Entersekt CEO Says AI Can’t Change the Fundamentals of Digital Trust

Artificial intelligence has become the spark and the shield of a new security revolution in banking.

The reality of financial crime is that the same neural networks that can generate a perfect fake voice or clone a customer’s face can also be trained to detect those counterfeits faster than any human analyst. This paradox sits at the center of where instant payments can just as easily become instant fraud.

“It’s a very interesting conundrum we’re in,” Entersekt CEO Schalk Nolte told PYMNTS. “AI democratizes attack vectors. You don’t need to be a specialist anymore to do an attack.”

However, despite the noise around synthetic identities and deepfakes, Nolte said the underlying principles of digital trust have not been rewritten.

“If you take a step back, the fundamentals of authentication and security have not been impacted,” he said.

Only by pairing AI-driven insight with timeless security fundamentals, and by collaborating across institutions, can banks stay ahead of a fraud ecosystem that’s learning at machine speed, Nolte said.

What has become clear is that the rise of generative AI has flattened the technical barrier to entry, allowing anyone with a laptop to launch a phishing campaign that once required specialized code and infrastructure. That accessibility makes the speed of attacks, and of defenses, the defining variable in banking security.

It also makes collaboration indispensable as a defense multiplier. Through consortiums, banks can flag bad devices, IPs or transaction signatures before the damage spreads.

Fraud patterns repeat across institutions, Nolte said.

“Attackers hit this bank, then the next,” he said. “If you only see your own data, you might not notice the pattern.

“Normally, with the first instance, unless you have intelligence, people can get away with it,” he added. “But the second time, you can stop it. A consortium lets you avoid that first-time loss. … Having sufficient data to see the patterns is what you get if you actually partner up.”

Equally crucial to technological defenses is education, helping customers understand what banks will and won’t ask them to do.

“Somebody called a customer pretending to be from their bank,” Nolte said, giving an example. “They just asked, ‘Have you seen any funny transactions?’ The customer said yes or no and hung up. What the fraudster did was record the voice, use AI to clone it, and get past the bank’s voice-verification system.”

The attack required no stolen passwords or OTP codes, just human trust. It also underscored the need for authentication as a dynamic process rather than a static checkpoint, Nolte said.

“You can’t rely on the fact that it sounds like John on the other side,” he said. “Get two factors, get two channels. … You can use the same biometric but test other signals.”

As AI becomes more deeply integrated into authentication, it is reshaping how risk itself is measured.

“The one-size-fits-all model is broken,” Nolte said, adding that banks still relying on rigid playbooks like pushing a notification and falling back to SMS are inadvertently inviting attackers to reverse-engineer their defenses.

Instead, banks should employ dynamic orchestration, using AI to choose the right “treatment” for each risk, much like a doctor selects medication based on the diagnosis, he said.

“Antibiotics are great if you have an infection, but not so much for a headache,” Nolte said.

Entersekt’s own platform applies that logic in real time, analyzing behavioral, device and network data to decide which authentication method to deploy.

“If this is a phishing attack, deploy one mechanism; if it’s man-in-the-middle, deploy another,” Nolte said. “Our ethos from day one has been to balance [user experience (UX)] with security.”

The challenge is integration. Many financial institutions juggle multiple authentication vendors whose systems “don’t have input from each other,” he said. Without a unified view, signals become silos, and fraud slips through the cracks.

AI’s role is to connect those dots. Context turns static credentials into living profiles.

“We gather about 8.5 billion data points a year,” Nolte said, and this scale allows Entersekt’s models to learn what “normal” looks like for each individual.

“The key is to determine what is normal for John, so we can determine what is abnormal,” he said.

As AI becomes embedded in the financial fabric, its role is shifting from reaction to prediction. The next generation of authentication will blend biometrics, behavior and consortium intelligence into a self-adjusting “trust fabric” that recalibrates with every interaction, Nolte said.

He said he envisions a system that understands users not by credentials but by rhythm.

“We’ve seen you on this device doing eCommerce,” he said. “How do we use that to make banking safer and vice versa?”

The banks that thrive won’t just detect fraud faster; they’ll share intelligence faster, too.

“It remains a bigger-bullet, thicker-armor game,” Nolte said.

The future of trust belongs to those who build that armor together.

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