Q2 Holdings, a digital transformation solutions provider for financial services, has launched two new AI-powered fraud protection capabilities designed to help financial institutions detect and stop account takeover fraud in real time.
The two new tools — User Activity Monitoring (UAM) and Restricted Entitlements Mode (REM) — combine AI-enabled detection with real-time response and integrate into Q2’s existing fraud portfolio, creating a continuous account takeover protection system across the digital banking journey.
UAM uses AI-assisted behavioural detection to continuously analyse behavioural signals and identify high-risk patterns during live digital banking sessions, pairing deterministic rules with a foundation for future machine learning. REM functions as a deterministic enforcement layer that responds to high-risk signals by limiting access, adjusting permissions, or containing compromised accounts in real time. The two capabilities build on existing protections within the Q2 Digital Banking Platform, including Q2 Patrol for high-risk account actions and Q2 Sentinel for transaction monitoring and anomaly detection, forming what the company describes as a closed-loop, continuous fraud defence system.
Q2 develops digital banking and lending solutions for banks and credit unions. Its platform-first AI strategy focuses on embedding intelligence directly into digital banking workflows, and the latest additions reflect a broader industry shift away from siloed fraud tools towards unified systems that connect signals, decisioning, and enforcement.
Account takeover has evolved into a coordinated, multi-step attack spanning login, session behaviour, account changes, and transactions — a shift that has exposed significant gaps in point-in-time fraud controls. Q2’s AI-driven approach analyses signals across user behaviour, high-risk account activity, and transactions simultaneously, allowing institutions to identify threats earlier and respond more decisively before losses occur.
Q2 managing director, fraud intelligence Jeff Scott said, “Fraud no longer happens at a single point; it unfolds across the entire digital session. 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.”
First Bank VP and digital banking lead John Schulte said, “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. 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.”
IDC research director for risk, compliance and financial crime Sam Abadir said, “What is notable about Q2’s approach is the combination of behavioral signal detection with direct control over enforcement. 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.”
Copyright © 2026 FinTech Global
