Fraud Intelligence Network: Veriff’s Crosslinking — IDV’s hidden superpower

In the identity verification industry, there’s a secret weapon that most providers don’t have, and many prospects don’t even know to ask about. While legacy solutions focus on document accuracy and processing speed, Veriff has quietly built something far more powerful. Veriff Crosslinking: a real-time fraud intelligence network that no other IDV platform can match.

And recent insights from the Veriff Fraud Index highlight how urgent the industry needs this evolution. Nearly 96% of consumers worldwide have encountered fraudulent activity while using online services in the past year, and three-quarters have personally suffered a financial impact from such attacks. In particular, the report underscores the growing sophistication of fraud, with more than 78% of people targeted by AI-powered or deepfake fraud, and almost half expressing significant concern about these technologies. Against this backdrop, users increasingly demand more robust protections. Over 97% of respondents believe advanced identity verification and biometrics are crucial, especially in financial institutions and ecommerce. It’s clear: the stakes have never been higher and crosslinking has never been more important.

The power of cross-customer intelligence

Every day, fraudsters attempt to use the same stolen identities, fabricated documents, and sophisticated spoofing techniques across multiple platforms. Traditional IDV solutions treat each customer as an island; a fraudulent document that gets caught at Company A won’t be flagged when the same fraudster tries it at Company B minutes later.

Veriff’s crosslinks system changes this game entirely. Our industry crosslinks automatically share fraud intelligence across customers operating in the same industry, creating a defensive network that gets stronger with each new customer and every new verification.

Impact of crosslinking on fraud prevention

Here’s what makes this powerful: when our system detects that multiple sessions are completed by the same user, document, or device across different customers, it creates automatic links that provide early risk management  indicators. This cross-customer intelligence contributes to 2-4% of all prevented fraud – but more importantly it reduces false positive and negative rates  by 22-28%.

During a recent testing experiment where image-fingerprint crosslinking was temporarily disabled, our core system continued to outperform industry benchmarks. However, analysis showed that enabling industry crosslinks adds approximately 20% more fraud detection – demonstrating just how much additional strength cross-customer intelligence brings on top of an already market-leading solution.

Why other IDV vendors can’t replicate this

The crosslinks advantage isn’t just about technology, it’s about scale and market position. Building an effective fraud prevention consortium requires:

1. Critical mass of customers across industries

2. High transaction volumes to generate meaningful patterns

3. Diverse industry coverage to detect cross-vertical fraud attempts

4. Advanced AI systems to process and correlate massive datasets in real-time

Many platforms simply don’t have the customer base or processing volume to make cross-customer intelligence effective. It’s a network effect that strengthens with scale, and Veriff’s 2,500+ customers provide the foundation that smaller other platforms cannot match.

The compound effect of crosslinking

This is where Veriff’s advantage becomes truly compelling. Our customers include some of the world’s largest platforms – from financial services giants to major marketplaces and mobility companies. The fraud patterns we see from high-volume customers create intelligence that protects all customers in our network.

When a sophisticated fraud attempt fails at a major financial institution, that intelligence immediately strengthens fraud detection for a marketplace or gaming platform. The diverse customer base creates a compound effect where each customer benefits from the collective experience of the entire network.

Real-time fraud intelligence – how Veriff’s crosslinking consortium detects what others miss

While most identity verification providers focus on analyzing documents in isolation, Veriff operates something far more sophisticated: a real-time fraud intelligence network that sees patterns across our entire customer ecosystem. This isn’t just about better technology – it’s about fundamentally different approaches to fraud prevention that only scale can enable.

Multi-dimensional crosslinking

Veriff’s crosslinks system operates across multiple detection layers simultaneously:

Document-based intelligence

Advanced document analysis that detects signs of reuse, manipulation, or forgery through:

• Document similarity comparison across verification attempts
• Recognition of repeated or suspicious document attributes
• Detection of synthetic, altered, or fabricated identity documents
• High-precision document representations enabling forgery pattern recognition

Identity-based tracking:

Cross-identity behavioral and attribute profiling to uncover hidden links between fraudulent attempts:

• Matching personal data across platforms and customer ecosystems
• Detecting anomalous or high-risk identity attribute patterns
• Device-level behavioral analytics for identifying persistent fraud actors

Network intelligence:

Infrastructure-level insight into coordinated or repeated attack patterns:

• Monitoring for suspicious network activity and high-risk connection behaviors
• Cross-attempt correlation using device and network identifiers
• Detection of organized fraud clusters and shared risk signals

The Swiss cheese model of defense

What makes Veriff’s approach unique is the “Swiss cheese model”: multiple overlapping fraud detection systems where crosslinks work alongside velocity checks, device analysis, and behavioral patterns. When sophisticated fraudsters defeat one layer, others catch them.

