Candidate fraud detection: what it is, the main types, and how to check

Hiring teams use the phrase "candidate fraud" for a wide set of problems, from a padded resume to an organised scheme. This post narrows it to what a hiring process can check: is this the person who applied, is that their real face and voice, and are the answers their own. It covers the types, how common they are, and where in the process each one can be caught.

What candidate fraud means

Gartner's survey gives the narrow version. HR Dive reported that "In a survey of 3,000 job candidates, 6% said they participated in interview fraud, either by posing as someone else or having someone else pretend as them."

Gartner also made a prediction: by 2028, 1 in 4 candidate profiles worldwide "could be fake". It is a forecast, not a measurement. Gartner advises a "multi-layered fraud mitigation strategy", including in-person interviews and post-hire "system-level validation". Our statistics guide keeps the numbers and how each was measured.

Five types of candidate fraud

Most of these are not new. The FBI warned in 2022 of "the use of deepfakes and stolen Personally Identifiable Information (PII) to apply for" remote jobs. In June 2025 the US Justice Department said North Korean IT workers had obtained jobs at "more than 100 U.S. companies", and that agents searched "29 known or suspected 'laptop farms'" across 16 states.

How common it is

• Managers. In Checkr's 2026 survey, 40% "have interviewed a candidate later found to be using a fake identity, up from 31% in 2025", and "just 23% of managers are extremely confident their hiring process would catch a fraudulent candidate". It is a vendor survey of 3,000 US managers involved in hiring, fielded September 11 to 16, 2026.
• Candidates. 6% of 3,000 candidates in Gartner's survey said they had taken part, by their own account.
• Assessments. CodeSignal's attempt rate on proctored assessments rose from 16% in 2024 to 35% in 2025 (vendor data). Its categories include "proxy test-taking" and "identity fraud".

In the same Checkr survey, 68% of managers believe "candidates are better at faking their identities with AI than companies are at detecting them."

Where to check: four layers

No single check covers every type. An ID check confirms a document; it does not confirm who is answering on the call an hour later. Each layer below catches something the others miss.

Each layer has its own blind spot. Ashby's docs say it plainly: "A successful check does not mean there was no fraud." The FBI's 2025 advice spans every layer: "Implement identity-verification processes during interviewing, onboarding, and throughout the employment of any remote worker".

Signals the FBI lists

The FBI's public warnings list signs worth knowing. None is proof on its own; each is a reason to look closer.

• On video, the "lip movement of the person seen interviewed on-camera do not completely coordinate with the audio", and "coughing, sneezing, or other auditory actions are not aligned with what is presented visually" (2022).
• Use of "artificial intelligence and face-swapping technology during video job interviews" (2025).
• "reused phone numbers (particularly voice-over-IP numbers) and email addresses" (2025).
• "changes in address or payment platforms during the onboarding process" (2025).

The FBI also suggests "soft" interview questions about where the candidate is. For a fuller list of signs at each stage, see red flags before, during and after the interview, and for identity checks on video, how to verify a candidate's identity.

What Verified Call adds on the live call

Verified Call works on the live-call layer. It never joins the call. It plugs into the calls you already run. Google Meet today, actively expanding to Zoom and Teams. We publish how each check was tested.

Results are advice for the host, not a verdict on a person. Every result, with its date and conditions, is on the Research page. No other tool publishes its research or test data. We do, false alarms included.

Questions to ask any vendor

• Which layer does it cover: the application, the identity, the live call or day one?
• How often does it catch the problem, as a count, and how often does it flag someone who did nothing wrong?
• Does it join the call, and what does the candidate have to do?
• Was it tested on live calls or on recordings, and when?

To compare vendors by approach, see cheating detection tools for interviews. To judge a vendor's evidence, see how interview integrity tools are tested.