Revolut and Monzo lead UK fintech charge, as sector grapples with AI — TFN

The UK fintech sector is a cornerstone of the UK startup sector. Flush with unicorns, from Revolut to Checkout.com to GoCardless, the UK fintech sector attracted $3.6bn in investment across 576 deals in 2024, second only behind the US, according to Innovate Finance, the industry trade body.

Fintechs span the gamut of sub-sectors, from challenger banks, BNPL, payments, money transfer, mobile wallets, investment and wealth management, to insurance apps.

UK fintechs like Monzo and Wise are a key part of the UK’s financial landscape and, along with other startups, have forced incumbent brands to launch replica-type startups. 

Meanwhile, the sector’s importance to the UK economy was underscored when Chancellor of the Exchequer Rachel Reeves tried to secure a meeting with the Bank of England, to discuss Revolut’s ambitions to become a fully authorised UK bank.

But the fintech sector is facing several challenges, notably around London’s status as a fintech hotbed and a lack of fintech IPOs.

But perhaps fintech’s most pressing challenge is how it best leverages booming GenAI technology. 

The tech has the potential to be transformative for fintech but is beset by challenges, such as being prone to hallucinations and the conundrum of how it can be integrated into fintech ecosystems.

Nick Harding, co-founder and CEO of Fifty One Degrees, which builds AI agents for fintechs, said a “transatlantic divide” in GenAI has opened up between the US and UK.

Harding said: “A transatlantic divide is defining the race for Generative AI dominance in financial services. The US currently leads in scaled, commercial implementation, while the UK excels in agile, regulatory-supported innovation.”

Harding pointed to the example of Starling Bank launching a spending tool, powered by Google’s Gemini, as an example of UK fintechs integrating cutting-edge AI tech.

He added: “While the US is winning on sheer scale, the UK is carving out a crucial role as the world’s premier testbed for specialised, next-generation financial AI.”

The challenger banks

Revolut

Revolut, valued at $45bn, is Europe’s most valuable startup and is reportedly in talks to raise $1bn, valuing it at $65bn. Revolut is well known for the velocity of its launches, be it crypto, insurance or its proposed move into private banking.

This year, Revolut’s product launches include Stocks and Shares ISAs and UK-listed Exchange-Traded Funds (ETFs), purpose-built ATMs in Spain and a mobile offering for its customers.

On the key question of AI, Revolut haș been leveraging AI in customer support. It said that in 2024 despite growing its customer base 34 per cent year-on-year, Revolut limited the increase in its customer support to five per cent. Revolut also uses generative AI to support its financial crime compliance function. 

Revolut is also launching an AI finance assistant, according to Revolut UK CEO Francesca Carlesi. The firm is still experimenting with AI technology, but “will go live shortly,” the CEO said.

Monzo

Monzo, famed for its coral-coloured cards, is valued at $5.9bn and is gearing up to launch across the EU this year. 2025 marked the year when Monzo, which has more than 13 million customers and is backed by Google, topped the annual £1 billion revenue mark.

Its product launches this year include a fully independent backup bank, a Monzo for under 16s product and, like Revolut, a move into mobile.

On the AI front, Monzo has an AI-driven self-service system that customers can use to resolve non-complex queries and tasks.

On average, customers are now able to resolve 42 per cent of simpler queries themselves, Monzo says.

Monzo has also invested in AI to tackle financial crime and fraud, using  machine learning to trigger a range of interventions. In 2025, Monzo says it prevented 2.9 times the value of unauthorised fraud compared to last year. 

Meanwhile, its CEO TS Anil has given a thumbs up to GenAI, saying the tech can have an “extraordinary” impact on financial services while he said machine learning can help stamp out financial crime.

Starling Bank

Starling Bank, which was last officially valued at £2.5bn in 2022, has more than 3.6m customers. This year Starling has beefed up its business offering with a key acquisition and is making a play in the US.

Starling is opening a US subsidiary to sell its tech infrastructure platform Engine to North America’s mid-tier banks, community banks and credit unions and is also reported to be eyeing possible US acquisitions and a potential US listing. 

Backed by Goldman Sachs and Chrysalis, Staring this year launched an AI-powered spending tool, called “Spending Intelligence”, which allows customers to ask questions about their money, such as “How much did I spend on groceries last week?” or ”How much did I donate to charity last year?” before receiving instant analysis. 

Starling says AI-generated chat summaries of customer interactions are now saving staff about 8,000 hours of administrative time every month. Starling has also rolled out Google Gemini for Workspace for its employees.