Recent analysis shows that 88.19% of fraud patterns identified through crosslinks were automatically neutralized by our rules-based systems. This reflects the strength of a multilayered detection engine designed to stop patterns from reappearing – not luck, and not manual cleanup. The remaining patterns weren’t missed – they were simply captured by other automated layers, such as device intelligence, behavioral analytics, and velocity checks, which are built to handle these types of fraud signals

Speed of detection

Traditional fraud prevention is reactive: you catch fraud after it happens. Veriff’s crosslinks provide predictive intelligence. When a known fraudulent identity attempts verification with a new customer, the system provides immediate context to verification specialists during manual review.

This real-time decision support means fraudsters can’t simply “shop around” to different customers using the same stolen identity. Once caught in our network, they’re flagged across all relevant customers immediately.

Industry-specific intelligence

One of the most powerful aspects of Veriff’s consortium is industry-specific crosslinking. Fraud patterns that work in financial services might be attempted in gaming, or sophisticated document fraud in mobility might migrate to marketplaces.

Our system maintains industry crosslinks where fraud patterns detected across one customer’s verification sessions are shared with other customers in the same industry. This creates industry-specific fraud intelligence that no single company could develop alone.

The volume advantage

The effectiveness of cross-customer intelligence is directly related to transaction volume. Veriff processes has processed many millions of verifications, creating a data advantage that other reputable providers cannot match.

When a competitor processes thousands of sessions monthly, they might see a sophisticated fraud attempt once. When Veriff processes millions of sessions, we see patterns, evolution, and adaptation in fraud techniques – intelligence that benefits every customer in our network.

Multi-account detection

Perhaps most importantly, our system detects when the same fraudulent identity attempts verification across multiple clients within the same country or industry. This multi-account detection capability helps customers identify organized fraud operations that coordinate attacks across platforms.

This isn’t just about catching individual fraudsters – it’s about detecting and disrupting organized crime networks that operate across multiple platforms simultaneously.

The data advantage – why Veriff’s customer base creates unmatched fraud intelligence

In identity verification, data isn’t just about volume – it’s about variety, velocity, and the network effects that create intelligence no single customer could achieve alone. Veriff’s 2,000+ global customers across diverse industries create a fraud intelligence dataset that would be impossible for other platforms to replicate.

The scale factor

Veriff serves customers across financial services, marketplaces, mobility, gaming, and other industries globally. This diversity isn’t just impressive – it’s strategically critical. Different industries see different fraud patterns, and fraudsters often test techniques in one vertical before scaling to others.

Our customer base includes major players like Blockchain, Western Union, Deel, Monzo, Instacart, and Webull. When these large-volume customers encounter sophisticated fraud attempts, that intelligence immediately strengthens detection for smaller customers who might otherwise be vulnerable.

Cross-industry fraud pattern recognition

The reality of today’s modern fraud: it’s highly organized and systematic. Professional fraud operations don’t limit themselves to one industry. They develop techniques in one vertical and systematically apply them across others.

For example, a document forgery technique that works in financial services might be quickly adapted for gaming platforms, or a biometric spoofing method tested in marketplaces might be scaled to mobility apps. Veriff’s cross-industry customer base means we see these patterns as they emerge and spread.

The compound intelligence effect

For participating customers, every verification session adds to our fraud intelligence dataset. But when you’re processing millions of sessions across diverse industries, something powerful happens: you start seeing meta-patterns that reveal organized fraud operations.

In a recent analysis period, our crosslinks system surfaced 1,406+ additional fraud cases through cross-customer intelligence. These weren’t isolated attempts – they were coordinated patterns that only become visible when activity is connected across customers and industries.

Geographic fraud intelligence

Fraud patterns vary significantly by geography. A technique common in Eastern Europe might be rare in North America, while Latin American fraud patterns might be completely different from Asian approaches. Veriff’s global customer base across 230+ countries and territories creates geographic fraud intelligence that other competitors with more regional focus cannot match.

When a sophisticated fraud technique emerges in one region, our global network means customers worldwide benefit from that intelligence immediately. A document forgery pattern discovered in Europe instantly strengthens fraud detection for customers in North America, Asia, and elsewhere.

Volume creates pattern recognition

Here’s the key insight: pattern recognition requires more than volume – it requires connected volume. Even Tier 1 competitors processing millions of sessions a month still analyze fraud in isolation, and without a consortium they often see advanced fraud techniques only a handful of times – too few to recognize emerging patterns with confidence.

Veriff processes many millions of sessions per month, and – critically – routes that data through our industry crosslinks. That means we see the same technique repeatedly across customers and verticals, revealing its variations, evolution, and cross-platform reuse. This combination of scale and shared intelligence enables our AI to detect subtle adaptations that siloed systems simply can’t see.

