Revolut is setting its sights on becoming a broader technology company rather than remaining just a digital bank. Chief Executive Nik Storonsky said the company is using its large stream of customer transactions to develop proprietary artificial intelligence models, while expanding into new markets and financial products. The ambition is striking: the fintech was valued at $115 billion in a secondary share sale in 2026, and now wants to use its scale and data to compete in a wider technology market.
What Revolut said about its next phase
Speaking at the Wave by Vento technology forum in Turin on October 9, 2026, Revolut CEO Nik Storonsky said the company plans to move beyond financial services and build a broader set of technology products. Reuters reported that Storonsky described the company’s daily transaction flow as a distinctive data asset for developing its own AI models.
Revolut processes around 30 million to 40 million transactions a day, according to Storonsky. He said the company had developed proprietary models using customer transaction data and techniques similar to those used to train large language models. His stated long-term ambition is for Revolut to reach a scale comparable with major US technology companies.
That is an ambition, not a promise that Revolut will immediately launch a general-purpose AI assistant or compete directly with every large technology platform. The company’s current advantage is its position inside financial activity: it can observe patterns in spending, transfers and other transactions, subject to the privacy, consent and regulatory rules that apply to its services.
Why transaction data matters for AI
AI systems are shaped by the data they can lawfully and reliably use. A company that handles millions of transactions every day may be able to identify patterns useful for fraud detection, customer support, financial insights and personalisation. For example, models may help flag unusual activity, categorise expenses or make financial tools easier to use.
But transaction data is not interchangeable with the internet-scale text used to train many general-purpose language models. Financial records are sensitive, structured and tied to real people. Turning them into useful AI requires careful handling of personal information, strong security, reliable labels and safeguards against errors. A model that misunderstands a payment or incorrectly flags a customer could cause real inconvenience or financial harm.
There is also a difference between building an internal model and offering a new AI product. Internal models can improve a company’s own services without becoming a standalone platform. A broader consumer technology business would need clear use cases, dependable performance and a reason for customers to choose it over established apps.
For Revolut, the commercial question is whether its data and customer relationships can create services that are genuinely better—not simply whether the company can train a model. Its financial footprint may offer useful context, but customers will expect transparency about how their information is used and the ability to trust decisions that affect their money.
What “beyond banking” could mean
Revolut already operates as a multi-product financial app, and expanding further could take several forms. AI-assisted money management could help customers understand spending and recurring costs. Automated support could answer routine questions faster. Business customers might benefit from tools that help reconcile payments or identify unusual transactions. The company could also apply its AI expertise to operational systems behind the scenes.
These are plausible directions for a fintech with large transaction volumes, not a confirmed product roadmap. Revolut has not, in the Reuters report, announced a specific list of new non-banking AI products or launch dates. Its broader statement is that it wants to move into technology sectors beyond its current financial services base.
Expanding into adjacent services can help a digital platform increase the value it provides to each customer. But it can also dilute focus. Every new service brings additional costs, customer expectations, competition and potentially new regulatory requirements. The company will need to decide where its data, distribution and engineering strengths offer a meaningful advantage.
Growth, regulation and trust
Revolut’s valuation rose from $45 billion in 2024 to $115 billion in a secondary share sale in 2026, according to Reuters. It has also been expanding internationally, including progress toward banking licences in the United States and licences in Britain and France. Those developments could broaden the company’s reach, although licensing and authorisation processes differ by market.
Fast growth has not been free of challenges. Reuters noted that Lithuania’s central bank fined Revolut €3.5 million in 2025 over shortcomings in transaction-monitoring controls. The company said the investigation found no confirmed instances of money laundering and that it had strengthened its systems. Reuters also reported that in September 2026 Revolut accidentally sent customer data to people posing as government investigators. The company said its systems and customer funds were unaffected.
These incidents matter especially if Revolut wants to build more AI-driven services on top of customer data. Customers and regulators will expect strict access controls, clear internal processes and careful testing. If a company uses sensitive financial data to power new services, its security and governance practices become part of the product itself.
AI can support monitoring and detection, but it cannot replace accountability. Financial firms still need people and processes to review unusual activity, correct mistakes, investigate incidents and comply with local laws. The larger the platform becomes, the more important these safeguards are.
Can a fintech become a tech giant?
Revolut’s plan reflects a broader pattern in technology: companies increasingly want to turn an existing customer relationship into a platform for many services. Financial apps have a particularly frequent connection with customers because people use them to check balances, make payments and review spending. That can create opportunities to offer additional tools without asking customers to install a completely separate app.
However, becoming a global technology company is harder than growing a successful financial app. Large technology platforms have extensive developer ecosystems, infrastructure, consumer habits and products that reinforce one another. Revolut would need to demonstrate that its non-banking services can attract sustained use and generate value beyond its core financial products.
AI may help the company build features more quickly and personalise services, but competitors can use similar technology. Long-term differentiation is likely to depend on execution: product quality, customer trust, responsible data use, international availability and the ability to maintain strong controls while expanding.
Investors will also have to distinguish between a strategic vision and measurable results. New products, adoption, customer retention, revenue contribution and operating costs will provide more useful evidence than ambitious comparisons with major technology companies alone.
Abhijeet Take
Revolut’s most interesting asset may be the frequency with which customers use it—not just its valuation. Daily financial activity can give a company useful context for building smarter money tools, fraud detection and customer support. But the same data is highly sensitive, so the opportunity comes with a higher responsibility than building an ordinary recommendation engine.
The key test is whether AI creates products customers actually need. A helpful assistant that explains spending, spots a suspicious payment or simplifies a business workflow could strengthen Revolut’s core app. Launching unrelated technology products simply to look more like a big tech company would be a much harder bet.
For now, the company has stated a broad ambition rather than a fully detailed product plan. Watch for specific launches, clear explanations of data use and evidence that new services generate real customer value. Those will show whether “beyond banking” becomes a practical business strategy or remains a headline-grabbing vision.
Frequently asked questions
What is Revolut planning?
CEO Nik Storonsky says Revolut wants to expand beyond financial services into a broader range of technology products, while developing proprietary AI models.
How many transactions does Revolut handle daily?
Storonsky told the Wave by Vento forum that the company handles around 30 million to 40 million transactions each day.
Is Revolut launching a general-purpose AI chatbot?
The Reuters report does not announce a specific general-purpose chatbot or a launch date. It describes the company’s broader ambition to develop AI and expand beyond banking.
How much is Revolut valued at?
Reuters reported that Revolut was valued at $115 billion in a secondary share sale in 2026, up from $45 billion in 2024.
What are the main risks of using transaction data for AI?
Key risks include privacy, security, inaccurate decisions, unfair outcomes and regulatory compliance. Financial data is sensitive and must be handled with strong safeguards.
Sources
Reuters — Revolut aims to become global tech company beyond banking, CEO says (October 9, 2026)
Reporting note: Potential AI use cases in this article are identified as possibilities, not confirmed product announcements. Financial and regulatory details are attributed to Reuters and the company’s reported statements.