In this article, intO’s Commercial Director, Chloe Amos-Edkins, reflects on the insights shared in a recent Fintech Insider podcast episode on AI in financial services. As AI adoption moves from buzz to business-critical, Chloe explores why trust, cultural context, and user understanding are essential to success. Drawing on intO’s global fintech research, she outlines how UX research can help teams design AI that’s scalable, ethical, and truly user-centred.
Generative AI is everywhere. From boardroom discussions to Friday night fintech podcasts, it seems we’re all asking the same question: Where is this going, and what does it mean for our sector?
So when I tuned in to the recent Fintech Insider episode on AI in financial services (Ep 944, Insights: The future of generative AI in financial services), I was pleasantly surprised.
The conversation—featuring Aditi Subbarao (Instabase), Colin Payne (FCA) and Fernanda Dobal (Cleo)—cut through the usual hype to offer something rarer: honesty.
🧠 AI is powerful, yes, but it’s also immature.
🔐 Trust is more important than speed.
🌎 Cultural context is make-or-break.
At Studio intO, these themes often surface in our work. As a global UX research partner to fintech brands like Google and Amazon, we see the real-world complexity that AI adoption can present. So I wanted to share a few reflections, from an insight perspective, on where things stand, and what fintech teams should be thinking about next.
A clear message from the panel: fintech is shifting from GenAI experiments to embedding AI in core processes—underwriting, onboarding, fraud detection.
This is where things get trickier.
Because AI in fintech doesn’t live in a lab. It exists in messy, emotional contexts where money is personal, trust is fragile, and cultural differences matter more than you think.
On paper, biometric verification and automation sounded ideal. But out in the wild? Our on-the-ground researchers find that users expect smart friction: visible, user-controlled security steps that signal control. Without this, trust drops, and so does adoption.
It’s no longer enough to ask, does this model work? We now have to ask, will people trust it?
And that’s not a technical question. It’s a human one.
Our global study with Amazon revealed five distinct trust profiles in payment behaviour across markets like Brazil, Japan, Germany and the US. In some regions, users expect detailed explanations behind financial decisions. In others, they simply want a smooth experience and will trust you if it just works.
If you’re building AI for global scale, you can’t assume that trust travels. You have to understand what it looks like, sounds like, and feels like in each market.
That’s where culturally attuned UX research makes all the difference.
Aditi’s analogy stuck with me: “We’re dealing with teenage AI. It’s smart. It’s brave. But it doesn’t know where the red lights are yet.”
It’s an image that will resonate with anyone building AI in fintech. The job now isn’t just to empower AI, it’s to shape it responsibly.
Yes, we need regulation (as the FCA’s Colin Payne rightly stressed). But we also need insight.
At intO, our Equitable AI Framework supports fintech teams to build fairness, transparency and accessibility into AI design—before it hits the market. Because once something has broken trust, it’s very hard to win it back.
One of the most resonant moments in the podcast, for me, was when Aditi proposed a new way to measure success in AI:
Customer Outcome ÷ Time & Effort = Real Impact
Simple, but spot on. And crucially, this is where UX research shines.
We help fintech teams define what a “successful outcome” looks like from the user’s perspective, not just the system’s. We test for emotional reassurance, perceived control, moments of hesitation. And we benchmark those outcomes across regions, channels, and cultural mindsets.
In our work with Google Wallet, this meant going beyond usability to examine payment behaviours in the context of local trust, habits and regulation. The result? Product and marketing decisions that are grounded in real user expectations.
If you’re leading AI innovation in a fintech business, here’s what our experience in the sector suggests:
Test trust early. Don’t wait for complaints, validate AI design with real users across key markets.
Embed local voices. Engage researchers who live the context, not just translate it.
Design explainability. Don’t bolt it on, make transparency part of the experience.
Balance automation with reassurance. Know when users want to hand things over, and when they want a human hand back.
Think glocal. One-size-fits-all is a risk because the planet is made up of many different places. Culturally aware design is a competitive advantage.
AI has the power to transform financial services, but only if people trust it, understand it, and see themselves in it.
That’s why UX research matters more than ever. It’s how we turn AI from something users fear, into something they value.
At Studio intO, we help fintech innovation teams future-proof their strategy with research that’s:
Want to talk about building AI your users will trust? I’d love to hear from you.
intO has just won two UK Enterprise Awards—Best Global Research Agency and the Equitable Innovation Excellence Award. Read on to learn what caught the judges' eyes, from our distributed global model and award-winning Equitable AI Framework, to the people-first culture and research that drives real-world impact. Discover how intO is setting a new standard for research in a borderless business landscape.
The best researchers know that good research doesn’t happen in isolation; the most valuable insights come from diverse perspectives, cultural awareness, and cross-disciplinary collaboration. Join us at the People of Research event in London on March 27th—a gathering of UX Researchers, Research Ops professionals, Behavioural Scientists, and others who understand the value of expanding their network beyond their immediate environment.
