Fingerprint, a leading provider of device intelligence for fraud prevention, has introduced Proximity Detection, a new location-based capability designed to help enterprises identify coordinated fraud operations and device farms by linking devices that operate in close physical proximity. The solution brings a powerful new layer of contextual intelligence to mobile applications that already rely on location data but have struggled to connect behavioral patterns at the device level.
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In many industries including delivery services, financial platforms, ridesharing, iGaming and social applications fraudsters have learned to exploit gaps in existing location tools by operating multiple devices from a single location. These clusters often power large-scale attacks such as multi-accounting schemes, promo abuse, bot-driven sign-ups or fraudulent gig-worker activity. By combining Fingerprint’s precise device identification with proximity insights, enterprises gain a stronger signal to detect suspicious device clusters in real time.
Proximity Detection is particularly aimed at stopping device farm activity, in which fraudsters use dozens or even hundreds of mobile devices within the same physical area. For example, fraudulent actors can create multiple gig-economy driver accounts to collect bonus incentives or generate fake passenger accounts for referral rewards. Fingerprint’s new capability correlates clustered devices and reveals coordinated behaviors that traditional tools miss, even when fraudsters attempt to mask their locations behind VPNs, spoofing or virtual environments.
To ensure privacy and compliance, Fingerprint built Proximity Detection using app-level permissions and designed the system to return only hashed proximity identifiers with ranges and confidence metrics. The solution compares zones rather than exposing personal location information, helping enterprises enforce stronger fraud defenses without compromising user privacy.
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CEO and co-founder Dan Pinto said the launch extends Fingerprint’s commitment to developing advanced signals that help fraud teams stay ahead of increasingly sophisticated attacks. He noted that Proximity Detection gives enterprises a reliable method of connecting hidden fraud behaviors while maintaining responsible data practices.
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The feature supports a wide range of high-risk industries, including fintech, banking, gig-economy platforms and online gaming markets where coordinated activity and account-level abuse have become costly challenges. With fraud schemes rapidly evolving across consumer and commercial channels, Fingerprint aims to give risk and fraud teams stronger intelligence to protect businesses from manipulation at scale.
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