Q2 Enhances Account Takeover Protection With AI-Enabled Detection and Real-Time Response Capabilities

Q2 Holdings, Inc. , a leading provider of digital transformation solutions for financial services, announced two new capabilities—User Activity Monitoring and Restricted Entitlements Mode—that combine AI-enabled detection with real-time response, helping financial institutions detect and stop account takeover fraud. These products integrate with the existing Q2 fraud portfolio, enabling a continuous approach to account takeover protection across the digital banking journey.

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Account takeover has evolved into a coordinated, multi-step attack that spans login, session behavior, account changes, and transactions. This evolution exposes wide gaps in point-in-time fraud controls and reactive strategies against fraud. Because criminal behavior grows more sophisticated over time, banks and credit unions face increasing pressure to move beyond reactive detection toward continuous, real-time protection.

Unlike traditional fraud tools that operate at isolated moments in the end user experience, Q2’s holistic and AI-driven approach to continuous account takeover enables financial institutions to move from fragmented controls to coordinated protection. Q2’s AI-powered analysis of signals across user behavior, high-risk account activity, and transactions in real-time enables banks and credit unions to identify threats earlier and take faster, more decisive action to prevent fraud losses.

“Fraud no longer happens at a single point; it unfolds across the entire digital session,” said Q2 Managing Director, Fraud Intelligence Jeff Scott. “With this continuous approach to account takeover protection, we’re embedding intelligence directly into digital banking session workflows to help institutions shift from reactive detection to taking immediate, dynamic action before fraud occurs. Threats get stopped earlier, reducing both fraud losses and operational burden.”

Q2’s approach brings together multiple solutions embedded within the Q2 Digital Banking Platform and introduces two new capabilities that power this detection-and-response system:

• User Activity Monitoring (UAM): Uses AI-assisted behavioral detection to continuously analyze behavioral signals and identify high-risk patterns during live digital banking sessions, combining deterministic rules with a foundation for future machine learning
• Restricted Entitlement Mode (REM): Acts as a deterministic enforcement layer that applies restrictions in response to high-risk signals, limiting access, adjusting permissions, or containing compromised accounts in real time

These capabilities build on existing protections, including Q2 Patrol for high-risk account actions and Q2 Sentinel for transaction monitoring and anomaly detection. Together, they form a closed-loop, continuous fraud defense system that detects, evaluates, interrupts, and contains attacks, connecting intelligence and enforcement across the full lifecycle of account takeover.

“In just a few months of testing, we’ve seen strong signal quality from User Activity Monitoring, with more than a third of alerts aligning to confirmed fraud and a meaningful portion identifying risk we hadn’t detected elsewhere,” said First Bank VP and Digital Banking Lead John Schulte. “It’s helping us uncover high-risk activity earlier, refine our fraud strategies proactively, and collaborate more closely with Q2 to continuously improve detection accuracy. We’re especially encouraged by how this will evolve—bringing together richer data and better visibility across User Activity Monitoring and Sentinel to further strengthen our fraud monitoring capabilities.”

“What is notable about Q2’s approach is the combination of behavioral signal detection with direct control over enforcement,” said IDC Research Director for Risk, Compliance and Financial Crime Sam Abadir. “By connecting User Activity Monitoring with real-time action through Restricted Entitlements Mode, Q2 is addressing one of the more persistent challenges in fraud operations: the lag between identifying a threat and acting on it. Closing that gap within a single session, without requiring manual intervention, is what makes this model worth attention.”

This approach reflects Q2’s platform-first AI strategy—embedding intelligence directly into the workflows where digital banking occurs—while aligning with a broader shift in fraud mitigation from siloed tools to connecting signals, decisioning, and enforcement into a unified system. By applying a unified model across sessions, actions, and transactions, Q2 enables consistent, real-time decisioning that helps financial institutions reduce false positives, streamline fraud operations, and strengthen account protection.

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