Fraud Detection - Digital Element

Beyond the IP Address: How IPC Powers Smarter Fraud Scoring

Posted on October 24, 2025October 24, 2025 by Stephanie Erbesfield

Introduction: The Rising Cost of IP-Based Fraud

Online fraud has evolved into a highly sophisticated threat, with criminals using advanced tactics such as proxies, VPNs, and rotating IP addresses to mask their activities. This level of sophistication often outpaces traditional defenses, such as blacklists and VPN detection, leading to false positives and allowing malicious actors to slip through.

Recognizing the need for deeper context in the fight against fraud, Digital Element’s Intelligent IP Characteristics (IPC) helps bridge the information gap. By enriching IP intelligence with behavioral and contextual signals, IPC transforms static data into a dynamic, real-time risk profile. This empowers businesses to identify threats earlier and with greater accuracy, all while respecting user privacy and regulatory compliance.

What Is IPC?

IP Characteristics (IPC) is not just another fraud detection tool. It’s Digital Element’s proprietary metadata that enriches IP address geolocation with unique context and behavioral insights. By analyzing patterns such as activity, location stability, movement range, and activity, IPC creates a dynamic risk profile that goes far beyond traditional IP checks.

Unlike many fraud tools, IPC delivers this intelligence without relying on personally identifiable information (PII) — helping businesses strengthen fraud detection while maintaining user privacy and regulatory compliance.

Breaking Down the Four Dimensions of IPC

Fraud detection powered by IPC evaluates four key dimensions:

Activity – How many devices connect to the same IP?

Dozens of devices on one IP address may indicate shared networks or anonymization services.
Example: A residential IP tied to one device appears normal; one tied to 150 devices in an hour likely indicates abuse.

Geolocation – How many distinct locations are associated with the IP?

Too many inconsistent locations can indicate spoofing or account sharing.
Example: An IP address associated with multiple cities or countries over the course of a month could suggest shared or anonymized usage.

Range – The distance between observed locations.

Broad, rapid jumps often reveal VPNs or proxies.
Example: An IP moving thousands of miles in minutes is almost certainly masked.

Location Persistence – How long an IP remains tied to a location.

Low persistence may signal botnets or rotating proxy infrastructure.
Example: An IP that changes cities every few minutes is unlikely to belong to a legitimate customer.

Together, these dimensions create a layered IP risk profile that helps systems distinguish between genuine users and suspicious actors.

Deterministic vs. Probabilistic Data

Not all fraud signals carry the same weight. IPC combines deterministic and probabilistic intelligence to provide a more complete picture of network behavior.

Deterministic data reflects verifiable truths — clear, measurable signals that confirm fraud or legitimacy with high certainty.

Example: If an IP address is observed in Paris and Sydney within minutes, it’s definitive evidence of manipulation.

Probabilistic data reflects patterns of likelihood — behaviors that suggest risk but aren’t absolute on their own.

Example: An IP that frequently shifts between nearby cities or shows unusually high device activity may indicate shared usage or a VPN, but it requires supporting context before labeling it as fraudulent.

By blending these two approaches, IPC helps businesses move beyond binary “safe or risky” decisions. This combination minimizes false positives — allowing legitimate users to pass through friction-free while still catching sophisticated threats early.

Why IPC Matters for Fraud Scoring

Adding Context to the IP Address

A raw IP provides limited insight. IPC enriches it with activity, persistence, and geolocation data — turning static numbers into actionable signals.

Strengthening Risk Models

Each dimension contributes a unique context:

High Activity: May initiate shared or one-to-many connections, such as mobile data networks, or the use of a proxy or VPN service.
Wide Distance Range: Reflects IP volatility, which can be flagged and checked against additional metadata, such as connection type, to detect unusual behavior.
Low Persistence: Indicates when an IP address’s location is not stable over time, potentially suggesting VPN/proxy usage or other one-to-many network connections.
Geolocation Mismatches: Highlight potential suspicious activity when observed IP locations do not align with expected patterns.

