Deliver safe, secure financial services with advanced geolocation

Locance combines IP location and connection analysis, browser- and app-based location, and device profiling to build a complete picture of where a transaction is really coming from. Each layer catches something the others might miss: IP intelligence flags proxies and anonymizers, device profiling detects VPNs, virtual machines, and tampered devices, and behavioral and velocity analysis surfaces bot activity or physically impossible travel patterns. When a discrepancy shows up, such as a device located in a different region than the account’s stated address, your system can trigger step-up authentication or block the transaction outright. Whether verifying the location behind a transaction or reinforcing identity checks at login, these layers help guard against risks like account takeover, which resulted in more than $15.6 billion in reported U.S. losses in 2024. That’s up from $12.7 billion in 2023, with reports rising over 36% year-over-year, according to Suspicious Activity Report filings tracked by the Federal Reserve.

Our iOS and Android SDKs bring location verification and device profiling directly into your mobile banking app, with users prompted for consent through the same OS-level privacy controls they already know. If they decline, you can block the transaction or fall back to step-up authentication. GPS, Wi-Fi, and cell tower location signals feed into the location result, providing accuracy from a few meters to a few hundred meters depending on the signals detected by the device. Our JavaScript toolkits cover web-based mobile use cases in the same way.

Yes. IP location and connection analysis is one of the core layers of our platform. We leverage a network with visibility into more than 99.9999% of active IPv4 and IPv6 addresses, identifying the geographic origin of a connection along with details like ISP, connection type, and whether a proxy, VPN, or other anonymizer is masking the true location. We don’t rely on IP location alone; it’s paired with device profiling and browser- or app-based location, so spoofing attempts that slip past one method can be caught by another.

Financial services firms can draw on four complementary verification methods: IP location and intelligence, browser-based location, mobile app-based location, and device profiling with anti-spoofing checks. That layered approach matters: banking absorbed 83% of API endpoint attacks in 2025, and 96% of financial services leaders reported at least one API security incident in the prior 12 months. This means that no single checkpoint is enough on its own. Our geolocation compliance APIs and Smart Zone geofencing add another layer of control, letting you define allowed service areas or exclusion zones, restrict cross-border activity, and tailor validation rules to jurisdictions with stricter regulatory requirements. These pieces are designed to work together as a layered defense rather than as standalone tools.

U.S. consumers reported losing more than $12.5 billion to fraud in 2024, a 25% increase over the prior year, with more than 1.1 million reports of identity theft logged through the FTC’s IdentityTheft.gov website. Geolocation helps close that gap by verifying that the person behind a transaction is actually where their account activity says they should be. Layering IP intelligence, device profiling, behavioral analytics, and real-time location data helps catch common fraud tactics like VPNs, proxies, spoofed GPS coordinates, and remote access tools before a transaction clears, reducing the risk of discovering fraud only after the damage is done.

Every transaction can be checked against geofence rules, location confidence scores, and device risk signals in real time. If a user falls outside an approved service area, uses a known high-risk connection, or shows signs of tampering, the transaction can be flagged, blocked, or routed to additional verification. The stakes are real: FinCEN assessed a $140 million civil money penalty against USAA Federal Savings Bank for willfully failing to maintain an AML program that met Bank Secrecy Act requirements. Locance gives you a defensible, auditable process for meeting requirements under regulations like the Bank Secrecy Act and the Anti-Money Laundering Act, plus the reporting and analytics your compliance team needs to document how each decision was made.

Regulatory expectations vary by jurisdiction, and enforcement has real teeth: in July 2025, OFAC settled with Interactive Brokers for $11,832,136 over more than 12,000 apparent sanctions violations tied to serving customers in sanctioned jurisdictions. Some states also impose additional fraud detection and compliance requirements on top of federal rules like the BSA and AMLA. Locance’s compliance APIs and rules engine include geofences and validation logic configurable for those requirements: restricting access only to certain states, blocking transactions from high-risk countries, or applying enhanced scrutiny based on transaction type, value, point of origination. Because the rules are configurable instead of hardcoded, they can be adjusted as regulations evolve without you having to rebuild your fraud detection stack.

Synthetic identity fraud is a growing blind spot: TransUnion found that 8.3% of all digital account-creation attempts in 2025 were suspected of fraud, the highest-risk stage across the customer lifecycle. This is part of why Locance layers several detection methods together through its Location & Identity Verification Engine. IP intelligence flags proxies and anonymizers. Browser- and app-based location provides real-time GPS, Wi-Fi, and cell tower verification. Device profiling supports risk scoring, persistent device fingerprinting, velocity analysis, and behavioral analytics; reviewing signals such as system and software versions, connection type, and mouse or keyboard usage patterns to help distinguish a legitimate customer from a bot or impostor. Each method assigns its own confidence and risk scores, so your fraud rules can weigh multiple signals instead of depending on a single data point.