Candidate Fraud Detection in the Age of AI: How to Catch What Traditional Hiring Can't

One in four candidate profiles will be fake by 2028, according to a Gartner Survey. AI-generated resumes, deepfake interviews, and fabricated work histories are already slipping past traditional hiring workflows, costing organizations tens of thousands per fraudulent hire.

The key is catching fraud before it gains momentum. Leading organizations aren't relying on a single checkpoint — they're building multi-layered defense systems that start when the job seeker first submits their application. AI agents, psychometric assessments that are highly contextual to each role, and real-time integrity detection work together across every stage of hiring. The result: more confidence in who you’re hiring and far fewer surprises after the offer.

Join us to learn how to catch what AI can’t replace and resumes can’t validate. We’ll cover ways to:

• Recognize the various methods of candidate fraud and why it’s harder to catch than ever

• Leverage highly contextual assessments that accurately measure behavioral, situational, and technical expertise for each role, adding a skills validation layer to overcome augmented resumes

• Use agentic AI-led interviews to detect fraud signals in real time, analyzing voice, behavior, and response patterns while probing for depth, context, and real-world application

• Analyze across applications and interviews to determine if the same candidate is applying under different names with different credentials

• Create a centralized decision dashboard to consolidate application, assessment, and interview signals into a layered verification process that flags fraud across the entire hiring lifecycle