By weaving these insights into fraud scoring, businesses strike the right balance between security and seamless user experiences.

Practical Applications

Account Takeover (ATO) Prevention

If an account usually logs in from Chicago but suddenly appears in Eastern Europe with low persistence, data from IPC can help teams identify the anomalous behavior. Businesses can then trigger MFA or block the attempt.

Payment Fraud Detection

Transactions tied to IPs with abnormal activity or mismatched locations can be stopped before payment is processed, thereby reducing chargebacks and protecting revenue.

Bot and Automation Detection

Bots run credential stuffing, fake signups, and scraping campaigns. IPC’s activity, persistence, and range metrics expose non-human behavior, helping businesses block bots without frustrating real users.

Risk-Based Authentication

IPC enables adaptive security:

Low risk: A stable residential IP with consistent behavior → smooth checkout.
High risk: Sudden range jumps or mismatched geolocation → extra verification or block.

The IPC Advantage with Digital Element

Global Reach, Local Accuracy

Powered by over 350 billion unique observations from 1.1 billion devices, IPC covers 995 million active IP addresses across 243 countries, ensuring global reach with local accuracy. This scale ensures coverage while preserving local accuracy, so a legitimate customer traveling abroad isn’t penalized, while spoofing is still caught.

Seamless Integration

IPC integrates with Digital Element’s broader portfolio — including NetAcuity, Nodify, and LocID — enabling businesses to layer IP intelligence with identity resolution.

Building Trust While Fighting Fraud

Fraud prevention isn’t just about blocking threats. It’s about protecting customers while maintaining smooth experiences. IPC helps apply stronger checks only when needed, improving loyalty and safeguarding revenue.

Final Thoughts

Fraud prevention can’t rely on static IP address geolocation alone. Today’s threats demand a multidimensional approach that combines GPS-based determinism with probabilistic analysis. Intelligent IP Characteristics (IPC) delivers that balance — reducing false positives, improving customer experiences, and strengthening fraud models.

From stopping account takeovers to reducing chargebacks and detecting bots, IPC equips organizations to stay ahead of modern fraud while protecting revenue and trust.

👉 Ready to see IPC in action? Request a demo and explore how seamlessly IPC integrates into your fraud prevention strategy.

FAQs

What makes an IP address suspicious with IPC?

Unusually high activity, wide geolocation ranges, low persistence, or mismatches with user data all raise IPC’s fraud score.

Can IPC reduce payment fraud and chargebacks?

Yes. By scoring IPs in real time, IPC helps companies flag risky transactions before they’re processed — lowering chargebacks and protecting revenue.

How does IPC enhance traditional IP checks?

Instead of relying on static blacklists, IPC applies machine learning across multiple IP traits, offering higher accuracy with fewer false positives.

What are the benefits of IPC for fraud scoring?

Greater accuracy in detecting threats
Fewer false positives → less customer friction
Real-time risk assessment
Better balance between security and user experience

How do businesses implement IPC?

Implementation is straightforward. IPC can be integrated via API into existing login or checkout flows, allowing risk scores to drive security decisions — from triggering MFA prompts to automatically blocking suspicious transactions.

It’s Time to Rethink How You Treat VPN Traffic (Here’s Why)

Posted on August 8, 2025August 11, 2025 by Vinod Kashyap

When a VPN Provider Becomes the Story

In June 2023, popular VPN provider Windscribe found itself at the center of a legal firestorm. Greek authorities launched criminal proceedings against the company and its co-founder and CEO, Yegor Sak, after fraudsters used a Windscribe-owned server to gain unauthorized access to a Greek government system and send spam emails.

At the heart of the controversy was Windscribe’s strict no-logging policy, which prevented law enforcement from accessing critical user activity data during the investigation.

After a two-year legal battle, the case was dismissed earlier in 2025. However, it left behind a pressing question: how should organizations evaluate VPN traffic in a world where privacy and security often conflict?

