The race to build the best AI model is quickly becoming less important than the race to build the best product around AI. What’s instead becoming crucial is who owns the interface, the daily engagement, and the trust that allows users to act confidently on what the system recommends.

Apple’s approach to Siri makes that shift easy to see. Rather than relying only on its own AI capabilities, Apple is partnering with Google to use Gemini models where they offer better performance, while also working with OpenAI for certain use cases.

The priority is clear: ensuring that Siri delivers a strong, reliable experience for users matters more than insisting on a single, in-house intelligence layer. If using an external model improves the product, then that's the way to go. 

Technology competition hasn’t always worked this way, though. For a long time, owning the entire stack was the safest path to differentiation.  
 
Today, even the largest platform companies are comfortable treating AI models as interchangeable components, as long as the overall product experience remains consistent. 

FinTech has always been won on experience and trust 

For the FinTech industry, this way of thinking should feel familiar. Financial products have never been won purely on the strength of algorithms and features.  

What ultimately drives adoption and retention is the experience: how easily users can complete tasks, how predictable the outcomes are, how secure the system feels, and how quickly issues are resolved when something breaks. 

Klarna offers a useful example of how this approach plays out in practice. When the company introduced its AI assistant for customer support and shopping assistance, the objective was not to showcase AI capability for its own sake. It was to address a clear friction point in how customers interacted with the platform. Since launch, the assistant has handled a large share of customer conversations, reduced response times, and supported users across markets and languages. From the user’s perspective, the improvement is experienced as faster resolution and simpler interactions, rather than as  an extra layer of technology. 

Increasingly, AI will become a default embed in workflows, but the organisations that benefit most will not be those promoting technical sophistication. They will be the ones that redesign everyday financial journeys in ways that feel simpler, faster, and more reliable for users. 

When AI moves from support to execution 

Once AI becomes part of how financial actions are executed, not just how information is presented, platforms must address a different set of operational and regulatory questions. 

If an AI assistant can help place an order, move funds, pay bills, or apply for credit, financial institutions must be able to answer basic but critical questions: 

• Was the user’s intent clearly established? 

• Were spending limits and internal policies respected? 

• How are disputes handled if the user claims an action was not intended? 

• What audit trail exists when decisions are triggered through conversational interfaces rather than structured forms? 

These are not problems that can be solved by improving language models. 

They require careful product design, strong policy frameworks, identity controls, transaction monitoring, and regulatory alignment. In other words, they depend on the parts of FinTech that aren’t glamorous but are essential to stable financial, regulated operations. 

The interface becomes part of risk and compliance 

If AI becomes the primary entry point for financial actions, the interface is no longer just a design consideration. It plays a direct role in how consent is captured, how decisions are explained, and how safeguards are applied. 

Product teams will need to shift how they think about journeys. Instead of designing linear screens and forms, teams will need to design around intent, permissions, and escalation paths. What actions can happen automatically? When should the system slow down and require confirmation? How should explanations be presented when decisions are made inside conversational flows rather than traditional application processes? 

This reinforces what FinTech has always needed to balance: convenience and control. AI increases the importance of getting that balance right, rather than reducing it. 

Distribution, infrastructure, and where advantage sits 

If users increasingly interact with financial services through AI interfaces rather than standalone apps, distribution power begins to concentrate around whoever controls those interfaces.  
 
That could be operating systems, super-apps, browsers, or other large consumer platforms. In that case, FinTech firms that do not own those entry points will need to compete on how effectively and reliably they integrate into them. 

This places a renewed emphasis on infrastructure rather than surface-level features. Well-designed APIs, real-time decision systems, high availability, and strong fraud controls become more valuable than visible AI features that users may never directly notice. 

So, when AI is discussed as a driver of transformation in fintech, the most meaningful changes are unlikely to come from institutions claiming patented AI breakthroughs. They will come from organisations that redesign financial products so that actions fit naturally into how people already communicate and make decisions. 

This isn’t going to be easy. It requires coordination across product, engineering, risk, compliance, and legal teams. But it is also where long-term competitive advantage is most likely to be built. 

What this signals for fintech strategy 

Apple’s decision to power Siri using external AI capabilities is not simply a technology partnership. It reflects a product strategy that prioritises user experience and platform consistency over ownership of every technical layer. It treats intelligence as something that can evolve behind the scenes, while the relationship with the user remains firmly within the product. 

Fintech appears to be moving in the same direction. The companies that perform best will not necessarily be those that speak most prominently about AI. They will be the ones that quietly rebuild their systems so users can complete financial actions more easily, with fewer steps, and with confidence that safeguards remain in place. 

AI capabilities will continue to improve across the ecosystem. What will differentiate platforms over time is how effectively that intelligence is translated into products that are reliable, understandable, and resilient when things do not go as planned. 

Cheers,  

Srijan Nagar
Co-founder  
FinBox