The network defense advantage

The most powerful aspect of Veriff’s data advantage is that it creates a network defense effect. When one customer in our network is attacked by a sophisticated fraud operation, every other customer immediately benefits from that intelligence.

This is fundamentally different from traditional fraud prevention, where each company builds defenses in isolation. With Veriff’s consortium approach, an attack on any customer strengthens defenses for all customers.

Balanced accuracy that protects users and revenue

Veriff’s multilayered system maintains high fraud-capture rates alongside exceptionally low false rejections .

This balance is powered by diverse, real-time intelligence across millions of monthly verifications – giving our models the context needed to block sophisticated attacks without harming conversion.

Competitive moats through data

This creates what investors call “competitive moats” – advantages that become stronger over time and harder for other platforms to replicate. As Veriff’s customer base grows, our fraud intelligence becomes more comprehensive. As our fraud intelligence improves, we become more attractive to new customers. It’s a virtuous cycle that compounds our competitive advantage.

Most importantly, this advantage accelerates. For others in the industry, building a comparable data moat would take years, and even then, new entrants would be modeling yesterday’s fraud techniques while Veriff stays aligned with what’s happening right now.

Beyond individual companies – how consortium intelligence transforms industry security

The identity verification industry is at an inflection point. While fraudsters become increasingly organized, well-resourced, and collaborative, most companies still operate in silos – fighting sophisticated organized crime with fragmented, individual defenses. Veriff’s Crosslink customer consortium represents a fundamentally different approach: collective defense that matches the sophistication of modern fraud operations.

The collaboration gap in financial crime

Recent insights from Financial Crime 360 conferences reveal a stark reality: fraudsters today are organized, well-resourced, and highly collaborative – sharing data freely and exploiting new technologies like AI with alarming speed. In contrast, legitimate financial institutions still struggle with fragmented systems and limited data collaboration.

This collaboration gap creates vulnerabilities that organized crime exploits systematically. While individual companies invest heavily in fraud prevention, they’re fighting distributed, coordinated attacks with isolated, individual defenses.

Cross-company fraud operations

Modern fraud operations don’t target single companies – they execute coordinated attacks across multiple platforms simultaneously. A sophisticated identity theft operation might attempt to:

• Open accounts at multiple financial institutions
• Create profiles on various marketplaces  
• Register for mobility services
• Access gaming platforms
• Apply for multiple employment verification services

Without cross-customer intelligence, each company sees only one piece of a larger fraud operation. With Veriff’s Crosslink consortium, the entire pattern becomes visible, enabling proactive defense across all targeted platforms.

The early warning system

Veriff’s crosslinks create what amounts to an early warning system for the entire ecosystem. When a sophisticated fraud attempt is detected and blocked at one customer, that intelligence immediately flags similar attempts across other customers.

This transforms fraud prevention from reactive (catching fraud after it succeeds) to predictive (preventing fraud before it causes damage). The financial impact is significant – preventing fraud is always more cost-effective than remediating it after the fact.

Industry-specific threat intelligence

Different industries face different fraud profiles, but threats often migrate between sectors. Our consortium provides industry-specific threat intelligence that helps customers prepare for emerging fraud patterns before they become widespread problems.

For example, a document forgery technique that emerges in financial services might quickly spread to gaming platforms. Customers in the gaming industry benefit from early warning about techniques they haven’t encountered yet, enabling proactive defenses.

Breaking down information silos

The UK’s FCA (Financial Conduct Authority) is exploring ways for institutions to share “confirmed fraud” insights to strengthen collective defenses. It reflects a broader industry recognition that collaboration is essential as fraud becomes more organized and technology-driven.

Veriff is already leading in this direction. Our crosslink intelligence layer identifies meaningful connections across customer environments within existing legal and contractual frameworks, giving customers the benefits of shared insight today. It strengthens defenses proactively by delivering broader, real-time intelligence exactly when it matters.

The network effect in security

Security experts understand that network effects create exponential improvements in defense capabilities. Each new customer in Veriff’s consortium doesn’t just add their own protection – they strengthen protection for every existing customer.

This network effect means that large customers benefit from insights generated by smaller customers, and vice versa. A fraud pattern discovered at a startup might prevent significant losses at an enterprise customer. A sophisticated attack blocked at a major financial institution might protect dozens of smaller companies.

Regulatory compliance through collaboration

Increasingly, regulators expect companies to demonstrate not just individual compliance, but industry-wide collaboration in fraud prevention. Veriff’s Crosslink consortium approach helps customers meet these expectations by participating in shared defense networks.

The ability to demonstrate that your fraud prevention includes intelligence from across the industry strengthens compliance positions and reduces regulatory risk.

Speed of response to emerging threats

Fraud techniques now spread organically across online communities – one attacker’s success becomes everyone’s playbook within hours.

