The new standard for geo-compliance and fraud prevention

Location-based fraud detection uses real-world GPS, Wi-Fi, Bluetooth, and device signals to verify that a user is physically where they claim to be. Unlike IP geolocation, which is easy to spoof with a VPN or proxy, location-based fraud detection cross-references multiple signals to confirm genuine physical presence and device integrity. 
‍

Radar Protect applies this approach to stop account takeovers, location spoofing, bonus abuse, and geo-compliance violations in real time. Because Radar works at the SDK level on iOS and Android, it captures the precise, hard-to-fake signals that server-side and IP-based tools miss.

IP geolocation estimates a user's location based on their internet connection, which is easy to manipulate using VPNs, proxies, and residential IP services. GPS-based fraud detection uses the device's actual location hardware alongside Wi-Fi, Bluetooth, and environmental signals to confirm where a user physically is. 
‍

The result is significantly more accurate and significantly harder to fake. Radar Protect combines GPS with environment fingerprinting to catch the spoofing techniques that IP-based tools from providers like MaxMind, SEON, and Sift are not designed to detect.

Radar Protect detects location spoofing by cross-referencing GPS coordinates, IP address, Wi-Fi network, device sensor data, and behavioral patterns to identify when a reported location is inconsistent with what the device is actually doing. This catches GPS spoofing apps, VPN and proxy services including residential proxies, device tampering, emulators, and device farms. Because Radar checks multiple signals simultaneously rather than relying on any single source, it catches sophisticated spoofing techniques that fool IP-only or GPS-only checks. Radar's mobile SDKs have been independently audited and certified by Gaming Labs International (GLI) for gaming use cases, and apply the same detection logic across every industry.

Radar Protect is used across any industry where location and device integrity are critical to fraud prevention and compliance. Current use cases include food delivery and ride sharing (fake couriers, spoofed pickups, bonus abuse), peer-to-peer payments and neobanks (mule accounts, impossible travel, account takeovers), gaming and betting (geo-compliance, location spoofing, bonus abuse), retail and e-commerce (promo abuse, bot operators, refund scams), and financial services (impossible travel, KYC accuracy, account integrity). Radar wins fastest where the app already uses GPS and where fraudsters depend on location spoofing and device farms.

Radar Protect adds a precise location and device signal layer that complements, rather than replaces, existing fraud tools. Platforms like Sift and SEON are built primarily on behavioral analytics, IP scoring, and device fingerprinting, signals that are increasingly easy to fake as privacy restrictions tighten and spoofing techniques grow more sophisticated. Radar fills that gap with GPS-level location accuracy, environment fingerprinting, and real-time spoofing detection that server-side tools cannot replicate. Most teams integrate Radar alongside their existing fraud stack, routing Radar's location signals into their existing rules engine or risk scoring model.