Applicant fraud is not a new phenomenon, but in a labor market shaped by remote work, easy access to AI tools, and faster-than-ever candidate workflows, it is showing up more frequently and in more sophisticated ways. In the RPOA webinar “Applicant Fraud Unmasked,” the speakers discussed what applicant fraud looks like in today’s hiring environment, why it’s accelerating, and what practical steps recruiting and RPO teams can take to reduce risk without compromising candidate experience.
Rather than treating fraud as a niche or rare issue, both speakers framed it as a growing operational reality for hiring teams, especially in tech and remote roles, where verifying identity, skills, and authenticity can be harder than in traditional in-person processes.
This post is based on insights from the speakers Matt Corbett, President of ZRG Embedded Recruiting/RPO and RPOA Advisory Board Member, and Dan Harten, Customer Marketing Strategist at hireEZ.
Key Takeaways
- Applicant fraud has existed for decades, but recent shifts, especially remote work and AI tools, have made it more common and more scalable.
- Five distinct forms of applicant fraud, ranging from AI-assisted resume embellishment to “state-sponsored” efforts aimed at accessing sensitive corporate data.
- Early identity verification and deeper interviewing techniques (camera-on expectations, probing follow-ups, and live skills demonstrations) serve as practical defenses.
- Recruiters’ “spidey sense” matters, but it needs organizational backing, including clear escalation pathways and cross-functional support rather than blame.
- Technology can help flag risk signals, but tools are not a complete solution without human judgment and process discipline.
Watch the webinar on-demand: What Talent Teams Are Seeing and How They’re Responding
Setting the Stage: From “Rare” to Regular Risk
Dan Harten opened the discussion by positioning applicant fraud as a broad term that can mean different things to different hiring organizations. He noted that part of the challenge is getting aligned on what fraud includes, from exaggerations on resumes to more serious identity deception.
Corbett underscored that fraud is not new. He shared that his first experience with applicant fraud dates back to the 1990s during the dot-com boom, when global demand for engineers created conditions where hiring teams encountered a familiar scenario: “the candidate we spoke to wasn’t the person doing the work.”
What’s different today, Corbett argued, is scale and visibility. He said it’s no longer something one or two people in an organization stumble across occasionally; hiring teams are increasingly suspicious that AI is assisting candidates “through the process at some point,” and many are encountering fraud directly.
Harten referenced several industry projections and survey findings during the webinar, including a Gartner projection that by 2028, one in four candidate profiles could be fake, and additional surveys suggesting significant levels of misrepresentation, especially in tech and remote hiring contexts.
Why Applicant Fraud Is Rising
When Harten asked what’s driving the increase, Corbett pointed to four primary forces:
- Remote work reducing face-to-face interaction and making identity verification harder
- AI tools increasing the ease and quality of deception
- U.S. labor market dynamics, which Corbett described as “open labor laws” and a highly fluid market that can also create opportunities for fraud
- Motivation to access corporate systems and data, especially as technology cycles accelerate and data has become a valuable target
Harten reinforced the remote-work point, noting that remote hiring creates “less face-to-face interaction,” while AI enables everything from AI-generated resumes and cover letters to convincingly fabricated experience. He also pointed to the ease of creating or manipulating credentials, such as producing a document that appears to validate education or experience.
Corbett agreed that these factors create an environment in which applicant fraud becomes easier to execute and harder to detect without deliberate process changes.
Defining Applicant Fraud: Five Types, From “Not So Scary” to “Terrifying”
A major theme of the conversation was that applicant fraud isn’t a single behavior. Corbett offered a practical taxonomy based on what he and his team have seen, ranked from lower-risk to higher-risk scenarios:
- AI-assisted embellishment: resume polish or exaggeration using AI tools
- Identity fraud: someone claiming to be a different person
- Skills fraud: presenting work as one’s own when it’s not
- Fraud as a business model: organizations supplying fake candidates to get them on payroll and generate revenue
- State-sponsored fraud aimed at gaining access to confidential data, intellectual property, or sensitive systems
Corbett described the first category (AI-supported embellishment) as an extension of what candidates have “done from the beginning of time,” but with technology making it faster and more effective. The latter categories, he suggested, pose significantly higher risk because the goal is not just employment but access for financial gain or the strategic extraction of proprietary information.
Harten’s definition aligns with this framework, characterizing applicant fraud as candidates “intentionally” providing false or misleading information, ranging from resume claims to fake identities. He distinguished between lower-risk scenarios (fabrication or exaggeration) and higher-risk scenarios in which fraudsters seek access to systems and data.
Why It Matters: The Business Cost of Getting It Wrong
Corbett noted that the first question he often hears from clients is straightforward: Why should we care? His response focused on cost and operational disruption. He cited a statistic he had recently read: when a fraudulent hire is caught, even early, it can cost a company $30,000–$40,000 per person.
Beyond dollars, both speakers suggested that fraud undermines trust in the hiring process, creates risk exposure, and consumes time across recruiting, hiring managers, HR, and potentially legal or security teams.
