Fingerprint has launched Proximity Detection, a new location-based signal designed to help enterprises uncover sophisticated fraud patterns by identifying mobile devices operating in close physical proximity. The feature addresses the growing challenge of device farms and coordinated multi-accounting fraud in industries like fintech, iGaming, and the gig economy.
Quick Intel
Fingerprint launches Proximity Detection to identify devices in close physical proximity.
The feature targets device farms and coordinated multi-accounting fraud on mobile platforms.
It helps link related devices, detect fraudulent clusters, and strengthen account security.
Proximity Detection uses a privacy-first approach with anonymized, hashed location data.
Key use cases include preventing bonus abuse in food delivery and detecting ATO in fintech.
The solution is available now to all Fingerprint customers.
Many mobile applications already collect location data but struggle to use it effectively for fraud prevention. Sophisticated fraud operations, such as device farms running hundreds of fake accounts, exploit this gap. Proximity Detection provides a structured signal that groups devices in the same physical area, enabling fraud teams to link seemingly unrelated accounts and uncover coordinated attacks in real time. This is critical for detecting patterns like multiple fake delivery driver accounts created from one location to claim sign-up bonuses or referral program abuse.
The new feature delivers three specific capabilities to enhance security. First, it links related devices faster by uncovering hidden multi-accounting fraud through physical proximity. Second, it detects device farms by spotting clusters of "new" accounts or devices operating from the same place, even when using VPNs or spoofing tools. Third, it strengthens account security by flagging suspicious login attempts when devices from the same location attempt to access multiple accounts, aiding in the detection of account takeover (ATO) attacks.
Built with privacy as a core principle, Proximity Detection leverages existing app-level location permissions and provides only hashed, anonymized proximity IDs in its payload. This ensures enterprises can detect fraud without compromising individual user privacy. The solution is applicable across multiple high-risk verticals: Fintech/Banking can detect ATO attempts; iGaming can reveal coordinated bonus abuse and region restriction evasion; and the Gig Economy (ride-hailing, delivery) can unveil fake driver or passenger accounts operating from a single hub.
Proximity Detection represents a strategic enhancement to Fingerprint's device intelligence platform, adding a crucial contextual layer to its identification technology. By transforming raw location data into actionable fraud signals, it empowers enterprises to preemptively disrupt large-scale, coordinated fraud operations that traditional methods often miss.
About Fingerprint
Fingerprint, powered by the most accurate device intelligence technology, enables companies to prevent fraud and improve user experiences. Fingerprint processes 100+ signals from the browser, device and network to generate a stable and persistent unique VisitorID that can be used to understand visitor behavior. With a commitment to best-in-class data security and privacy, Fingerprint is proud to be SOC 2 Type II, GDPR and CCPA compliant. Fingerprint is trusted by over 6,000 companies worldwide, including 16% of the top 500 websites, to help catch sophisticated fraudsters and personalize experiences for trusted users.
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