How can Spur IP intelligence help prevent payment fraud?
Spur IP intelligence adds context about the infrastructure behind a transaction, including VPN usage, proxy activity, network type, geographic consistency, and historical risk indicators. These signals can be incorporated into fraud models to improve decision-making and reduce both false positives and false negatives.
Similar questions
How can organizations use Spur IP intelligence within a fraud decisioning workflow?
Many organizations incorporate Spur IP intelligence into risk-scoring models, adaptive authentication systems, transaction reviews, account creation workflows, and trust-and-safety investigations. Spur IP intelligence is most effective when combined with behavioral, device, and identity signals.
Can Spur IP intelligence help identify coordinated fraud rings?
Fraud rings frequently share infrastructure, anonymization services, proxy providers, or geographic patterns. Spur's Infrastructure-level intelligence can help uncover relationships that may not be visible when reviewing accounts individually.
How can organizations reduce false positives when using Spur IP intelligence?
Organizations should avoid making decisions based on a single signal. VPN usage, proxy detection, geographic anomalies, and infrastructure classifications are most effective when evaluated together with customer history, transaction context, and other risk indicators.
Can Spur IP intelligence distinguish between good bots and malicious automation?
Spur's IP intelligence can provide valuable context about the infrastructure behind automated activity, including whether traffic originates from known AI providers, hosting environments, VPNs, or residential proxy networks. Organizations can use this context alongside business policies to determine which automated activity should be allowed, monitored, or restricted.
Should transactions be blocked simply because a VPN is detected?
VPN usage is a risk signal, not proof of fraud. The most effective approach is to evaluate VPN usage alongside other contextual signals such as transaction history, geography, account behavior, and infrastructure characteristics before acting.
Related guides & explainers
Why Residential Proxy Classifications Can Appear on Legitimate Infrastructure
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"Client Proxies" in Spur data describes proxy-network activity Spur observed coming from an IP — it does not mean the IP is owned or operated by the listed provider.
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Spur classifications describe what was observed happening on an IP during a given window, not who owns the IP or ASN — a key distinction when investigating a classification that looks wrong.