Expert outlines tips to to keep hiring smooth amid the rise of AI-assisted candidate fraud
The rise of artificial intelligence tools has made candidate fraud easier for bad actors, introducing a greater challenge for many HR leaders during recruitment.
A report from Gartner last year warned that one in four job candidates globally will be fake by 2028, as GenAI tools make deepfakes "increasingly sophisticated and adaptable."
One example of this was the case of Vidoc Security co-founder Dawid Mozcadlo, who shared his experience on LinkedIn last year with a job applicant who used AI to alter his appearance and answer his questions during a job interview.
Husnain Bajwa, SVP, Product at SEON, said the fabrication of an entire professional identity using AI is one of the biggest issues they see for HR and talent acquisition teams.
"Fraudsters are using AI to build entire professional identities from scratch, including fake names, synthetic headshots, polished LinkedIn profiles, and convincing portfolios," Bajwa told HRD.
"What makes it especially dangerous is how these campaigns operate. It's rarely just one fake application. These are coordinated efforts; dozens of submissions hit multiple open roles at the same time, and they're all designed to look like legitimate, high-quality candidates."
How to spot fake candidates
No single red flag is enough to determine if a job applicant is a fraud, according to Bajwa.
However, he noted that certain patterns emerge that HR leaders can watch out for if they want to spot fake candidates. They include:
- Multiple applications coming from the same device or IP address
- Identity details that don't add up
- AI-generated responses that tend to be very polished but generic
When it comes to a portfolio, HR leaders can look out for GitHub accounts created just a month before the application, watch out for cloned repos, or design portfolios packed with shallow derivative work.
A string of applications that arrive within a 15-minute window with the same formatting and language may also be cause for concern, according to the expert.
"The good news is that technology to surface these signals exists," he said.
"HR teams don't have to be doing this manually and can instead use tools that can pull this data together and offer a clearer picture of who's real and who isn't."
Maintaining a smooth hiring experience
But even with enough tools, the challenge of spotting a fraud while maintaining a smooth application process for a jobseeker can persist.
HR leaders are already grappling with long hiring times, with the current global average between 40 and 60 days, according to PlugScale.
Previous research has indicated that the longer and more complex the hiring process, the less likely that jobseekers will stick around until the end of the process.
Introducing fraud prevention techniques can make the hiring process even more troublesome for genuine applicants.
"No one wants to jump through extra hoops just to apply for a job. HR teams need to find a balance between screening for fraud without filtering out genuine candidates," Bajwa said.
What HR leaders can do instead is implement checks in the background, starting from the moment an application is submitted.
"A good verification system can look at device fingerprints, network behaviour, submission timing, document metadata, and identity consistency across platforms, all without the candidate ever knowing it's happening," he said.
According to Bajwa, the only time an application may be reviewed by a human is when the system picks up on certain red flags, such as a VPN combined with a new LinkedIn profile, as well as a CV that matches other submissions word for word.
"The model you want is fast and frictionless for legitimate candidates, with extra scrutiny reserved for those who need it," he said. "It also saves your recruiters wasted time. Instead of discovering a problem after multiple rounds of interviews or after making an offer, you're catching it upfront."
Ultimately, Bajwa emphasised that no verification system should compromise fairness, especially for genuine jobseekers.
"When you're screening based on objective, technical signals rather than gut feelings or surface-level impressions, you're less likely to let bias set in," he said.
"The goal is to catch bad actors at the onset so your team can focus their time and energy on the candidates who deserve it."
