US-based verification and fraud prevention company Sumsub has launched its AI Agent Verification solution that controls AI-driven automation by binding it to real, verified human identity within its know-your-agent framework and thereby helps organizations fight AI-driven fraud by ensuring only trusted AI automation can act on their behalf.

As AI agents and browser-based automation grow in popularity, businesses struggle, the company notes, to tell legitimate activity from fraud. Most platforms treat automation as inherently suspicious and block it by default.

In light of this, the company’s solution enables businesses to separate lawful, human-driven automation from malicious agent attacks by linking all activity to a verified human identity. This creates a clear line of accountability, allowing legitimate automation to operate while preventing illicit activity.

The solution treats automation as a manageable risk rather than an automatic red flag. The system first detects when activity is automated, evaluates its risk level and only applies additional checks when necessary.

In higher-risk scenarios, the solution can require a targeted liveness test to confirm that a real human is present and authorized. By doing so, it prevents deepfakes from being used in place of real users and ensures that every action is directly linked to the person responsible. The risk-based approach prevents unnecessary friction for legitimate users, while preserving strong safeguards against abuse.

The solution enables risk-based control by building on the core capabilities of the company’s full-cycle verification platform: 

• Device intelligence and bot detection – Detects when activity is automated and assesses its risk level in real time.
• Mule network prevention - Analyzes device behaviour and network-level signals beyond basic IP tracking, uncovering suspicious patterns across devices, accounts and sessions to expose coordinated mule activity before it can scale.
• Liveness verification – Confirms that a real human is present and authorizing the agent’s actions at critical moments, such as onboarding, account control changes or high-value payouts.
• Risk scoring and monitoring – Continuously evaluates behavioural and contextual signals across the customer lifecycle, so automation can be allowed, limited or challenged based on risk.

AI fraud agents are emerging as a new form of evasion, according to the company’s Identity Fraud Report 2025–2026, as identity fraud reaches unprecedented levels of sophistication, with a 180% year-on-year increase in multi-step, coordinated attacks globally in 2025.

As AI agents and browser-based agents are increasingly deployed for mass payouts and automated transactions in sectors, such as fintech, payments, e-commerce and ticketing, the report notes, automation is becoming a standard lever for efficiency and is now effectively unavoidable.

“AI agents are rapidly becoming the backbone of digital operations, yet most of today’s systems still treat them as opaque, unaccountable black boxes,” says Sumsub’s Vyacheslav Zholudev, co-founder and CTO. “With AI Agent Verification, the company is the first to bind AI agents to verified human identities at scale. Rather than attempting to blindly trust AI agents themselves, our solution focuses on verifying the humans behind them.”

Artem Popov, the company’s head of fraud prevention, adds: “Today, automation itself isn’t the problem – anonymity is. When AI agents can autonomously move money, create accounts or transact at scale without a real person behind them, fraud can almost become impossible to mitigate. AI Agent Verification changes that dynamic by requiring human accountability at the moments where automation becomes dangerous. Businesses must be assured that if an agent takes action, there is always a real, verified individual responsible for it.”