Next Year Could Be a Turning Point for AI in Financial Services | Bud | FF News at Money20/20 USA

Banking on AI.

At Money20/20 we spoke to Ed Maslaveckas, CEO of Bud, who shared some reliably bold insights on the transformative potential of AI in financial services.

While acknowledging the hype, he points out how it can help and adds to the growing anticipation that the technology could really add a lot of value to the industry by 2030. We also hear about the emerging role of “agentic AI,” which goes beyond recommendations to perform actions on behalf of users and the potential for fintechs to outpace traditional banks by adopting these tools.

One thing’s for sure, 2025 will be a turning point.

Maslaveckas isn’t afraid to share bold predictions as we discovered when we featured Bud in the most recent edition of The Paytech Magazine. You can read the full article here. Here he adds more insight to the current state of AI with a focus on both immediate applications and the next frontier—agentic AI.

A Balanced View on AI Hype and Reality

There’s no question that there’s a lot of hype surrounding AI, particularly generative AI, but while AI’s entry to the mainstream is exciting, Maslaveckas points out how it’s important to recognize the long-standing role of machine learning (ML) and neural networks in financial services. For example, Bud developed a transaction enrichment language model as early as 2018, demonstrating that foundational AI applications have been in play for years.

But what can’t be ignored is that there are genuinely impactful AI use cases that could have a huge impact on the banking sector. According to The McKinsey Global Institute (MGI) Gen AI could add between $200 billion and $340 billion in value annually to the global banking sector. Those use cases include personalization, segmentation, and process optimization.

In the interview above, he candidly points out that banks are fundamentally driven by numbers. AI systems excel at processing and making sense of these data-heavy operations so it’s bound to play a role. He also noted the value of AI tools in enhancing workflows, describing Bud’s data analyst product, which automates data tasks to augment human capabilities rather than replace them.

What’s Next for Agentic AI

One of the key messages here is around the distinction between “agents” and “agentic” AI models. Agents, such as today’s conversational AI, interpret user input and provide recommendations. Agentic models, however, take this a step further by performing actions on behalf of users—like transferring funds, applying for financial products, or optimising account settings.

Maslaveckas paints a vivid picture of agentic banking’s potential to revolutionise customer engagement. Bud has been making their own manoeuvres into the Agentic banking space and he discusses their own product. Imagine an AI proactively identifying better mortgage rates, optimising your credit card choices, or automating tedious admin tasks like switching service providers.

“The biggest problem in financial services is customer apathy,” Ed explained. By eliminating the friction of manual intervention, agentic AI can empower users to act on financial opportunities effortlessly.

While agentic systems could streamline workflows and reduce manual errors, their deployment comes with higher risk due to regulatory complexity. Therefore he encourages banks to embrace this paradigm while acknowledging that fintech companies might be faster to adapt and capitalize on agentic capabilities.

The Competitive Landscape: Banks vs. Fintechs

Drawing parallels to the rise of neobanks like Monzo and Revolut, Maslaveckas also suggests that agentic AI could catalyze a similar wave of disruption in the Gen AI space. Fintechs, with their agility and innovation, may outpace traditional banks in adopting these tools, particularly as data becomes the linchpin of competitive advantage. He praised open banking frameworks in the UK, like app-to-app consent flows, for making data sharing seamless and fostering trust.

However, he also noted that the U.S. market’s distinct dynamics could drive even faster innovation. Unlike the UK, where financial engagement tends to lag, U.S. customers are more proactive. Combined with the presence of tech giants like Google and a robust ecosystem of data companies, the U.S. might soon leap ahead in delivering cutting-edge AI experiences.

We also get some important thoughts on the disconnect between AI advancements and regulatory frameworks. Financial services operate under stringent compliance requirements, which can slow down AI adoption.

A Transformative Year Ahead

Bud has come a long way and Maslaveckas describes how far the industry has come and how pivotal AI could be in its future. “Everyone’s tooling up,” he remarks, adding that while commercial outcomes may not yet be clear, the foundational work being done today will pay dividends in the years to come.

As Bud continues to innovate in agentic AI, Ed remains optimistic about its ability to transform not only customer experiences but also the operational fabric of banks. The big question, he concluded, is whether traditional institutions can move fast enough to stay competitive—or whether fintechs will seize the opportunity to lead the next era of banking.

There’s no doubt in his mind that AI is not just a trend – it will revolutionise the future of financial services.