<div id="readability-page-1"><div><p>TransUnion has introduced a major advancement to its Device Risk solution, delivering next-level capabilities that redefine how businesses combat fraud. This breakthrough empowers organizations to identify risky devices with unprecedented precision, uncover hidden anomalies, and dynamically optimize fraud strategies in real time--hel helping them stay ahead of increasingly sophisticated threats. The enhancements come as fraud continues to escalate at an alarming pace, costing businesses an average of 7.7% of annual revenue--totaling $534 billion.</p><p>As fraudsters deploy increasingly sophisticated tactics, businesses need advanced tools to protect their customers and revenue. Devices with risky attributes, suspicious histories or questionable associations often drive fraud losses. Financial institutions including lenders, retail banks, fintechs, and others, struggle to identify new or familiar devices that match known fraud patterns, making early detection a persistent challenge.</p><p>Key enhancements to Device Risk include: Cross-session device identification: Recognize and track devices across multiple sessions and platforms without relying on cookies, ensuring consistent identification even as privacy regulations evolve. This approach reduces dependence on cookies while maintaining strong compliance with privacy standards and delivering reliable device recognition for fraud prevention. Adaptive Machine Learning (ML): Leverage advanced ML models and dynamic rule strategies that deliver significant performance improvements, boosting fraud detection rates by up to 50% compared to static device recognition alone.</p><p>These models continuously adapt to evolving fraud patterns and incorporate feedback from confirmed fraud cases, ensuring defenses remain agile and effective over time. Advanced Anomaly and Evasion Detection: Detect and flag virtual environments, remote access tools, and automated bot activity while strengthening resistance to user manipulation techniques. By making it harder for fraudsters to bypass detection, this capability helps organizations proactively block suspicious behaviors and maintain trust in digital interactions.</p><p>Device Risk analyzes thousands of device attributes and behavioral signals in real time to generate a unique device fingerprint. It evaluates key risk indicators, including device integrity, behavioral patterns and environmental context. By combining these insights with adaptive machine learning, Device Risk continuously refines risk scoring and fraud detection strategies.</p><p>Businesses can integrate the solution into existing workflows via APIs, enabling instant decisions and seamless customer experiences. When used in conjunction with TransUnion's IP Intelligence, the authoritative source of IP decisioning data on 99.99% of IP addresses worldwide, customers can even further reduce potential risk for each transaction.</p></div></div>

<p>TransUnion 已增强其设备风险解决方案，以更好地打击欺诈，提供识别风险设备和优化欺诈策略的先进能力。主要改进包括跨会话设备识别、自适应机器学习和高级异常检测。这些增强旨在减少欺诈损失，欺诈每年给企业造成 7.7% 的收入损失。该解决方案通过 API 与现有工作流程集成，并可以与 TransUnion 的 IP Intelligence 一起使用，以进一步降低风险</p>

TRANSUNION 推出下一代设备风险解决方案的增强功能，以应对不断上升的欺诈损失