Harriet Rees, CIO at Starling, said: “Banks must look beyond the finance sector to see how customers are using technology to engage with other products and services.

“Just as app-based banking became a necessity for people who became more dependent on their phones, it’s clear that globally, the world is now being more AI literate and enabled day by day. As such, AI will become a critical differentiator for banks, with those that leverage it effectively defining what money management looks like in the AI era. 

“For AI to be considered truly transformative, we need to look to solve the problems that technology has not been able to thus far – financial literacy, financial accessibility and financial fraud to name a few. Banks who leverage AI to solve these pain points for customers will be the ones raising the bar for their customers when it comes to new features, products and experiences.”

Fintechs tap into AI mania

Checkout.com

UK payments fintech Checkout.com, last valued at around $9.35bn, says that AI spans all its product portfolio, from AI fraud protection tools to AI chatbots helping improve efficiencies.

Meron Colbeci, chief product officer, Checkout.com, said: “AI runs across our entire product portfolio at Checkout.com, and plays a central role in how we unlock value for our customers. It’s embedded in everything we do, from payment optimisation to fraud management and customer support.”

As an example, Colbeci cited Checkout’s AI-powered optimisation engine which he said uses machine learning across billions of transactions to boost approval rates in real time and reduce costs for merchants.

Another example Colbeci said was Checkout.com’s fraud detection tools, which he said leveraged AI to help stop fraud before authorisation, protecting customers from harm while its identity verification solution uses AI-powered video checks to confirm user identities in under two minutes. 

Another key area for Checkout is agentic commerce, which Colbeci says will have a “transformative” impact in payments.

He added: “We believe agentic commerce will be one of the most transformative shifts in payments. We expect AI assistants to move from product discovery to completing entire transactions, creating new consumer touchpoints and sales channels, forcing brands to engage with both humans and agents.”

GoCardless

UK payments fintech GoCardless, thought to be valued at around $1.5bn and reported to be being close to being acquired, extols the virtues of Large Language Models in helping deliver “personalisation at scale”.

Shaun Puckrin, chief product officer, GoCardless, said: “Machine learning is perfect for mining structured data for the deep insights that are needed for truly bespoke offerings, and AI provides the automation and efficiency to help organisations manage a myriad of personalised services.

“We use AI in a few different ways at GoCardless. Firstly, we’re using it to reduce repetitive, day-to-day tasks. This includes recent work we’ve done to service internal, intracompany queries more efficiently, such as automating ticket categorisation, routing, and finding answers to common questions. 

“For product development, we’re looking at how AI can accelerate the speed of design, prototyping and proof of concepts.”

Bud Financial

Founded in 2015, data intelligence platform Bud Financial, backed by HSBC and Goldman Sachs, has been an early adopter of AI, developing its own AI model for banking, which can be used by third parties.

Ed Maslaveckas, founder and CEO at Bud Financial, said: “Since around 2017, Bud has been developing its own language model for banking, which is central to our AI suite. 

“From the launch of large language models (LLMs), we have been able to combine these models to create highly personalised financial products while also ensuring security, accuracy, and accountability through our own models.”

He says Bud Financial is focused on consumer agents and banking agents.

He added: “These are designed to enable more functionality for both clients and banks. For example, on the consumer side, we are developing a generative UI.

“When a customer asks about their finances, they will not just receive a text response but potentially tailored widgets or graphs to help them better understand, monitor, or reference their finances daily, which can be added to their home screen.”

Maslaveckas said Bud was also launching its Bud.ai product, which will allow users to manage their finances, and which bank or financial institution will be able to build on top of.

Kriya

Kriya, a London-based B2B payments fintech, which is backed by investors including Northzone, Barclays and Santander, competes in the hot fintech area of embedded payments.

Co-founder and CEO Anil Stocker said Kriya leverages AI frontier models, including ChatGPT, to assist with document reviewing; content generation; and information retrieval and research. 

He adds: “Additionally, we are experimenting with AI agents to assess their potential value across different business scenarios (sales automation, software development, risk data processing, financial operations). 

“However, we do not currently use AI in customer service, as many queries require access to sensitive financial data that we prefer not to share with AI systems for privacy and compliance reasons.

“AI has made it possible to automate some scenarios that couldn’t be automated earlier.

“We are still scratching the surface of what’s capable and over the coming years we will see just how impactful AI can be to all businesses, including our own.”