Candidate fraud is accelerating rapidly, with Gartner projecting 1 in 4 candidate profiles will be fake by 2028 and 41% of enterprises reporting they have already hired a fraudulent candidate.
Hiring depends on trust across people, systems, and handoffs – each an opening for an attacker. Remote hiring widened those openings, and AI has made them easier to exploit.
Today’s candidate fraud often goes beyond resume inflation, involving coordinated efforts to steal data, money, and access to critical systems.
Standard hiring and identity tools weren’t built for candidate fraud at today’s scale and sophistication. Catching it takes stronger detection where the risk shows up: in the interview itself.
BrightHire surfaces fraud signals from applications, AI screening interviews, and live interviews, so flags are raised wherever they appear, instead of at a single checkpoint a bad actor can slip past.
Candidate fraud takes many forms, from impersonation and AI-assisted answers to deepfakes, multi-device cheating, and manipulated identities. BrightHire looks for all of them, so a single type of attack can’t slip through unseen.
BrightHire brings together signals across behavior, identity, device, and context into a single, scalable view, so your team can see the full picture.
THE ZOOM ADVANTAGE
As part of Zoom, BrightHire incorporates proprietary signals and models that bring a differentiated level of security to your live interviews on Zoom, with identity, device, and deepfake detection available on no other platform.Proprietary fraud detection for Zoom interviews
Every signal is backed by audit-ready records, so detection holds up to scrutiny.
Every flag links back to the signal that triggered it, so teams can investigate before deciding.
Every signal, review, and decision is documented, giving teams a defensible trail for candidates, hiring managers, and regulators.
Signals route candidates for review so people stay in control of every hiring decision.
Built to align with NIST 2025 digital identity guidance and emerging rules around AI in hiring.
Candidate fraud detection is embedded directly into the leading platform for driving hiring excellence, with no additional tools or process changes required.
Expert insights and in depth guides for candidate fraud prevention.
What is candidate fraud?
Candidate fraud is when an applicant misrepresents who they are or what they can do, ranging from inflated resumes and AI-assisted cheating to impersonation, deepfakes, and stolen or fabricated identities. It has grown from a hiring nuisance into a security risk, and Gartner projects that by 2028, one in four candidate profiles worldwide will be fake. You can go deeper in our candidate fraud guide.
What types of fraud does BrightHire detect?
BrightHire detects signals across the full range of interview fraud, including impersonation, deepfakes, AI-assisted cheating, and identity inconsistencies, in both AI screening interviews and live interviews. Levels of coverage differ depending on the platform used, with the deepest coverage on Zoom but also available for Microsoft Teams and Google Meet.
How do you detect a fake candidate during the interview?
You look for patterns across stages rather than any single red flag. BrightHire surfaces signals in AI screening interviews and in live interviews, then combines them into one unified view of risk your team can investigate. Catching fraud inside the interview itself reaches what identity checks alone cannot. An ID check can’t stop a different person from joining the call, or AI from coaching answers in real time.
How does AI help detect deepfakes and AI interview fraud?
AI does the groundwork. It passively surfaces and combines fraud signals in your interview process, with no extra verification steps for legitimate candidates. For Zoom users, BrightHire adds deepfake interview detection powered by Zoom’s own proprietary models. AI surfaces the signal and your team makes the call, with every flag linked back to the moment that triggered it, so decisions stay explainable and human.
Will hiring fraud detection hurt the candidate experience?
No. The point of catching fraud is a faster, fairer process for honest applicants. Signals trigger human review, never automated rejection, and they are captured in the flow of work with no friction for legitimate candidates. Teams that structure their interview process with BrightHire run a more consistent process overall.
How is BrightHire different from an identity verification tool?
ID verification before the interview is necessary but not enough. It cannot stop a different person from joining the call or AI from coaching answers in real time. BrightHire works inside the interview, the richest place to catch what slips past earlier checks, and rolls every signal into one defensible, audit-ready record aligned with NIST 2025 digital identity guidance. It complements identity tooling rather than replacing it.
