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The $1.2 billion skin graft scheme and what it reveals about modern fraud networks
A medical product most people have never heard of is now one of the largest Medicare fraud categories in the United States driving over $10 billion in annual Medicare spend.
Skin substitutes, often derived from human or animal tissue, are used to treat chronic wounds. They are legitimate, clinically approved, and reimbursed at high rates. They are also being exploited by sophisticated fraud networks.
In under five years, Medicare spending on these products has exploded from hundreds of millions to over $10 billion. Not because patient need suddenly surged, but because fraud found a scalable, low-visibility entry point.
What makes this trend dangerous is how these schemes operate: quietly, legally on the surface.They rely on networks of businesses that appear compliant in isolation, routing billing and payments through processors, billing intermediaries, distributors, and service providers. We’re seeing this same pattern emerge across payment portfolios.
This case is not about one bad clinic, it’s about a new fraud model, that spreads risk across a network rather than concentrating it in a single merchant.
The case that exposed a $10 billion fraud category
In October 2025, the US Department of Justice announced the sentencing of the owners of a wound graft company behind one of the largest healthcare fraud schemes on record. Over 18 months, the operation billed Medicare approximately $1.2 billion for skin substitute procedures, many of which were medically unnecessary or improperly applied.
At the time, Medicare reimbursed skin substitutes at up to $2,000 per square centimetre, creating unusually strong financial incentives for volume. This means a graft the size of a standard smartphone could bill for over $150,000.
According to the DOJ, the scheme followed a familiar pattern:
Elderly and hospice patients were targeted
The largest reimbursable grafts were ordered regardless of clinical need
Billing was routed through a web of seemingly legitimate entities
When authorities raided the operation, they seized tens of millions of dollars in cash and assets, including luxury vehicles and gold bars.
This case was not isolated.
Medicare spending on skin substitutes increased from roughly $256 million in 2019 to more than $10 billion by 2024. In the DOJ’s 2025 Healthcare Fraud Takedown, seven additional individuals were charged for running parallel schemes totalling over $1.1 billion.
What we’re witnessing is industrialised exploitation at its core.
The ecosystems behind fraud, and what they mean for payment teams
Modern fraud networks rely on an ecosystem of legitimate-looking businesses. This typically includes:
Billing companies
Consulting firms
Product distributors
Shell clinics and provider entities
On the surface, each entity appears compliant. They are registered businesses, with real suppliers, functioning websites, and basic compliance artefacts.
For payments teams, every one of these entities needs to move money. When merchants are analysed in isolation, risk often remains hidden. When payment teams begin mapping how entities, accounts, and infrastructure connect, patterns emerge that do not exist in legitimate portfolios.
The hidden signals fraud teams should be watching
Across fraud investigations, the same infrastructure-level patterns appear again and again.
On their own, these signals rarely trigger alerts. Together, they reveal how fraud networks are structured.
Domain and digital infrastructure
Fraud networks often register clusters of websites within short timeframes, using the same registrars, recycled templates, and overlapping language. Privacy policies, service descriptions, and contact pages are frequently reused.
Physical footprint overlaps
Clinics or billing offices tied to supposedly independent entities may share addresses, office parks, or highway corridors. These groupings are rarely accidental.
Shared operating infrastructure
Distinct companies may use the same phone numbers, email domains, payment processors, or backend tools. These shared dependencies expose connected entities operating behind separate brands.
Repeat entity formation
When one entity is shut down or flagged, closely related businesses may appear with similar names, structures, or infrastructure, linked to the same underlying operators.
Why this is hard to catch at the payments layer
For payments teams, schemes like this are difficult to detect because they rarely fail in obvious ways.
At onboarding, each business often presents as legitimate:
Websites look complete and professional
Policies and documentation are present
Declared activity aligns with the stated business model
Transaction behaviour, where visible, is often consistent with their services
Viewed in isolation, each merchant looks reasonable.
Signals are distributed across connected entities, with shared domains, infrastructure, addresses, and operating dependencies.
Assessed separately, by different analysts, at different points of time, these signals fall below review thresholds. Connected, they reveal a coordinated network.
From a payments perspective, exposure accumulates when fragmented signals are approved independently, allowing networks to form and scale.
In cases like this, the challenge is not a lack of data. It is the lack of a consistent way to connect messy, real-world signals into a clear, defensible risk view.
A note on how TrueBiz approaches this
TrueBiz focuses on helping payments and risk teams see what is difficult to detect at the merchant level: how businesses are connected.
Rather than evaluating entities in isolation, we analyse relationships across domains, infrastructure, ownership signals, and payments data to surface coordinated activity earlier.
The skin substitute cases show why this matters. The fraud was not hidden, it was distributed.
Understanding those connections sooner enables faster, more defensible decisions before issues form across your portfolio.
If you’d like to discuss how networked fraud risk may be showing up in your portfolio, or how these patterns can be identified earlier, reach out to the TrueBiz team here.