Banking Infrastructure Is Ready for Its Next Chapter
The fintech SaaS model did exactly what it was supposed to do. Now the same wave of innovation it helped create is opening up something bigger for the vendors ready to move with it.
The fintech SaaS model was built on a genuinely good idea: give banks access to best in class functionality without requiring them to build and maintain it themselves. It worked, and worked well. Banks shed decades of mainframe debt, vendors grew into significant businesses, and a generation of B2B fintech companies earned strong positions by doing one thing exceptionally well. That foundation matters, and the companies that built it carry real advantages into what comes next.
What comes next looks different in the most interesting way. When Klarna eliminated over 1,200 external SaaS tools in favour of an internally built, AI powered knowledge stack, consolidating everything into a unified graph database and reporting annual savings exceeding $10 million, it was less a departure from the SaaS model and more a preview of where the market is heading.12 The opportunity for fintech vendors is to be the ones who lead that transition rather than simply observe it.
The opportunity hiding in plain sight
In my experience working with banks on technology strategy, one theme comes up consistently: banks hold far more useful institutional knowledge than they have ever been able to act on. Transactional data is well organised, well governed, and increasingly well analysed. But the knowledge that actually shapes relationships and outcomes, the notes from a client meeting, the context behind a deal, the reasoning in a compliance decision made years ago, tends to live in documents and conversations that sit outside what existing systems were designed to read. UBS tackled this directly by building an internal platform called Eliza, which brings the bank’s knowledge base into daily workflows and has been adopted by over 46,000 employees across the organisation.4 That kind of capability is increasingly what banks are looking to their vendors to help them build.
Banks have always had the knowledge. The opportunity now is making it usable, and fintech vendors are better positioned to do that than anyone.
This is one of the more compelling commercial opportunities I have seen in this space. The vendors who help banks act on that institutional knowledge will build relationships that go well beyond any individual product, creating the kind of embedded partnership that compounds in value over time.
Two capabilities that move together
Across the engagements I follow most closely, the vendors making the clearest progress are approaching AI capability and architectural flexibility as parallel workstreams rather than sequential ones. On the AI side, banks have raised their baseline expectations considerably: smarter customer interactions and predictive analytics are table stakes, and global investment in financial AI is on track to approach $200 billion by the end of 2025.5 The real differentiation comes from helping banks extract and act on the institutional knowledge they already own, surfacing it through the platforms they use every day rather than requiring a separate tool or workflow.
Architectural composability is moving at a similar pace. Banks increasingly want to select and assemble services that reflect their own operational priorities, and the core banking software market, currently valued at around $13.8 billion and forecast to grow significantly over the next decade, is being shaped by vendors who have built API first, modular platforms from the ground up.6 Vendors who have structured their platforms around interoperable components are finding they can meet banks on their own terms, which is a much stronger starting point for any strategic conversation.
Where the market is heading
The destination, as I see it, brings together the functional depth that banks relied on in previous generations of infrastructure with the flexibility and openness that modern operations demand. The table below maps the evolution.
| Platform Paradigm | Functional Coverage | Architectural Profile |
|---|---|---|
| Legacy Monoliths | Broad functional coverage | Integrated, single unit design |
| Modern SaaS Providers | Focused operational scope | Cloud native, modular bundles |
| The Destination | Full functional depth | Composable, open, AI native |
Getting there involves two phases of work that are best done with intention rather than urgency. The first is decomposing existing platforms into components that can operate independently and integrate cleanly with whatever else a bank chooses to run. The second is rebuilding on forward looking assumptions that put the bank in control of its own stack rather than dependent on any single vendor’s roadmap. Both phases reward the vendors who start early, because the compounding benefit of modularity grows with every new customer conversation.
A moment worth seizing
When I talk to banks about what they want from their technology partners over the next few years, the answer is remarkably consistent: fewer systems, better insight from data they already own, and a genuine reduction in the complexity that sits between them and their customers. That is a clear brief, and well positioned fintech vendors are genuinely equipped to answer it. The companies moving toward composability and deeper AI capability are building the kind of strategic partnerships that strengthen over time. This is one of those moments where the vendors who lean in will find themselves defining the next era of banking infrastructure, and I think that is worth moving toward with real conviction.
- Silicon.eu, AI Strategy: Klarna eliminates 1,200 SaaS services.
- PYMNTS, Klarna CEO: SaaS Companies to Consolidate Amid AI Adoption.
- Finacle, Architecture Trend 2026.
- Starburst, How Banks are Leveraging Structured and Unstructured Data for AI.
- Training the Street, The State of AI in Finance: 2025 Global Outlook.
- M2P Fintech, 10 Banking and Fintech Trends That Will Redefine 2026 and Beyond.
All articles on this site are written by me. I use AI to assist with final formatting and editing before publication.