2026 FinTech Predictions: Insights from Michele Tucci of Credolab

We spoke with Michele Tucci, Chief Strategy Officer and Co-Founder at Credolab, a global leader in device and behavioural metadata analytics. Michele shares his predictions on how behavioural intelligence will reshape financial services, why incumbent banks face an existential challenge from challengers, and the blind spots the industry is dangerously underestimating as we head into 2026.

Over to you Michele - my questions are in bold:

What's the biggest shift you expect across financial services in 2026?

We are moving toward a state of "Invisible Banking" where automation and personalisation are so embedded that the banking process recedes into the background, leaving only the result. End-users will demand faster results with less friction. However, the flip side is immense pressure on incumbent banks. They aren't just competing with each other anymore; they are losing ground to challenger banks and the likes of Klarna or Revolut, who are successfully bringing a polished, high-speed retail experience into the banking sector. The "slice of the pie" is growing, but the incumbents' share is at risk if they cannot match that velocity.

Which emerging technology will have the most practical impact on banks and the FinTechs that support them?

Behavioral intelligence and analysis. While GenAI grabs the headlines, the practical impact in 2026 will come from technologies that can distinguish humans from bots and reliable customers from fraudsters without asking for a single document. As deepfakes and AI-driven fraud become scalable, the only reliable truth left is behavior analyzed in a sequential and seamless way. The logic is straightforward: if the input data is "good" (meaning fresh, real-time, and granular), the predictive model cannot help but be accurate. Think of this technology as a "golden filter." It uses a single, consistent stream of smartphone and behavioural biometrics metadata to expose the bots and scammers that fragmented data sources miss. By combining high-quality data with advanced analysis, we can uncover nuanced interactions: app installation patterns, typing cadence, hesitation, linear finger movements, storage levels, battery charging, and contact organisation. This will become the standard for assessing credit risk and catching fraud during onboarding. Ultimately, it shifts the focus from who the data says you are to how you behave in real-time.

What customer behaviours or expectations will most challenge banks and financial service providers?

The expectation of real trust. Customers want zero friction, but they also expect the bank to be an infallible shield against their own mistakes. This is personal for me. I recently almost fell victim to a call centre scam. It was incredibly sophisticated; the agents were knowledgeable, and their objection handling was flawless. The only red flag was the artificial pressure to make a quick decision. As someone who works in the field, I was humbled by how easily I was nearly swayed. This is the challenge for 2026: Social engineering is becoming so polished that even experts are vulnerable. Customers will expect their banks to detect these behavioural anomalies and intervene to protect them, even when the customer is the one pushing the "send" button.

What risks or blind spots do you think the industry is underestimating as we move into 2026?

There is a common saying that "banks are IT companies with a banking licence." Today, that is a dangerous misconception. While it is true that modern tools allow code to be written faster and more efficiently than ever, deployment latency is the blind spot. Producing code at speed does not mean you can deploy it at speed. Banks are notoriously slow to change due to legacy infrastructure and compliance layers. The risk in 2026 is an innovation gap: fraudsters and agile competitors move at the speed of AI, while many banks are regrettably stuck moving at the speed of internal procurement and, in some cases, legacy integration. The blind spot isn't the technology itself; it's the inability to adopt it without compromising the fundamental trust people place in the institution.

If you were advising a bank's leadership team today, what strategic priority should they focus on to stay competitive in 2026 and beyond?

Stop building what you can buy, and start mining what you already own. My advice is to extract every gram of value from the data you already possess, specifically behavioural data that often sits dormant. If you can't refine that data internally, rely on partners who do this for a living. In a year where Agentic AI can automate complex workflows, the "Build vs. Buy" debate should be settled. Buying specialised, ready-made solutions allows banks to focus on their only true differentiator: maintaining consumer trust and delivering on their capital promise. You don't need to build the engine; you just need to drive the car better than anyone else.

Thank you Michele!

You can connect with Michele on his LinkedIn Profile and find out more about the company at www.credolab.com.