Practical Defenses: Interview Design, Verification, and “Going Deeper”
While the topic can feel daunting, Corbett repeatedly emphasized that many countermeasures are straightforward. He described several practical signals and process adjustments recruiters can deploy immediately:
- Camera-on video interviews with “no exceptions”
- Watching for consistent delays between question and answer that could indicate AI prompting or outside assistance
- Avoiding interview patterns that allow simple “yes/no” responses and instead asking complex questions with layered follow-ups
- Multiple interviewers and internal escalation when someone’s “gut feeling” suggests a problem
- Greater emphasis on skills assessments, including live demonstrations
Harten agreed that recruiters should lean into their instincts, summarizing the approach as: “If you see something, say something.” He recommended documenting concerns and escalating through a defined internal process rather than making accusations in real time. In his view, recruiters aren’t investigators, but they are often the first to detect when something seems off.
Corbett added that candidates can be tested on depth and authenticity through structured follow-ups: go “three or four or five levels deep” into a topic, and it becomes much harder for a fraudulent candidate to sustain a fabricated narrative.
Live Skills Demonstration and Portfolio Scrutiny
Harten described how technical hiring has long used assessments, but argued that the current landscape may push teams toward even more live validation, such as real-time whiteboarding or live coding over video, because it tests whether a candidate can actually perform without hidden assistance.
Corbett strongly agreed: “Live coding is essential,” he said, and he urged interviewers to treat portfolios with more skepticism. Rather than accepting work samples at face value, he recommended digging into specifics:
- What was the situation when you joined?
- What were the requirements?
- What exactly did you build?
- What was the outcome?
For Corbett, failing to probe a portfolio is a missed due diligence step: if a candidate is presenting a body of work, interviewers should “break out a lot of time to dig deep.”
Training Without Cynicism: Keeping Recruiters Effective and Human
A recurring tension in the conversation was how to prepare teams for fraud without turning recruiting into a cynical, adversarial process.
Corbett cautioned against creating a culture where recruiters assume dishonesty by default. He emphasized that recruiters still need to be excited about engaging candidates and building relationships. The goal, as he framed it, is awareness and simple, repeatable checks, not suspicion of everyone.
At the same time, Corbett argued that the landscape has changed enough that verification steps should become routine. He highlighted reference checks as an example, questioning why they have become “almost non-tested these days,” and suggesting they should regain value.
Corbett also pointed to how AI has changed applicant pools. On platforms like LinkedIn, he noted that match rates that used to be 12–15% can look dramatically higher now because “AI has adjusted their background.” In that environment, he argued, recruiters should assume some level of AI-driven optimization and respond with stronger validation.
A Real Example: The Syracuse University Test
To make the issue tangible, Corbett shared a recent example from his own interviewing. The candidate’s resume listed Syracuse University. Before the call, Corbett looked up the campus map and asked practical questions about residence halls and campus orientation, questions someone who attended would likely answer naturally.
The candidate couldn’t answer any of them. Corbett described it as an “innocuous way” to validate credibility that requires only a bit of research. In his view, this kind of lightweight verification can catch identity or credential fraud early without turning the interview into an interrogation.
Technology’s Role: Helpful Signals, Not Full Automation
Although much of the webinar focused on human-led process, both speakers acknowledged emerging technologies designed to detect fraud patterns and flag risks.
Corbett mentioned clients asking about tools such as Phenom, Eightfold, Beamery, and other approaches he had been reading about, including tools associated with “cross clarify,” which he described as interesting.
Harten shared how hireEZ is approaching the problem through technology that flags hidden signals, such as “white text” prompts embedded in resumes (instructions aimed at manipulating screening tools) or conflicting information within candidate materials. He emphasized that these tools don’t “make a decision” about fraud; instead, they provide indicators so recruiters can “dig a little bit deeper” and interview more effectively.
When asked whether technology is more applicable in high-volume environments, Harten described it as an enabler rather than a replacement. Corbett added that because technology stacks vary widely across organizations, the most universal control remains human decision-making, though he acknowledged “amazing work” being done in areas like AI-based interviews and language-pattern insights.
What This Means for RPO and Talent Acquisition Teams
Across the discussion, Corbett and Harten framed applicant fraud as a shared operational risk requiring shared responsibility. Recruiters need permission and training to escalate concerns. Hiring managers need to understand that fraud is part of the modern landscape. And organizations may benefit from cross-functional structures. Harten suggested ideas like an applicant fraud committee that includes recruiting, legal, and technology stakeholders.
Corbett also highlighted that fraud prevention can be positioned as a capability and differentiator, particularly for RPO providers, by setting candidate expectations (camera-on, deeper portfolio review, live tests) and supporting recruiters to flag issues without fear of being blamed for slowing down hiring.
As Corbett put it, the old hesitation to raise concerns may have been valid years ago, but “today, it’s different.” The landscape has shifted, and the recruiting function has to adapt to it.
