Fraudsters often employ high-activity devices to execute scaled abuse schemes like device farming and multi-accounting fraud, which can manipulate metrics and exploit promotions by generating far more interactions than typical users. Traditional detection methods, such as IP tracking and cookies, fall short as fraudsters can easily bypass them, prompting the need for advanced device intelligence. Fingerprint's platform offers a solution by creating stable, persistent visitor IDs from a myriad of device, network, and behavioral signals, allowing for effective detection even when fraudsters attempt to hide their tracks. This platform's Smart Signals provide context by distinguishing between legitimate power users and devices used for fraud, utilizing High-Activity Device Detection, Velocity Signals, and Bot Detection to identify suspicious patterns. The integration of these insights into risk scoring, manual review, and automated response workflows can help various industries tailor their defense strategies against specific types of abuse, while minimizing false positives through context-aware thresholds and progressive verification.