Fight Synthetic Business Fraud With Layered Verification

With realistic entities manifesting out of thin air, synthetic business fraud is a far cry from the traditional fraud that has burdened the global economy for decades.

As fraud tactics evolve, bad actors are setting up fake companies or impersonating real ones to open fraudulent accounts, access credit and launder money. The rise of artificial intelligence (AI) is making it increasingly difficult to distinguish synthetic businesses from real ones.

“Traditional fraud is all about identity theft and the misuse of those stolen identities,” said Mayank Sarkar, Trulioo senior product manager. “Synthetic business fraud is different. It involves the medicalese creation of entirely fictitious entities. Bad actors will skillfully combine elements of real data that is stolen or has been compromised, and combine that with entirely fabricated information, resulting in a business profile that looks completely authentic on the surface and very difficult to detect using traditional checks.”

Sarkar joined Mastercard Vice President of Product Max Lessman in a Trulioo-hosted webinar, “Combating Synthetic Business Fraud With Layered Verification.” The panel explored how AI, synthetic data and fragmented KYB flows are reshaping digital business verification and how organizations can stay ahead with layered defense strategies.

Cautionary Tales: Real Business and Consumer Impact

Falling behind on fraud prevention can lead to far-reaching, devastating consequences, something Lessman illustrated with a real-world example.

In this case, a fraud ring infiltrated a mid-sized marketplace. They exploited a weakness in the business’s onboarding flow, bypassing KYB checks by using synthetic data to create fraudulent merchant profiles.

The damage rippled through every part of the business. Fraud teams were forced into rapid response mode, chargebacks surged and customer trust began to erode.

According to Lessman, approval rates dropped from the mid-90s to the low-70s in just two days, ultimately cutting 20% of the marketplace’s overall revenue.

“Up to 60% of consumers say that they would not return to a business if they had a bad experience with them,” said Lessman. “The risk of reputational damage, especially in a fairly crowded space, is very detrimental to the business. From a business impact perspective, there’s financial gain, operational cost, reputation, ecosystem and trust and safety at risk.”

Fighting Back With Layered Verification

When synthetic fraud floods the system, a single checkpoint can help mitigate the damage. But why rely on a bucket in a storm when you can build a strong defense while the skies are still clear?

“These defense strategies need to be dynamic, multi-layered and they should follow a risk-based approach,” Sarkar said. “Instead of static, one-time checks, it’s really important that you’re corroborating information across multiple authoritative sources in real time.”

The future of KYB lies in going beyond single checkpoints to combine real-time registry data, document and nondocument verification, digital footprint analysis and ongoing monitoring. Leading companies are creating workflows that adapt to risk by escalating verification checks for high-risk profiles like newly registered businesses or sole proprietors. They’re also incorporating tools like biometric authentication, alternative data sources and AI-driven anomaly detection.

Lessman emphasized that the key to robust protection is rooted in multiple layered sources of information. “Continuously layering things on top of each other [helps] you be able to build the best picture that you possibly can and be able to discern: do I feel confident that this person or this business is who they say they are? That requires layering in both looking at the business, but also the people behind it.”

Combating Fraud Isn’t a One-Size-Fits-All Approach

A layered approach entails building on foundational identity verification, such as legal existence checks and document verification for PSCs or UBOs. The onboarding process should automatically trigger enhanced verification flows based on a business’ unique situation, tailoring defenses to context, risk and intent.

As fraud tactics grow more sophisticated and harder to detect, organizations must move beyond fixed workflows and embrace systems that are adaptable, nuanced and risk-aware. The goal is to detect bad actors and confidently recognize legitimate businesses without introducing unnecessary friction.

Looking ahead, this adaptive approach will become a defining capability for organizations operating in digital, data-rich and trust-sensitive environments. Combating synthetic business fraud isn’t simply a matter of building higher walls. It’s about building smarter systems that learn, adjust and respond in real time.