Many organizations still rely on outdated, binary approaches: either blocking all VPN traffic or trusting it implicitly. That black-and-white mindset creates blind spots in threat models, allowing bad actors to slip through unnoticed.

It doesn’t have to be this way. With the right tools and a more nuanced mindset, organizations can adapt to today’s complex landscape. Let’s explore what Windscribe’s case revealed—and what it means for the future of VPN traffic management.

The Windscribe Case: Privacy vs. Public Safety

The Windscribe controversy underscores the growing tension between user privacy and public safety. Greek authorities treated the VPN provider as a co-conspirator because Windscribe enabled this crime to be committed using their technology and infrastructure.

Greek authorities later found out that Windscribe protected the criminals by having a “no logging policy”. This policy was in place under the guise of the “privacy” of the users.

This is why the Greek authorities ultimately lost the case. Privacy won out. But so did criminal activity using VPNs with a no-logging policy.

This raises an urgent question for businesses: How can organizations respect user privacy while also preventing fraud and malicious activity?

For security teams, the takeaway is clear: unquestioningly blocking VPN traffic is no longer a viable strategy.

Instead, organizations must analyze the context behind VPN usage to determine which connections are legitimate and which are not. This involves distinguishing between those who use a VPN solely to encrypt their traffic from others to see and those who intend to hide their malicious online behavior, which could signal a risk.

Users who rely on VPNs to encrypt their traffic are typically less concerned about the VPN provider having limited visibility, especially when safeguards are in place to prevent that data from being used for ads or other purposes. Given the choice between being blocked for using a VPN or maintaining access, most will choose a provider that protects their privacy while keeping the door open.

Malicious actors, on the other hand, intentionally avoid VPNs that log user activity. Anonymity is part of their threat model, and any traceable footprint increases their risk of detection.

This is undoubtedly a nuanced view, but the advent of special-purpose VPNs and the maturation of the internet require that cybersecurity professionals approach VPNs with a nuanced perspective.

The Flaw in Blanket VPN Policies

For years, the prevailing wisdom in cybersecurity was simple: all VPN traffic carries risk. To mitigate potential threats, many organizations either block VPN connections entirely or permit them without question. This binary approach might have been sufficient in an era when VPNs were niche tools for tech-savvy users.

But times have changed. VPNs are no longer confined to a small, tech-savvy audience. They’ve entered the public consciousness in a big way, promoted on YouTube by influencers, featured in Super Bowl commercials, and adopted by everyday users for work, streaming, and online privacy. VPNs have gone mainstream—accessible to almost anyone, even with minimal technical know-how.

This ubiquity creates new challenges. Blanket-blocking VPNs alienate legitimate users who rely on them for privacy and convenience. Yet indiscriminately trusting all VPN traffic leaves organizations vulnerable to fraudsters who deliberately choose no-log VPNs to stay untraceable.

In a world where sophisticated attackers hide in plain sight among regular traffic, security teams can no longer rely on blunt, all-or-nothing policies. The answer lies in adopting a more nuanced and context-driven approach to managing VPN traffic.

Moving Beyond Binary: Context Is the New Security Imperative

Not all VPNs present the same level of risk. Certain features—such as no-logging policies—can raise red flags, yet many organizations still fall back on the old binary mindset: either block all VPN traffic or allow it unchecked.

This is where context becomes essential. With the right intelligence, security teams can assess VPN traffic based on behavior and intent, not just broad labels like ‘VPN’ or ‘proxy’, to identify potential threats.

Nodify’s IP Characteristics database provides the insights necessary to distinguish signal from noise. Instead of blanket blocking, security professionals should:

Move beyond “block all VPNs” thinking.
Include contextual information about VPNs in decision algorithms
Weigh multiple risk signals to make smarter, defensible decisions.

Consider this scenario:

Two IP addresses attempt to access your platform.

