There’s hardly a discussion about the future—of business, technology, or society—that doesn’t include artificial intelligence. With so much noise surrounding it, some may be tempted to dismiss AI as just hype. Yet, it has the potential to be the transformational innovation it’s promised to be—provided organizations have the right people, processes, and infrastructure in place.
In a recent PaymentsJournal webinar, Nick Botha, Global Payments Sales Manager at Autorek, and James Wester, Co-Head of Payments at Javelin Strategy & Research, discussed the state of AI in the payments industry, outlined a roadmap for companies still evaluating its role, and shared a new AI-powered playbook for financial institutions.
Two Lessons Ahead
As organizations of all shapes and sizes race to implement AI, many still struggle with too many unknowns. This is especially true in the financial services industry, where highly regulated institutions have concerns about privacy and bias issues that have been identified in AI.
Because of these concerns, many financial institutions have taken a cautious approach toward AI. This has created a new challenge: the fear that the organization is falling behind in implementing one of the most powerful technologies of recent decades.
“It reminds me of when I had to teach my kids algebra in eighth grade,” Wester said. “They came to me, and I was like, ‘I haven’t taken this in forever.’ So, I went online and found their text and I was always about two lessons ahead of them and they thought, ‘Wow, you really know a lot about algebra.’”
“There are a lot of people who claim expertise in this and say, ‘I know a lot about AI,’ but really they’re only about two lessons ahead of us on AI,” he said.
Though many institutions are likely not as far behind the curve as they think, some proven use cases for AI have already begun to emerge.
These include areas like detecting suspicious activity and streamlining onboarding processes like Know Your Customer checks. AI also excels at parsing vast amounts of data, making it highly effective for analyzing payments flows to identify opportunities for reducing fees.
In fact, many organizations are now moving from small-scale pilots to widescale implementations—a shift that is accelerating every day.
“It’s almost a bit of a revolution,” Botha said. “Like the internet revolution of maybe 30 years ago, where it went from a nice-to-have to a must-have. We’re getting to that stage where you see something being applicable to so many different industries in such a short space of time. It’s going to be interesting to see how the payments space adapts and adopts the key benefits of AI.”
The Name of the Game
To illuminate the current payments landscape, Autorek conducted a survey that highlighted a common theme: a persistent overreliance on legacy systems. Roughly 90% of respondents reported that they still depend on spreadsheets in the middle and back office.
“It’s not to say that Excel is not a brilliant tool, of course it is,” Botha said. “It’s just hard to understand how this can be considered an enterprise piece of software for payments operations. The reason I say that is because the name of the game in payments. And payments firms typically make their revenues through transaction volumes.”
“Processing very high volumes of data is really where these firms start to benefit, and working off spreadsheets and legacy systems can have a lot of limitations around scalability and flexibility,” he said.
Another issue is that once many organizations reach the limits of what spreadsheets can accomplish, many create additional processes around them to close the gap. These layers of process upon process only exacerbate functions that are already manual and labor-intensive.
One reason many institutions haven’t scrapped this model entirely is that they often don’t see the value in modernizing middle- and back-office processes.
“Instead of making some investments in the software and finding something that’s a better, more efficient way of doing things, it’s just, ‘Well, let’s solve this problem so we can get this box checked,’” Wester said. “We’ll just put in another process, or we’ll bring in one other person who can now add to that process.”
“We’ve been talking about all of the things that we’re going to invest in on the user experience and the front office for so long, and so much investment goes in there,” he said. “Yet, all of these processes that are underlying all of that and that are so important for payment companies just continue to be done on spreadsheets.”
Taking Practical Steps
Although many financial institutions are lagging in payments modernization and AI adoption, organizations exist at every stage of the journey. For those just beginning, there are concrete steps to move forward.
“It’s definitely not too late to start,” Botha said. “Some of those practical steps would be educating and training resources that you have today on how these things work and where they’re going to benefit your organization. In the future, what we’re going to find is that firms are going to be hiring a lot of individuals that have this experience and expertise, but that doesn’t mean that you can’t start somewhere within your organization.”
“I did see this interview some time ago, whereby they said it’s not going to be AI that replaces people’s jobs, it’s going to be people that know how to use AI that will be replacing people’s jobs,” he said. “That sits true with me.”
In addition to more robust training programs, organizations should explore incremental AI adoption across various parts of the business. Even small integrations can add up quickly, while also giving organizations the chance to fully understand how AI will affect their operations.
Partnering can also add significant value. For many financial services firms, building AI solutions in-house may not be feasible, making it essential to identify vendors and software providers that can deliver impact.
That said, introducing more third parties and systems can create challenges of its own.
“One of the key things that we find, especially with the inclusion of AI, is the interoperability between systems and partners,” Botha said. “When you are partnering, you’re making those investments, and they are typically very large investments. Just make sure that the interoperability between your systems and processes is there.”
“If you’re buying something that’s going to solve one particular issue, but it creates three or four other issues that sit around it because it doesn’t communicate effectively between different systems and processes and different business units—it’s actually going to create more of a headache,” he said.
The Nature of AI
Many well-run financial institutions may not see the value in rushing into AI implementation. While that may not be an issue now, the game-changing potential of artificial intelligence means organizations shouldn’t dismiss it out of hand.
“AI is transformational,” Wester said. “There is a lot that AI is going to do in financial services. One of the things that financial institutions and payment companies really need to do is be deliberate in the way that they’re looking at it. Don’t just dismiss it. Don’t take a wait and see attitude, understand that this is something that’s big.”
“Put together a team of people—put together the leadership team that’s going to say, ‘OK, where can we use this and where can we derive some benefit?’” he said.
Once an organization explores the benefits, it will often find they outweigh any concerns about AI. This makes now the time to take intentional steps toward implementation.
“The key messages over the last probably 18 months have been talks of AI, crypto, stablecoins, etc.,” Botha said. “In the payment space, it’s kind of at its infancy, so don’t feel like you’re terribly far behind. I haven’t seen many firms that are completely driven by AI within the payments space.”
“I don’t think that you would be terribly far behind if you started today, but if you start in 18 months to 24 months you may be, because it might move pretty quickly. That’s the nature of what AI has to offer.”
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