Fraud prevention is increasingly challenging due to the sophisticated tactics of threat actors, prompting businesses to seek real-time, actionable device intelligence data tailored to their security needs. Fingerprint has introduced enhancements to its device intelligence platform, offering features like unified analytics, advanced data visualization, and customizable threat scoring to optimize fraud detection models and gain insights into visitor behavior. Traditional fraud detection methods often fail against VPNs, proxies, and device spoofing, but Fingerprint's approach leverages device fingerprinting to analyze browser, device, and behavior signals, transforming them into actionable insights. The platform's new features, including a customizable dashboard and Smart Signals Statistics, provide cross-platform insights and allow businesses to tailor their fraud detection models with configurable Suspect Score weights, enhancing their ability to respond to threats in real-time. By integrating advanced analytics and real-time adjustments, Fingerprint enables organizations to convert raw device data into actionable intelligence, thereby improving fraud prevention and operational efficiency.