One comes from a VPN that logs user activity.
The other uses a no-log VPN

Which one poses a greater risk?

Here’s the hard truth: bad actors don’t want to be detected. It’s jail time for them if they’re detected. Those who choose to allow a VPN to see what sites they visit and what they do on those sites are weighing their actions against the potential outcomes.

Legitimate users will opt for VPNs that protect their privacy while still allowing access, unlike bad actors, who seek total anonymity to avoid detection.

If platforms block all no-log VPNs, legitimate users may be forced to choose VPN services that do log their activity, but still maintain their privacy, while bad actors simply find new ways to stay hidden.

Proactive Security in an Evolving Threat Landscape

As VPN usage expands and threat tactics grow more sophisticated, organizations can no longer rely on static, one-size-fits-all approaches to network security. Moving beyond reactive defenses requires tools that deliver context, allowing security teams to evaluate traffic patterns, detect anomalies early, and distinguish legitimate users from bad actors.

Nodify provides a nuanced perspective on VPN and proxy traffic, enabling businesses to close critical gaps in their threat models and build smarter, more adaptive risk strategies. Its IP Characteristics database provides rich contextual insights, giving teams the data needed to track patterns such as excessive device activity, persistence, and unusual geolocation shifts, to distinguish legitimate users from potential threats.

Despite this, many organizations continue to rely on blunt strategies that either block all VPN traffic or open the door to fraudsters. By underutilizing advanced intelligence, organizations leave gaps in their defenses and risk eroding user trust.

By leveraging Nodify’s insights, security teams can transition from reactive measures to proactive fraud prevention. Its contextual IP data enables precise risk modeling, empowering teams to make smarter decisions, whether that’s flagging traffic from no-log VPNs or isolating high-risk activity across volatile IP addresses.

The internet is evolving rapidly, and so are the tactics of bad actors. To stay ahead, security strategies must evolve as well. Nodify equips your team to detect anomalies earlier, refine threat models continuously, and protect your platform without sacrificing the user experience.

All traffic isn’t equal, and it’s time your security posture reflected that.

Conclusion

To keep pace with the evolving digital landscape, organizations must reassess their approach to VPN traffic. Blanket policies, whether allowing or blocking all connections, are no longer sufficient in a world where privacy-conscious users and malicious actors often appear identical on the surface.

A smarter strategy requires context. By leveraging tools that analyze the nuances of VPN and proxy behavior, businesses can differentiate between legitimate users and suspicious activity with greater precision. This balanced approach not only strengthens defenses but also preserves the seamless user experiences that today’s customers expect.

It’s time to move beyond outdated, black-and-white thinking. The right IP intelligence helps protect your platform, preserve trust, and stay ahead of threats in an increasingly complex landscape.

Ready to take the next step? Request a free consultation today to learn how Nodify’s IP Characteristics can give your team the context it needs to make smarter, more confident security decisions.

Frequently Asked Questions

Why shouldn’t I block all VPN traffic on my website or app?

While the binary approach of blocking all VPN traffic is a straightforward way to mitigate risk, it also alienates legitimate users, such as remote employees, privacy-conscious customers, or global audiences, who rely on VPNs for secure access. A smarter approach uses advanced detection tools to evaluate connection behavior and identify which VPN traffic is truly suspicious.

How can businesses distinguish between legitimate and risky VPN traffic?

The key lies in context. By analyzing behavioral patterns—such as unusual device activity, frequent IP address changes, or volatile geolocations—modern tools can highlight potentially malicious VPN usage without disrupting trustworthy users. This nuanced approach is essential to stay ahead of fraud tactics that exploit anonymity networks.

What’s the risk of relying on outdated VPN detection strategies?

Overly simplistic approaches, like blocking all VPNs or allowing them unchecked, create blind spots. Fraudsters often hide behind no-log VPNs to evade detection, while legitimate users get caught in the crossfire. A contextual, data-driven strategy enables security teams to strengthen defenses without compromising user experience.