DataVisor, Inc

06/02/2026

Today marks an exciting new chapter for DataVisor. We’re thrilled to welcome Patrick Harr as Chief Executive Officer as we continue scaling our mission to help organizations stay ahead of rapidly evolving fraud and financial crime threats in the AI era.

Patrick is a five-time venture-backed technology CEO with a proven track record of building and scaling AI-native cybersecurity, cloud, and enterprise software businesses. Across his career, he has helped turn deep technical innovation into market-leading growth, including leading HPE Cloud’s expansion from $40 million to $800 million in annual revenue.

He joins DataVisor at a pivotal moment for the industry. AI is fundamentally reshaping both fraud attacks and fraud defense. As attackers increasingly weaponize generative and agentic AI to launch faster, more sophisticated, and previously unseen attacks, organizations need a new approach built for real-time intelligence, adaptability, and decisioning at massive scale. That’s why DataVisor was built for this moment.

As part of this next phase, Co-Founder Yinglian Xie will assume the role of President of Technology and AI, where she will continue leading DataVisor’s long-term technology vision, AI innovation, and next-generation product strategy. Co-Founder Fang Yu will also continue playing a critical leadership role in advancing our AI and product innovation.

Together, Patrick, Yinglian, and Fang bring the leadership, technical depth, and customer focus needed to define the next generation of AI-native fraud and financial crime prevention.

We’re excited for what’s ahead. Please join us in welcoming Patrick to DataVisor.

Read the announcement:

https://hubs.li/Q04jLTd70

05/26/2026

Great conversations happening this week at the Canadian Credit Union Association (CCUA) National Conference.

From AI-driven fraud and scams to the operational realities credit unions are navigating every day, one thing has stood out across conversations at Booth #68: financial crime teams are being asked to move faster, investigate smarter, and do more with increasingly connected fraud and AML challenges.

A big thank you to everyone who has stopped by to connect with the DataVisor team so far. It’s been great hearing firsthand how organizations are thinking about modernization, operational efficiency, explainable AI, and preparing for the next wave of fraud threats.

If you’re attending CCUA and haven’t connected with us yet, there’s still time. The conference continues through tomorrow. Stop by Booth #68 to meet the team and continue the conversation.

05/26/2026

Top article to read this week in .
"The banking industry is not ready for a world of AI-boosted hackers"

A strong perspective on what AI-driven asymmetry means for the future of banking security, and why the industry may be underestimating how quickly the operating model itself needs to change.

Particularly important is the discussion around:
• AI-discovered zero-day vulnerabilities
• Real-time anomaly detection across infrastructure and transactions
• The growing exposure gap between large institutions and smaller banks/credit unions
• Why information sharing frameworks must evolve at AI speed

A timely and important perspective from our visionary leader, Yinglian Xie, CEO DataVisor for anyone in banking, fraud, cybersecurity, or financial infrastructure.

05/26/2026

A great week of conversations at both Safeguard Events 2026 and Payments Canada, connecting with leaders across , , and .

At Safeguard, DataVisor hosted a Breakthru Networking Dinner that brought together attendees for thoughtful discussions around the future of financial crime prevention, operational AI, and evolving fraud threats. Representing DataVisor were Yinglian Xie, Tony Kueh, and Michael Rini.

We also had a strong presence at Payments Canada with Ryan Fifield and Vijay Parandaman, where Ryan presented on AI agents for fraud and AML. The session drew one of the more highly attended demos of the event and sparked great discussions around strategy optimization, real-time decisioning, and the growing role of AI in financial crime operations.

Some recurring themes we heard throughout the week:
- AI is moving rapidly from experimentation into operational workflows
- Fraud, scams, and AML are becoming increasingly interconnected
- Financial institutions continue to prioritize explainability and governance alongside innovation
- Teams are looking for AI that can help execute and optimize workflows, not just generate insights

Thank you to everyone who joined the discussions, sessions, and dinner conversations throughout the week.

05/26/2026

Our CEO Yinglian Xie sat down with Matt Brady on the Leading Detection Podcast this week to talk about the AI readiness gap and the asymmetry of fraud.

The reality? A rule can only catch fraud you’ve already identified. To stay ahead, financial institutions must shift from reactive rules to Unsupervised Machine Learning (UML).

Key Takeaway:
While legitimate users act as "independent variables," fraudsters operate in highly correlated, sophisticated rings. UML sifts through high-dimensional data in real-time to spot these clusters—even during the "incubation" stage before a single dollar is lost.

Check out the clip below to hear Ying explain how we’re helping the industry move beyond the "known" and start detecting the "unknown."

Plus, the role of the AI agents in closing the gap between fraudsters and the good guys.

Watch the full interview here:
https://hubs.li/Q04hV7cp0

Explore how AI is transforming fraud prevention in financial institutions, shifting from rule-based systems to real-time, AI-driven solutions. Yinglian Xie, ...

05/26/2026

What’s happening in South Africa is a strong signal for where fraud detection is heading. Sharing this for broader, global relevance.

Shoutout to Ivone Ferreira Da Silva for the transparency, and to MoData for bringing this to life in production.

Capitec’s results are hard to ignore:
• 2.1% false positive rate
• Up to 50% more suspicious activity detected
• 30–40% faster investigations

A clear example of how graph-based approaches surface what traditional systems miss, by connecting accounts, devices, and identities into a single, analyzable network.

Just as important is the operational impact, analysts focusing on high-risk entities instead of chasing disconnected alerts.

For banks across South Africa, this is a model worth paying close attention to and a conversation worth having with MoData.

