Fingerprint has launched a new proximity detection feature designed to help digital platforms identify clusters of devices operating in close physical range, aiming to reduce the growing threat of device farm-based fraud and multi-account abuse.
The company, known for its browser and device fingerprinting technology, said the new capability allows businesses to detect when multiple accounts are being accessed from devices in the same location, even when users rely on sophisticated evasion methods such as VPNs or virtual machines. Fingerprint’s system can reportedly recognize groups of devices operating in physical proximity, using metadata and behavioral patterns to signal potential fraud rings.
Device farms, which are large-scale setups of emulators or low-cost physical devices, have become a key tool for fraudsters engaged in fake engagement, bonus abuse, or automated sign-up fraud. By masking IP addresses and cycling through thousands of devices, such operations can circumvent traditional fraud defenses. Fingerprint’s new proximity detection feature is positioned as an additional layer for fraud teams to identify and act on these coordinated networks in real time.
The company’s latest release builds on a wider movement toward multi-layered fraud intelligence, as seen in the adoption of hardware-backed authentication technologies such as the AllKey Ultra FIDO platform introduced earlier this year. These advancements reflect a shift across the digital identity sector toward contextual signals that detect fraudulent activity based on behavioral and environmental data rather than static identifiers alone.
According to Fingerprint, early adopters across fintech, e-commerce, and online gaming have reported measurable improvements in fraud detection accuracy. The proximity signal integrates with the company’s existing device identification APIs and dashboards, giving security teams visibility into account clusters without compromising user privacy.
“Our goal is to make it significantly harder for bad actors to hide behind infrastructure that mimics legitimate users,” said Fingerprint CEO Dan Pinto in a company statement. He added that proximity-based detection complements device-level identification by surfacing behavioral anomalies tied to geography and network behavior.
The addition of proximity detection aligns with broader market demand for signals capable of identifying organized fraud patterns. Industry research suggests that device farm operations now contribute substantially to automated fraud attempts in customer acquisition and incentive-driven applications. The new feature, Fingerprint said, offers customers a more comprehensive view of fraud risk while remaining compatible with existing browser and mobile SDKs.
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By the Mobile ID World Editorial Team
