The Candidate Fraud Curve: What Millions of Validated Assessments Reveal About Systemic Cheating in Modern Hiring

joseph cole

Updated on February 18, 2026

The Candidate Fraud Curve: What Millions of Validated Assessments Reveal About Systemic Cheating in Modern Hiring

joseph cole

Updated on February 18, 2026

In this post

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Fraud in hiring doesn’t fade because you catch it. It fades when you make it pointless.

Across millions of Glider AI validated technical assessments conducted over multiple years, one pattern stands out:

  • Hiring fraud follows a curve.
  • When hiring relies on signals, fraud rises.
  • When hiring requires proof, fraud declines, and stays down.
  • That’s not a theory. It’s longitudinal data.

And it matters now.

Investigations by The Wall Street Journal and Bloomberg recently exposed how remote workers using stolen identities embedded themselves inside U.S. companies, sometimes funneling millions of dollars abroad.   

  • Extreme cases? Yes.
  • Isolated? No.

Remote hiring built on signals is structurally vulnerable. Resumes can be written by anyone. Profiles can be manufactured. Assessments can be outsourced. Interviews can be staged. Signals scale. Manipulation scales with them.

Proof changes the math.

Fraud Has Phases


The data reveals three distinct stages.

Phase 1: Signal Dominance: In environments driven by resumes and unverified remote testing, fraud indicators approached 20–25%. Where manipulation works, it spreads.

Phase 2: Validation Introduced: Add structured skill validation and identity controls, and fraud doesn’t vanish. It fluctuates. Bad actors test the boundaries. Variance across hiring organizations becomes visible.

Phase 3: Proof Normalized: Over time, fraud stabilizes in the low single digits, typically 2–4%. Volume increases. Fraud does not.

That’s the collapse. Not detection. Deterrence. Once gaming the system stops paying off, the system stops getting gamed.

Risk Isn’t Evenly Distributed


Fraud doesn’t spread uniformly across the hiring ecosystem. And by hiring ecosystem, we mean the full architecture of how talent enters an organization:

  • Direct applicants
  • Agency-submitted candidates
  • Contingent workforce programs
  • Global or offshore hiring channels
  • High-volume technical recruitment streams
  • Enterprise hiring organizations operating as suppliers to other enterprises

To better understand the pattern, we analyzed the top 100 enterprise hiring organizations by assessment volume. A clear trend emerged.

The highest-volume organizations largely clustered in the low single digits, typically between 1-4% fraud indicators. But variance widened quickly outside that band.

  • Several organizations exceeded 6–10%.
  • Isolated outliers reached double-digit levels.
  • Volume alone did not predict fraud.

Governance did.

Enterprise hiring organizations operating within structured validation environments stabilized fraud rates over time. Those with weaker identity controls or inconsistent oversight exhibited materially higher exposure.

Even among large, enterprise-scale hiring organizations–whether internal enterprise teams or external staffing partners, risk varied significantly.

Fraud clusters where validation is weakest. This isn’t a candidate integrity problem.

It’s an architecture problem. And architecture determines risk exposure.

Scale Doesn’t Have to Increase Risk


Here’s what makes this counterintuitive. Assessment volume increased over time. Fraud decreased.

In most enterprise systems: cybersecurity, financial fraud, compliance–scale multiplies vulnerability. In proof-based hiring systems, scale compounds deterrence.

When validation becomes standard practice, manipulation becomes inefficient. Enterprise hiring organizations adapt. Repeat offenders disappear. Behavioral norms shift.

Fraud collapses because the incentives collapse. That’s structural suppression.

The Real Risk Is Architectural


Remote hiring now intersects with:

  • IT access
  • Source code repositories
  • Customer data
  • Financial systems
  • Regulatory and compliance frameworks

A fraudulent hire isn’t just a poor recruiting outcome. It’s a potential insider risk event. As remote work expands and AI lowers the barrier to impersonation, signal-based systems grow more fragile. Proof-based systems grow more resilient. That’s the curve.

When hiring relies on signals, fraud rises. When hiring requires proof, fraud declines, and stays down.

What This Means for HR and TA Leaders


If fraud follows a curve, system design determines where you sit on it.

  1. Signals invite manipulation. If it can be gamed remotely, it will be.
  2. Proof changes behavior. When manipulation stops working, attempts decline.
  3. Risk is uneven. Enterprise hiring organizations, whether internal teams or staffing partners, carry different exposure levels.
  4. Scale isn’t the problem. Unvalidated scale is.
  5. Hiring is now a security surface. It affects systems, data, and enterprise risk.

The question isn’t whether fraud exists. It’s whether your hiring architecture suppresses it, or quietly rewards it.

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