UK Banks Dragging Their Feet on AI, as Four-in-Five say Fintech Challengers Are Racing Ahead

SaaScada research shows poor quality data, legacy tech, and regulatory uncertainty are slowing AI adoption, pushing banks towards low-risk, low-value use cases.

London, 13 November 2025 – Data-driven core banking engine, SaaScada, today released a new report – AI in Banking: Big Ambitions, Broken Foundations. The report shows that despite AI’s promise, adoption in UK banking remains lacklustre, held back by legacy technology, poor data quality and regulatory uncertainty.

Based on a survey of 150 UK banking innovation leaders, the research shows that gaps persist between AI’s potential and the reality on the ground for banks:

• Barely half of banks have deployed AI, despite its potential: While 80% of banking IT leaders think the country’s financial sector is well positioned to take advantage of AI, only 55% of UK banks have deployed AI within their business. 
• Lack of real-time access to quality data is slowing AI down: 63% say AI in finance is “going nowhere fast” without instant access to accurate transactional insights. And 79% agree that a quality data foundation is needed to keep up with AI-driven innovation.
• But legacy technology is a weight around UK banks’ ankles: 66% say trying to run AI on legacy core systems is like fuelling an EV with petrol – as outdated tech simply can’t power modern innovation – with 79% saying fintech challengers are racing ahead as a result.

“AI isn’t magic. It’s maths, data, and timing. If your systems can’t deliver the data when and where it’s needed, no amount of clever tech on top will fix it,” says Steve Round, President and Co-Founder of SaaScada. “The banks that invest in a modern core now will be the ones leading the AI revolution tomorrow. Ultimately, you can’t build the future on foundations from the past.” 

Complacence in the Absence of Compliance

While AI advances rapidly, UK banks are waiting for clarity on the scope and demands of future regulations. 63% of banking IT leaders admit the prospect of more compliance and reporting requirements puts them off using AI altogether. And 68% say regulatory uncertainty is putting AI adoption on ice, as a lack of clear rules is creating hesitation across the industry. 

73% say the AI genie is already out of the bottle, and regulators are scrambling to catch up. However, respondents were largely in favour of a considered approach from the regulators:

• 67% believe that while stricter regulation will inevitably slow adoption, it’s a price worth paying to ensure oversight, build trust, and prevent misuse. 
• 54% think the Financial Conduct Authority’s approach to AI will be effective in tackling risks like bias, inaccuracy and data privacy.

“The FCA isn’t going to reinvent the rulebook for AI and nor should it. It’ll fold AI into existing principles and judge firms on outcomes. That’s the right approach,” argues Nelson Wootton, Co-Founder and CEO, SaaScada. “The guardrails already exist, and waiting for new rules is just an excuse not to act. Banks burying their heads in the sand are missing the point – AI won’t just need compliance, it’ll assist with compliance. But only if they get their act together on data.”

UK Banks are Playing it Safe

While most respondents (81%) believe AI will have a major impact on the industry, the timing of this impact is in dispute: 32% say it is already having an impact; 28% say it will within the year, while one in five (21%) think it will take years for the industry to truly embrace AI. 

Looking at where banks are applying AI, most efforts are concentrated in low-risk, customer-facing tools, like automated savings and smart bill management. And there are clear concerns from respondents about the risk AI could introduce to their business – with the top three being:

• Data security: Higher risk of breaches and exposure
• Skills gaps: Overreliance on AI reducing human expertise 
• Bias and fairness: Discriminatory lending and credit scoring due to biased training data

On the other hand, the top three factors identified that will drive successful AI adoption in financial services were:

• Clear regulatory guidelines and alignment on data privacy
• Enhanced data quality and accessibility – standardised, real-time, and reliable
• Seamless integration with core banking platforms

“It’s Groundhog Day. A new technology comes along, and banks rush to bolt it to the front end, calling it transformation. But until they do the hard work of modernising the core, it’s just lipstick on legacy,” concludes Wootton. “If your plumbing’s broken, painting the door red won’t fix the leaky tap. The real benefits of AI will come when it’s supported by a modern, cloud-native, API-driven core. With the right architecture, data can move in real time, systems can talk to each other, and decisions can be made in the moment – not weeks later – giving banks the perfect platform to start to see tangible AI success.”