Martin

TrackLight Whitepaper: Lessons from the FastLab Case

How Outdated Screening Enabled a $500M Fraud Scheme

and What Medicaid Leaders Can Do About It

Executive Summary

Government health programs—Medicaid, Medicare, and TRICARE—continue to be targets of highly sophisticated fraud schemes.  The case of Martin Perlin, who conducted one of the largest COVID‑era testing fraud operations, illustrates a critical failure point: programs rely on basic enrollment screening rather than proactive risk detection.

Perlin billed over $566 million across Medicaid, Medicare, TRICARE, and private insurance plans using his company, FastLab Technologies LLC.  Despite having a thirteen‑year history of sanctions, opioid misconduct, and a patient death, he met the minimum criteria required to enroll as a provider.

His case exemplifies how fraudsters slip past program enrollment checks—causing enormous financial loss and delaying care for patients who truly need it.

Case Overview

Martin Perlin and Jimmy Biricik orchestrated a scheme that one of the most brazen examples of COVID‑era healthcare fraud — not because it was complex, but because it was easy to detect using public data that already existed.

Perlin and Biricik owned and operated FastLab Technologies LLC, a clinical laboratory positioned to exploit the sudden surge in COVID diagnostic testing demand.  While legitimate providers struggled with supply chain constraints, FastLab executed an explosive growth pattern: registering corporate entities quickly, onboarding as an approved billing provider, and submitting extraordinarily high‑volume claims in an unrealistically brief period.

Within months, FastLab billed more than $566 million across Medicaid, Medicare, TRICARE, and private insurance plans.  Investigators later determined that FastLab frequently:

• Billed for tests that were medically unnecessary
• Used improper or fraudulent diagnostic coding sequences
• Submitted claims with little or no documentation
• Bundled COVID tests with unrelated panels to inflate billings
• Hid the scale by billing across different payer types and multiple NPIs.

Yet none of this activity occurred in a vacuum — Perlin had a documented history of:

• Thirteen sanctions in multiple states
• Opioid overprescription incidents
• A prior patient death tied to inappropriate medical treatment
• License surrender in Connecticut

For nearly two years this continued as Perlin and Biricik expanded their fortunes with Bentley’s, Ferrariri’s, Porche’s, aircraft, jewels, and a nearly $5M Boca Raton mansion.   Finally, with the help of whistleblowers, the fraud was brought to light and both Perlin and Biricik were charged on July 31, 2023.  On September 2, 2023, Perlin was excluded from Medicare and Medicaid.  To date, under $10M (under 2%) of the fraudulent payments have been recovered.

What Should We Learn from the Case of Martin Perlin?

Perlin’s case proves a critical point: Fraud is often detectable long before a claim is ever submitted.

Traditional enrollment screening focuses primarily on verifying basic compliance inputs such as active license status, exclusion list checks, and disclosure of ownership information.  Fraudsters exploit these narrow, binary criteria.  In Perlin’s case, all the warning signs were already available across multiple public sources — state licensure databases, public sanctions records, civil penalties and consent orders, and corporate filings that showed rapid business formation and explosive growth.  However, because these data sources were reviewed in isolation rather than analyzed together, none of the risk signals were connected, allowing Perlin to enroll and bill government programs without elevated scrutiny.

Changes in how fraud is approached and prevented are needed.  Available data across numerous publicly available sources must be analyzed and risk factors must be used to improve oversight and identify fraudulent activity early.

The Case of FastLab with TrackLight

TrackLight’s continuous provider integrity monitoring would have identified Martin Perlin and Jimmy Biricik long before they were able to amass conduct a scheme of this magnitude.

TrackLight gives organizations the ability to proactively analyze the full behavior or providers, companies, and other entities and the ability to assign a risk profile based on regulatory and historical data.  Perlin had thirteen sanctions across multiple states, a surrendered medical license, opioid-related reprimands, and a documented patient death tied to inappropriate prescribing.  These data points all existed in public licensure and sanctions repositories but were never evaluated together.  These actions did not rise to the level of fraudulent activity, but they were clear indicators that Perlin had a history of digressions.  Given this historical behavior TrackLight’s automatic ingestion and correlation of these data sources, would have generated a high-risk score even before a single COVID claim was submitted.

Once FastLab began billing, TrackLight’s anomaly detection models would have escalated the risk level based on billing velocity and claim patterns.  Perlin’s lab went from existence to billing hundreds of millions of dollars at a pace that was mathematically inconsistent with typical diagnostic testing operations.  In Perlin’s case, the system would have surfaced warnings as soon as volume growth became visible in billing data, well within the first few weeks of the scheme—not after hundreds of millions had already been paid.

TrackLight’s ability to connect identities, ownership records, and cross-state licensure data to reveal risk signals that legacy systems miss.  Perlin exploited the fact that a provider can lose a license in one state, maintain an active license in another, and still pass Medicaid enrollment screening.  By transforming fragmented regulatory signals into a unified risk assessment, TrackLight would have prevented enrollment—or at minimum triggered early investigative intervention—before the fraudulent billing cycle ever began.

Are You Ready to Modernize Fraud Detection and Prevention?

Every dollar lost to fraud is a dollar taken away from the people who need services the most.  TrackLight gives leaders the power to detect fraud early—before claims are paid—using real-time risk scoring, continuous monitoring, and intelligent alerts.  Don’t wait for the next Perlin-level scandal to expose program vulnerabilities or drain limited budgets.

A fully cloud based solution enterprise level security and privacy TrackLight can be implemented in any organizations immediately and can be integrated into existing systems allowing employees to augment their capabilities without learning new tools.

→ Take the proactive path.  Let us score a subset of your provider file — at no cost — and show you where risk is hiding.