like they interact with ChatGPT or any of those other generative AI tools.”

Of course, there are risks to be managed when using AI tools, and systems are only going to be as good as the data and governance models used.

Yet while at the moment output from AI still has to be reviewed and corrected, the evolution of datasets that can generate models to provide decisions and real-time actions will continue. It will set the pattern for everyone involved in banking and payments for the next few years and beyond.

In the meantime, financial institutions need to consider how to get their front- and back- office systems in shape to meet emerging customer expectations, while paving the way for ever-more sophisticated AI capabilities that will help modernize the industry as a whole.

Modernization is no longer about upgrading technology for its own sake. It is about giving banks and payment companies the flexibility and reliability they need to operate in a fast‑moving, always‑on environment.

Organizations that treat modernization as an ongoing, business‑led effort can improve customer experience, respond more effectively to regulatory change, and create room for innovation. Those that delay risk being constrained by legacy complexity at a time when expectations and competition continue to rise.