TransUnion enhances Device Risk system to tackle rising virtual machine and bot‑driven fraud

TransUnion has unveiled a major upgrade to its Device Risk platform. The company says the enhanced system gives businesses far greater visibility into the trustworthiness of the devices behind online transactions. 

It’s an increasingly important signal as fraudsters adopt virtual machines, remote‑access tools and automated bots to evade detection. The launch comes amid what TransUnion describes as an “alarming” escalation in fraud, with businesses losing an estimated 7.7 percent of annual revenue or roughly $534 billion. 

Financial institutions, retailers and digital platforms often struggle to assess risk when users log in from unfamiliar or manipulated devices, making early detection difficult even when biometric or identity‑based verification is in place. “Our Device Risk solution is a game-changer for organizations facing complex fraud challenges,” says Steve Yin, global head of fraud at TransUnion. 

“Whether it’s preventing account takeover in financial services, stopping synthetic identity fraud in e-commerce or blocking automated bot attacks on digital platforms, our enhanced capabilities give businesses the intelligence and agility they need to gain a clear picture of identity and protect customers and revenue.”

The enhanced platform now supports cross‑session device identification without relying on cookies, allowing organizations to recognize devices consistently across multiple sessions and channels while remaining compliant with evolving privacy regulations. TransUnion says this approach reduces dependence on traditional tracking methods while maintaining reliable device recognition for fraud prevention.

The company has also introduced adaptive machine‑learning models that continuously retrain using confirmed fraud cases. TransUnion claims these models can improve fraud detection performance by up to 50 percent compared with static device recognition techniques, enabling organizations to adjust their strategies dynamically as fraud patterns shift.

Another major upgrade focuses on detecting anomalies and evasion tactics. The system can now identify virtualized environments, remote‑access tools and automated bot activity, while strengthening resistance to user manipulation techniques designed to disguise device characteristics. 

By making it harder for fraudsters to mask their digital footprint, TransUnion says the platform helps organizations proactively block suspicious behavior and maintain trust in digital interactions. 

Device Risk analyzes thousands of device attributes and behavioral signals in real time to generate a unique device fingerprint, evaluating integrity, behavioral patterns and environmental context before feeding those insights into its adaptive models. The platform can be integrated into existing fraud‑decisioning workflows via API, enabling instant risk assessments without disrupting customer experience. 

When paired with TransUnion’s IP Intelligence dataset, which covers 99.99 percent of IP addresses globally, the system can further reduce transaction‑level risk.

Yin said the upgraded platform is particularly important for industries where trust and security underpin customer confidence. By adding a device intelligence layer between biometrics and digital identity, TransUnion’s platform is supposed to offer strengthened identity assurance to protect users and transactions as fraud tactics continue to evolve.

Last month, TransUnion announced a new fraud detection tool that takes aim at the rise of credit washing, a practice that involves the removal of legitimate and accurate credit data from consumer profiles.

Article Topics

behavioral analysis  |  device fingerprinting  |  digital identity  |  ecommerce  |  financial services  |  fraud prevention  |  TransUnion