Jeff Scott, VP, Fraudtech Solutions at Q2 Holdings – Interview Series

Jeff Scott is the VP of Fraudtech Solutions at Q2 Holdings. With experience leading teams in organizations ranging from $4M to $6B in revenue, Jeff has built a strong track record in driving performance, increasing membership and retention, and fostering collaborative management. At Q2, he has contributed significantly by leading initiatives across fraud, security, and digital solutions, including his previous role as VP of Corporate Strategy and General Manager of Innovation.

Q2 Holdings is a leader in digital banking, providing comprehensive solutions to help financial institutions and fintech companies streamline their operations, enhance security, and drive digital transformation. The company specializes in fraud detection, digital banking, and relationship pricing, and focuses on creating strong partnerships within the financial services ecosystem to deliver innovative solutions

In this interview, Jeff Scott will discuss his transition into fintech, the evolution of fraud prevention with AI and real-time analytics, and how Q2’s integrated tools help financial institutions balance security with user experience.

You’ve held leadership roles across sectors—from aerospace manufacturing to nonprofits, and now fintech. What inspired your move into fraud prevention and the digital banking space?

Across every leadership role I’ve held—whether in aerospace, nonprofits, or fintech—one thing has remained constant: a mission-driven focus on serving communities. During my time at a financial institution, I saw firsthand how central banks and credit unions are to a community’s resilience. At Q2, our mission to strengthen communities through digital banking deeply resonates with that purpose.

Fraud is one of the biggest threats to that trust. It undermines relationships that banks work hard to build. With my background in digital banking and a passion for mission-aligned work, stepping into fraud prevention felt like a natural evolution. It’s an opportunity to protect what matters most: trust and access.

How have cyber threats evolved in recent years with the rise of real-time payments and digital banking, and what new attack vectors are most concerning today?

Fraud has gotten faster, smarter, and more targeted. With the adoption of real-time payments, the window to detect and stop fraud has shrunk dramatically. We’re seeing a surge in identity-based threats—account takeover (ATO), business email compromise (BEC), synthetic identities, and social engineering attacks—many of which now happen in real time.

What’s more, fraudsters are adapting traditional channels like checks and ACH to bypass digital defenses. According to the Federal Reserve, check fraud alone accounted for over $800M in losses in 2022 and continues to rise. It’s a reminder that financial institutions must defend both legacy and emerging rails simultaneously.

What role does AI and machine learning currently play in fraud prevention, and how do you see this evolving over the next 3–5 years?

AI and machine learning are now table stakes for modern fraud prevention. Institutions use them to detect behavioral anomalies, adapt risk rules in near real-time, and reduce false positives.

But we’re just scratching the surface. Over the next 3–5 years, I expect to see growth in behavioral biometrics, AI-powered fraud ring detection, and “explainable AI” that improves both transparency and trust with regulators and risk officers. Gen AI will also help institutions investigate and respond faster, empowering teams to focus on high-risk cases without getting buried in alerts.

How effective are real-time analytics in detecting and stopping fraud during instant digital transactions?

Real-time analytics are absolutely critical—but they’re only as effective as an institution’s ability to operationalize them. We often see a gap between intent and execution. While nearly all institutions recognize the need for real-time decisioning, fewer than half have fully implemented it across the customer lifecycle—from onboarding to transaction risk.

Barriers like data silos, outdated infrastructure, and latency continue to limit effectiveness. But for those that do implement true real-time analytics, the impact is significant: better detection, reduced losses, and improved customer trust.

Can you walk us through the types of fraud detection tools Q2 Holdings provides to its banking partners?

Q2 delivers a layered, integrated fraud defense strategy that combines our native digital banking tools with an extensible partner ecosystem—all embedded directly into user workflows.

Our native products, Patrol and Sentinel, enable real-time risk response at key moments. Patrol uses Event-Driven Validation (EDV) to verify high-risk events like logins and profile changes. Sentinel applies machine learning to flag suspicious transactions and intervene before funds leave the account.

We also provide the Centrix suite (ETMS, DTS, PIQS) to support positive pay for checks/ACH and manage Reg E dispute workflows—all tightly integrated with digital banking.

In addition, we offer partner integrations with leading fraud and identity providers like Alloy via Reseller and Innovation Studio programs—making it easy for institutions to deploy best-in-class tools natively within their platforms.

What sets us apart is our philosophy: fraud prevention should be embedded, not bolted on. That enables smarter, real-time decisions that don’t disrupt the customer experience.

How do you strike a balance between security and user experience when implementing fraud mitigation?

The idea that security and user experience are mutually exclusive is outdated. The key is adaptive fraud management—introducing friction only when risk levels require it. By tying risk decisions to specific actions and signals, institutions can tailor their controls without compromising usability.

It’s about giving banks and credit unions policy-driven flexibility. They shouldn’t have to choose between serving and protecting their account holders. The right data, at the right moment, enables both.

With fraud solutions evolving rapidly, how do financial institutions stay compliant with regulatory expectations and remain agile?

Regulatory pressure—especially around liability and reimbursement—is driving urgency. The most agile institutions are turning to orchestration platforms that allow for quick rule changes, transparent audit trails, and consolidated decisioning.

Tools like continuous authentication, adaptive analytics, and identity orchestration help strike a balance between compliance and performance. Importantly, regulatory alignment is no longer an afterthought—it’s a real-time, integrated function of modern fraud strategy.

How do you see fraud strategies shifting as payment infrastructure changes (CBDCs, open banking)?

CBDCs and open banking will multiply entry points and increase the velocity of value movement—creating new attack vectors. Institutions will need to validate identities and assess risk across more endpoints and third-party environments.

This shift will demand faster, more intelligent tooling: real-time behavioral analytics, network-based fraud detection, and stronger orchestration layers. But it will also demand collaboration—between banks, data providers, and technology partners. Fraud doesn’t stop at your border anymore, and neither should your defenses.

Given your leadership experience across sectors, how do you approach change management and alignment in fraudtech?

Change in fraudtech is constant, and alignment is everything. My approach blends mission clarity, cross-functional transparency, and front-line feedback loops.

First, get the “why” right—fraud prevention isn’t just about risk mitigation; it’s about enabling trust. Then, equip teams with shared language and KPIs so they can move together. Finally, involve the field early—customer support, fraud ops, and risk analysts often spot shifts before dashboards do.

Change management works when everyone understands what’s changing, why it matters, and how they contribute to success.

What KPIs or success metrics do you prioritize when assessing the impact of a fraud prevention program?

• A well-rounded fraud program balances effectiveness, efficiency, and customer impact. We are always evolving and strive to look at:
• Fraud loss rate (as % of volume or users)
• Detection rate by channel and fraud type
• False positive rate and user friction score
• Average time to detect and resolve incidents
• Reg E compliance turnaround time
• Analyst productivity (alerts per case closed)

More advanced programs also track prevented fraud velocity—i.e., how quickly you identify new patterns and deploy mitigation. That’s a strong leading indicator of future resilience.

Thank you for the great interview, readers who wish to learn more should visit Q2 Holdings.