FraudNet Recognized as a Sample Vendor in Gartner® Hype Cycle™ for Fraud and Financial Crime Prevention, 2026
Key Takeaways
- •FraudNet was named a Sample Vendor in the Self-Supervised Learning for Fraud Detection profile of the Gartner Hype Cycle for Fraud and Financial Crime Prevention, 2026, released on July 27, 2026.
- •The profile highlights self-supervised learning, a machine learning technique where models create training signals from unlabeled data instead of depending entirely on manually labeled examples.
- •FraudNet attributes its inclusion to sustained investment in machine learning built to adapt as fraud patterns evolve, an approach it positions at the core of real-time fraud detection and prevention.
- •FraudNet's single platform combines real-time fraud prevention, AML compliance, and KYC/KYB capabilities, aiming to protect payment integrity while reducing friction for legitimate customers.
- •A Sample Vendor designation merely cites a company as an example within a profile and involves no endorsement, rating, score, or ranking from Gartner.

FraudNet, an AI-native fraud prevention, anti-money laundering (AML) compliance and know-your-customer/know-your-business (KYC/KYB) platform, has announced that it has been recognized as a Sample Vendor in the Self-Supervised Learning for Fraud Detection profile of the Gartner® Hype Cycle™ for Fraud and Financial Crime Prevention, 2026. The report was published on July 27, 2026.
Gartner Hype Cycles are research publications that map the maturity and adoption of technologies within a specific domain, and a Sample Vendor designation places a company among the examples cited under an individual profile. Per Gartner's disclaimer, such listings do not constitute an endorsement of any vendor, product or service. The profile in which FraudNet appears covers self-supervised learning, a machine learning approach in which models generate training signals from unlabeled data rather than relying solely on manually labeled examples.
According to the company, its inclusion in the profile reflects continued investment in machine learning designed to adapt as fraud patterns change — an approach it positions at the core of real-time fraud detection and prevention.
"Fraud teams are defending against threats that look different every quarter, and they need technology that keeps pace," said Whitney Anderson, CEO and Co-Founder of FraudNet. "Our focus is helping organizations stop fraud in real time without adding friction for the people they serve, and we're grateful to the customers and team members who make that work possible."
FraudNet's AI-native platform delivers real-time fraud, risk and compliance solutions that the company said help organizations protect the integrity of payments while reducing friction for legitimate customers. The offering spans fraud prevention, AML compliance and KYC/KYB capabilities within a single platform.
For readers tracking fraud detection technology, the announcement describes a Sample Vendor listing only and does not indicate any rating, score or ranking within the report.
Readers can learn more about the report and what it covers on its page on Gartner.com. Additional information about the platform's real-time detection and prevention capabilities is available on the FraudNet website.
Gartner Disclaimer: Hype Cycle is a trademark of Gartner, Inc. and/or its affiliates. Gartner does not endorse any company, vendor, product or service depicted in its publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner publications consist of the opinions of Gartner's business and technology insights organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this publication, including any warranties of merchantability or fitness for a particular purpose.
This announcement was originally published by Global FinTech Series.