Q2 Holdings, Inc. has launched two new capabilities User Activity Monitoring (UAM) and Restricted Entitlements Mode (REM) to help financial institutions detect and prevent account takeover fraud in real time. With this move, the company is strengthening its fraud prevention portfolio by shifting from reactive controls to continuous, AI-powered protection across the entire digital banking journey.
To begin with, account takeover fraud has evolved into a complex, multi-stage threat that spans login activity, user behavior, account changes, and transaction execution. As a result, traditional point-in-time fraud detection tools are no longer sufficient. Recognizing this gap, Q2 has introduced a more holistic approach that continuously monitors user behavior and applies real-time enforcement to stop threats before they escalate.
Moreover, the newly launched User Activity Monitoring capability leverages AI-assisted behavioral analysis to track user actions throughout live banking sessions. By combining deterministic rules with machine learning foundations, UAM identifies suspicious patterns and high-risk signals as they occur. Consequently, banks and credit unions gain earlier visibility into potential threats.
In addition, Restricted Entitlements Mode acts as an enforcement layer that responds immediately to detected risks. When high-risk behavior is identified, REM can restrict account access, adjust permissions, or contain compromised accounts in real time. Therefore, institutions can take decisive action without waiting for manual intervention, significantly reducing the window of opportunity for fraud.
“Fraud no longer happens at a single point; it unfolds across the entire digital session,” said Jeff Scott, Managing Director of Fraud Intelligence at Q2. “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.”
Furthermore, these new capabilities integrate seamlessly with Q2’s existing fraud solutions, including Q2 Patrol for monitoring high-risk account activities and Q2 Sentinel for transaction analysis. Together, they create a closed-loop system that detects, evaluates, and interrupts fraud attempts across the full lifecycle of an attack.
Early feedback from financial institutions highlights the effectiveness of this approach. “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 John Schulte, VP and Digital Banking Lead at First Bank.
Industry experts also recognize the significance of combining detection with immediate action. “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,” said Sam Abadir, Research Director for Risk, Compliance and Financial Crime at IDC.
Ultimately, Q2’s latest innovation reflects a broader industry shift toward unified, AI-driven fraud prevention. By embedding intelligence directly into digital banking workflows, the company enables financial institutions to reduce false positives, streamline operations, and strengthen customer protection in an increasingly complex threat landscape.
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