Account takeover is a fraudster’s holy grail.
John Fick, a fraud prevention expert on the Behind Enemy Lines podcast, explained recently. But what makes this attack vector so attractive to cybercriminals? And why is behavioral intelligence the right tool to stop it?
About 29% of Americans have experienced an account takeover fraud (ATO), according to a survey by Security.org—that’s roughly 77 million people. In 2023 alone, ATO fraud led to nearly $13 billion in losses, reports Javelin.
These figures make one thing clear: account takeover losses remain among the most damaging fraud threats to consumers worldwide. ATO isn’t just a cybercriminal’s holy grail—it’s a threat that consumers and financial institutions face every single day. In today’s fraud landscape, proactive ATO fraud prevention is the only way forward.
Account takeover fraud (ATO) is a type of cybercrime in which a malicious actor gains control of a legitimate user account—usually by stealing login credentials. While bank accounts are among the most valuable targets, ATO also affects social media accounts, email, messaging apps, telecom services, e-commerce platforms, and more.
Because of this wide reach, account takeover poses a threat not only to banks but to any organization that handles sensitive user data. Compromised business accounts are also on the rise, increasing the risk to both individuals and enterprises.
Today, with AI tools and credential-stuffing software readily available, attackers can automate ATO attempts at scale—testing thousands of stolen credentials across multiple platforms in a matter of minutes.
Cybercriminals use a variety of methods to gain access to user accounts. While many involve stealing login credentials, others—like session hijacking—allow attackers to take over accounts without needing a username or password. Below are the most common ATO techniques:
But why is account takeover the holy grail for fraudsters, who are willing to deploy a wide range of cunning tactics to achieve it? As with most types of fraud, the ultimate goal is financial gain—and account takeover provides a direct path to it. Once inside, attackers have countless ways to exploit the account, including:
In the Security.org survey, 35% of ATO victims reported financial losses. The median loss for personal account takeover was $180, though in many cases, the damage can be significantly higher depending on the circumstances and the amount of money in the bank account.
Money isn’t the only valuable asset in a user’s account. Many contain personally identifiable information (PII) or confidential data that can be used for extortion, identity theft, or sold on the dark web. In some cases, this information is also used to create synthetic identities for further fraud.
Around 40% of people who experienced account takeover reported identity theft as one of the consequences. The impact can be severe—ranging from the creation of fake identification documents to damaged credit scores and unauthorized loan applications.
The good news? Account takeover can be prevented—through effective measures adopted by both users and the institutions that manage their accounts.
Effective account takeover prevention starts with strong customer identity verification. Multi-factor authentication—often involving two distinct factors, as required under the EU’s Strong Customer Authentication (SCA)—has been a major step forward in protecting accounts. Still, many organizations find they need additional layers of defense to verify customer identities reliably.
Strong account security is essential to preventing ATO attacks. Some of the most effective best practices include:
While AI can help cybercriminals refine and scale their ATO attacks, it’s also a powerful ally in fraud detection—and more importantly, prevention. Artificial intelligence enables organizations to identify and stop ATOs, along with a wide range of other complex fraud threats.
AI—particularly machine learning algorithms—can analyze patterns of user behavior in real time to detect suspicious activity and potential account takeover attempts. This approach is highly effective because fraudsters may have pieces of stolen information, but they can’t truly mimic a user’s behavior and habits.
ThreatMark’s Behavioral Intelligence Platform leverages AI and behavioral data to create a powerful fraud prevention solution that enables financial institutions to detect and mitigate account takeover fraud. By focusing on behavior, institutions gain assurance that account access and transactions are being carried out by the rightful user.
The ThreatMark Platform uses machine learning to analyze hundreds of unique data points—captured through human-to-device interactions, device attributes, and account activity—to distinguish between legitimate users and fraudsters. This contextual, real-time risk monitoring spans the entire customer journey, enabling accurate and timely fraud detection.
Unlike traditional rule-based systems, this approach can detect account takeover attempts. And that’s not all: behavioral intelligence has also proven effective against APP fraud and scams, two of the fastest-growing threats facing banking customers.
The Behavioral Intelligence Platform is built to protect banking clients from threats before they materialize, preventing damage to both the customer and the bank’s reputation. This is especially important in today’s environment, where many fraud types are interconnected. Account takeover can lead to identity theft, phishing often serves as the entry point to APP fraud—the list goes on. And it all happens in real time, with instant payments firmly established in the EU and quickly catching on in the U.S.—leaving less room for error and slower fraud detection.
ATO attacks are a growing threat—but with the right fraud detection tools, they can be effectively mitigated. The challenge lies in striking the right balance: failed login attempts and unnecessary friction can frustrate users. As John Fick noted on the Behind Enemy Lines podcast, “You can’t just fight fraudsters—banking is a business. It’s customer-centric.”
To successfully combat payment fraud—especially when account credentials are at risk—while preserving a seamless experience, banks need smarter solutions. ThreatMark’s Behavioral Intelligence Platform offers exactly that—enabling real-time fraud detection without compromising user convenience.
Fraudsters are increasingly leveraging AI to streamline and scale their ATO attacks. Tools powered by artificial intelligence—especially deepfakes and automated scripting—are doing much of the “dirty work,” making it easier than ever to execute complex attacks, such as account takeover, with minimal effort.
We’re also seeing a rise in multi-pronged or hybrid attacks, where fraudsters combine multiple techniques—such as phishing, credential stuffing, and social engineering—to improve their chances of success. These layered strategies are harder to detect and block with traditional defenses.
Account takeover fraud (ATO) happens when a cybercriminal gains unauthorized access to a legitimate user’s account—often by stealing login credentials. These credentials are typically obtained through phishing scams, data breaches, credential stuffing, malware, or social engineering techniques like impersonation. Compromised accounts can include bank accounts, social media accounts, email accounts, and accounts on various other platforms.
In some cases, fraudsters don’t need credentials at all. Techniques like session hijacking or SIM swapping allow them to bypass traditional login processes entirely. Once inside the account, attackers can steal funds, access sensitive information, or use the compromised account to carry out further fraud.
AI is a powerful tool in preventing advanced fraud techniques, including account takeovers. As fraudsters turn to AI to enhance their attacks, financial institutions must do the same to stay ahead.
One of the most effective uses of AI is behavioral intelligence, which analyzes unique user patterns—like typing, movement, and session behavior—to detect anomalies. These patterns are extremely difficult for fraudsters to mimic, even with stolen credentials. By enabling real-time detection and prevention, AI helps organizations stop ATO fraud before it causes harm.
Traditional rule-based systems are no longer enough to stop account takeover fraud. Sophisticated fraudsters can easily find ways to bypass static rules without triggering alerts.
To effectively prevent account takeover (ATO), banks should implement machine learning models and behavioral biometrics. These technologies analyze how legitimate users interact with their devices—patterns that fraudsters can’t replicate, even if they have access to stolen credentials. By focusing on behavior rather than just credentials or device data, banks can detect anomalies in real time and stop fraud before it happens.