Consortium intelligence flips this dynamic: defenses developed in one part of the network immediately strengthen protections for all.

Building trust through transparency

One of the key themes emerging from Veriff’s research is that “transparency and cross-industry trust are the foundations of the next phase of fraud prevention.” Veriff’s Crosslink consortium embodies this principle by creating shared visibility into fraud patterns while protecting individual customer privacy.

This approach builds trust not just between Veriff and our customers, but between different industries and sectors in their collective fight against organized crime.

The future of identity verification

As fraud becomes more sophisticated and coordinated, individual company approaches become less effective. The future belongs to those that collaborate, that create shared intelligence and that drive collective defense.

Veriff’s Crosslink customer consortium is more than a current platform advantage – it represents the future of identity verification, where resilience is built on collective intelligence rather than isolated systems that can be easily targeted.

The competitive reality – why no other IDV vendor can match Veriff’s consortium advantage

After analyzing the identity verification landscape, one thing becomes clear: while every vendor claims advanced fraud detection, only Veriff operates a true customer consortium with cross-customer intelligence. This isn’t just a feature difference – it’s a fundamental structural advantage that other platforms cannot easily replicate.

A landscape filled with features, not defenses

The identity verification market is crowded, with 25+ vendors across multiple tiers:

Most focus their differentiation on familiar themes:

• Document coverage (Onfido: 2,500 documents vs Veriff’s 12,500+)
• Processing speed (various claims of automation speed)
• Geographic coverage (regional strengths in specific markets)
• Integration options (APIs, SDKs, no-code solutions)
• Pricing models (per transaction, subscription, enterprise deals)

While these dimensions matter, they’ve largely become baseline requirements in today’s IDV landscape. Document libraries, automation speed, regional coverage, and integration flexibility are essential, but they no longer determine competitive advantage.

What’s missing? Cross-customer intelligence

Notably absent from competitor materials is any form of cross-customer intelligence – no shared fraud signals, no network effects, no industry-level threat sharing.

And this isn’t an oversight; true cross-customer intelligence requires capabilities most providers simply don’t have.

Why other IDV providers can’t replicate it

Building an effective customer consortium requires five conditions few providers meet:

1. Critical mass of customers
Veriff’s 2,500+ customers generate the diversity required for meaningful pattern recognition. Vendors with a few hundred cannot match this signal density.

2. Industry diversification
Fraud patterns emerge across verticals. Veriff serves financial services, marketplaces, mobility, gaming, fintech, and more – while many other platforms cluster in narrow segments.

3. High transaction volume
Millions of monthly verifications are required to see techniques repeat often enough to identify their evolution. Lower-volume players see them too infrequently.

4. Geographic scale
Global fraud requires global intelligence. Regional IDV vendors simply can’t detect cross-border or multi-market patterns.

5. Technical infrastructure
Real-time cross-customer analysis depends on advanced AI systems and high-throughput data processing – investments many other platforms haven’t made.

The customer network advantage

Veriff’s customer roster – Blockchain, Bolt, Deel, Monzo, Starship, Trustpilot, Webull, and others – creates an unmatched ecosystem.

High-volume, high-diversity customers generate intelligence that strengthens defenses for everyone in the network.

Even a well-funded competitor starting today would need years to build comparable diversity and volume – years during which Veriff’s network continues compounding its advantage.

A network-effect moat

This is the classic flywheel:

• More customers → Better intelligence
• Better intelligence → Stronger differentiation
• Stronger differentiation → More customers
• More customers → Even stronger intelligence

This compounding cycle forms a data moat that becomes harder – not easier – for other platforms to overcome over time.

What other platforms actually compete on

Competitive analysis shows most vendors now lean on:

• Feature completeness (KYB, case management, workflows)
• Regional specialization
• Vertical focus
• Pricing strategies

But none compete on cross-customer intelligence – because they can’t. It’s not a product gap; it’s a structural one.

Why time isn’t on their side

Even if a competitor tried to build a consortium today, they’d face:

• Years to accumulate customer scale
• Limited fraud diversity during the build-up
• Difficulty selling future promises to enterprise buyers
• High technical and operational complexity

By the time they reached “critical mass,” Veriff’s advantage would have grown even further.

What this means for buyers? 

For buyers, this distinction is critical. Prospects aren’t simply choosing between similar vendors. They’re deciding between two fundamentally different approaches to fraud detection. The traditional approach analyzes each verification in isolation, leaving it blind to cross-platform fraud operations and unable to detect coordinated attacks. In contrast, Veriff’s consortium approach leverages pooled fraud intelligence across customers, industries, and regions. This enables the early detection of emerging patterns and the ability to stop coordinated attacks before they spread, offering a proactive and comprehensive defense against fraud.