AI agents aren’t just answering questions or setting reminders anymore. They’re booking flights, ordering groceries, and spending money for you. And while that’s convenient, it also creates a new kind of mess for fraud teams. A purchase can come from anywhere, at any hour, and look completely out of the ordinary – even when everything’s fine.
An AI might book a hotel in Tokyo while you’re asleep in Boston. It might order a birthday gift for your mother because you told it to three weeks ago. None of that fits the traditional fraud model.
Financial systems were built to detect anomalies based on human behavior. But agentic AI doesn’t behave like a person. It follows instructions, adapts quickly, and doesn’t always make it clear why it did what it did.
So how do you know if a purchase came from a trusted AI agent, a helpful family member, or a criminal? You can’t rely on behavior anymore. You have to focus on consent.
This article explores how agentic AI is changing user authentication, why traditional fraud models fall short, and what it means to build trust in a world where people aren’t always the ones pressing “Buy.”
Why Old-School Fraud Models No Longer Work
Fraud detection used to rely on patterns. If someone bought gas in Virginia and then a guitar in Montreal ten minutes later, the system flagged it. That kind of logic worked when purchases followed a predictable rhythm tied to one person, one device, one location.
But that world is gone.
You might ask your son to buy the guitar using your card while you’re on a road trip. Or an AI agent might order your groceries while you’re at work. To older fraud models, those actions look risky. But they aren’t. They’re just modern life.
This is why agentic AI complicates fraud detection. It can act fast, operate in multiple places, and behave in ways that humans wouldn’t – often with your permission. Pattern-based models can’t keep up. They don’t account for delegation, shared accounts, or AI-driven autonomy.
Even companies like Mastercard are rethinking their entire approach to fraud. Because guessing based on behavior is no longer enough when the rules of behavior itself have changed.
The Rise of AI Agents – and the Confusion They Cause
AI agents don’t impersonate people – they act on their behalf. But to most fraud detection systems, that nuance doesn’t matter. A transaction that doesn’t “look human” gets flagged as suspicious, even if it’s legitimate.
That creates friction for users and confusion for security teams. If an AI books your flight or orders your lunch, who is really behind the purchase? The AI? You? Both?
This raises a deeper challenge: How do we authenticate a transaction when the person isn’t the one doing the clicking?
Some companies are starting to take that question seriously. Okta, for example, is exploring new ways to identify and manage AI agents – not just human users. That includes tracking agent behavior, verifying its ties to a specific person, and creating boundaries around what it can do.
The goal isn’t to block AI. It’s to recognize when it’s acting with permission – and when it’s not.
A Different Path: Ask the Real Person
Most fraud systems try to guess whether a transaction is legit based on behavior – where it happens, how fast, what device. But with AI agents, those patterns fall apart. A bot might order takeout while you’re in a meeting or pay a bill while you’re asleep. That doesn’t mean something’s wrong – it just means the system needs a better way to verify.
Unibeam skips the guessing. When something happens, it asks the only person who really knows: the account owner. A quick prompt goes straight to their device. One tap confirms or denies the action.
That consent isn’t tied to a password or some network fingerprint. It’s tied to the device in your hand – the one thing that always goes with you. No assumptions, no behavioral math.
The result? A system that fits how people live now. Even with bots in the picture, you’re still the one in charge.
Rethinking Identity and Trust in a Bot-Driven World
AI agents now handle all kinds of tasks – booking travel, paying bills, running errands. That means identity isn’t just about proving it’s you. It’s about knowing when something is acting on your behalf – and making sure it has your okay.
We need tools that go beyond spotting suspicious behavior. They need to understand delegation. Who set the rules? Who approved the action? Who’s responsible if something goes wrong?
Consent becomes the anchor. If a bot acts with permission, that’s very different from acting on its own. Unibeam’s approach treats consent as the source of truth, tied directly to the person’s device. No guesswork, no complex modeling.
Agentic AI changes how transactions happen. Old methods try to predict. New methods just ask. And in a world where bots press the buttons, giving people control over what happens next isn’t just safer – it’s the only thing that builds real trust.