05/26/2026

🎉 We’re excited to announce the launch of the industry's first conversational AI agents for fraud and AML teams.

Meet .
Vera brings a new way of working to fraud and AML teams, where you can simply ask and see it executed instantly across the entire lifecycle.

Just ask :
✅ ”Surface patterns …”
✅ ”Create an alert …”
✅ ”Suggest thresholds …”
✅ ”Test this rule …”
And Vera executes, while keeping you in full control.

combines DataVisor’s AI, data, and decisioning capabilities into a single, intuitive interface. This is the next step in how financial crime fighters operate.

Now, fraud and compliance teams can move as fast as the threats they face.
As Charles Subrt, JD, Fraud & AML Practice Director at Datos Insights, shared:
“Bringing conversational AI together with embedded ex*****on agents puts more control directly in the hands of financial crime leaders. DataVisor's approach reflects the kind of practical innovation the industry demands to keep pace with increasingly sophisticated threats.”

==
What have some of our customers already gained with DataVisor’s AI agents?
⬆️ Detection coverage: 2–3x increase
⬇️ Investigation time: 20–30x faster
⬇️ Regulatory reporting time: 90% reduction

We believe is about to fundamentally change how the world fights financial crime.

🗞️ Read more in Yahoo Finance: https://hubs.ly/Q04hT0xV0

🔗 Explore Vera: https://hubs.ly/Q04hSP8p0

05/26/2026

Is your AI strategy stuck in the "interest" phase?

Fraud and AML teams recognize the power of AI, yet many struggle to turn that potential into operational impact. It’s time to bridge the gap.

Join DataVisor for our upcoming webinar: AI Agents for Fraud & AML: A New Era of Detection and Strategy Optimization.

We’re diving into:
1. Why the "AI readiness gap" exists and how to close it.
2. Using AI Agents to automate rule creation and strategy tuning.
3. How conversational AI empowers analysts to move at lightning speed.
4. Live Demo: See DataVisor’s AI Agent in action.

Stop fighting modern threats with legacy speed. Learn how to operationalize AI and slash false positives.

🔗 Listen to the Webinar here: https://hubs.ly/Q04hS_FK0

Artificial intelligence is rapidly reshaping financial services, but many fraud and AML teams still struggle to translate AI interest into real operational impact. While leaders recognize the need to adopt AI, implementation challenges and operational complexity often slow progress.

05/26/2026

Life insurance fraud teams don't need a bouncer. You need a pit boss.

The bouncer checks IDs at the door. If the credentials seem valid, the criminal is in. After that? They can do almost anything. That’s the problem.

In “Account Takeover in Life Insurance: How AI Is Protecting Policyholders,” Pierre Isensee breaks this down clearly.

Account takeover in life insurance doesn’t look like fraud. Every step is authorized. With dormancy periods in between, every action is allowed. And that’s exactly why it works.
☑️ A seemingly valid login
☑️ A profile update
☑️ A new bank account
☑️ A surrender request
__
One example:
A dormant policy—untouched for months—with ~$200K in cash value.
A login happens. Within minutes, email and phone number are changed.
Then… nothing. The account sits quietly. Days later, payout instructions are updated. Shortly after, a $180K surrender is requested. Funds move via same-day ACH. The system flags it the next day. By then, the money is gone.

This isn’t a transaction monitoring problem. It’s a context problem.
The transaction seems legitimate, but the real signal happens earlier:
→ the login
→ the behavior
→ the timing between actions
By the time the transaction hits the system, the attack is already complete.
--
Back to the analogy. Legacy systems act like a casino bouncer. AI acts like a pit boss.
The bouncer checks your ID once.
The pit boss watches everything:
- how you move
- how you interact
- how your behavior changes over time
The bouncer asks “is this allowed?”
But the pit boss asks “does this make sense for this person?”

That shift—from rules to behavior—is what actually changes outcomes.

Because in life insurance:
- inactivity is normal
- large payouts are normal
- rare transactions are normal
So the only reliable signal is context.

If you want to go deeper, we unpacked the full ATO kill chain + detection approach in the latest content:
🎧 Listen to a 15-minute recap on the Podcast: https://hubs.li/Q04hS-Bj0
📖 Read the complete article from Pierre Isensee: https://hubs.li/Q04hSXPp0

Account takeover fraud is draining life insurers' whole life policies with accumulated cash. Learn why rules-based systems are failing, and how AI is closing the gap in real time.

05/26/2026

DataVisor Co-Founder & CPO Fang Yu shares her perspective in CPO Magazine on how AI agents can help fraud teams move from burnout to breakthrough.

Fraud programs today face a difficult reality: attacks are increasing in speed, complexity, and scale, while analysts are expected to review hundreds of alerts every day. That combination creates cognitive overload, missed signals, and ultimately analyst burnout.

As Fang writes in CPO Magazine, the solution isn’t choosing between technology and people. It’s equipping teams with the right technology to elevate how they work.

AI agents can take on repetitive tasks across the fraud lifecycle — from alert triage and rule tuning to summarizing investigations and SAR narratives — allowing analysts to focus on what humans do best: investigating complex fraud rings, identifying emerging patterns, and shaping prevention strategy.

The result is not just faster detection. It’s a shift in the role of the fraud analyst, from reactive firefighting to strategic decision-making.

Read Fang’s full article:
🔗 https://hubs.li/Q04hSQD70

For fraud and AML leaders, the solution isn’t choosing between technology and people, but rather empowering teams with the right technology. AI agents are the key to this transformation with the ability to supercharge fraud and AML teams across end-to-end workflows with human-in-the-loop control.