You could be paying a salary to someone who doesn't exist. That's not a hypothetical, it's the reality of synthetic candidate fraud. A synthetic candidate is a fabricated identity created using AI and real data fragments to pass hiring processes undetected. Meaning, your next hire may not exist in human form at all.
It's not a fringe risk either. Candidate fraud is rising dramatically due to remote work and accessible, high-quality AI, but most hiring processes are still running like it’s 1995. Identity verification was designed as an afterthought. And that's exactly the gap synthetic candidates are built to exploit.
The question that TA teams must grapple with is, can your hiring process protect you?
Consider this your guide to finding out.
In this guide:
Synthetic candidate fraud looks like fake identities (stolen or augmented), deepfake video interviews, AI-generated CVs and credentials, fake LinkedIn profiles, and dodgy references that actually check out.
Since generative AI went mainstream, genuine candidates have been using it to apply faster, present better, and perform in interviews. But on the extreme side, fraud actors have been using AI to create synthetic identities that can pass through traditional processes and greenlight their access to sensitive information. Think you’re immune? Even a security firm got fooled!
You could be looking at:
Gartner predicts that by 2028, one in four candidate profiles worldwide will be fake. We’re not just talking about lone wolves – solo opportunists who are looking for an easy mark to make a quick buck. There are commercial fraud rings and state-sponsored operations looking to do serious harm.
In an era where application volumes are at record highs while hiring teams are stretched thin running clunky, fragmented hiring processes, mistakes are inevitable. The attention to detail required isn’t possible when you’re sifting through two hundred artificially enhanced resumes that all begin to look and sound the same.
Traditional hiring signals are breaking because they were designed in simpler times. Here are five common screening mistakes exposing you to fraud threats:
Hiring risk has moved earlier in hiring. The hiring process must be re-designed to catch it at the beginning.
A resilient hiring and screening process will:
Employers should explain to candidates how they define acceptable use of AI in recruitment and outline their screening and fraud detection process (including consequences) to set expectations up front.
A consistent, documented background screening process helps to standardise assessment criteria and reduce the risk of bias, but it also makes it easier to flag anomalies.
Background screening helps employers comply with relevant industry and government regulations around qualifications and conduct that are designed to protect employees, customers, workplaces, and sensitive data.
Verifying identity through authoritative data sources (like government agencies or biometrics) can more accurately flag anomalies and risks. Additionally, making sure checks are streamlined and relevant to job profiles will help meet risk and compliance needs (especially for sensitive roles).
A standard background check confirms that the name provided has the documented employment, educational, and criminal history. But that's not enough anymore. Here's what your hiring process should also include.
Document validation confirms that a presented document, like a passport or driver’s licence, is an authentic, valid, government-issued ID. This should help identify fake identity documents, but it won’t necessarily flag when an identity document is stolen.
Synthetic candidates using stolen identity documents need extra verification, by way of biometric checks (fingerprints, facial recognition / selfie) to confirm that the human candidate matches their official identification document. Biometric liveness verification can be deployed during video interviews to flag risk or use of deepfake technology.
Relying on a single source of information for your checks can expose you to fraud risks. Verifying your data across numerous sources improves the accuracy and quality of your findings. An example for qualified roles might be contacting professional licensing boards to verify certifications and currency, using savvy third-party tech that can scan and flag risk signals, and checking document metadata for creation date and edit history.
With role-based screening, you’ve developed a risk matrix for your role profiles that identifies the checks required for regulatory compliance while also considering any risk-based, role-specific checks you should run.
Employee background check software is designed with compliance and fraud protection in mind. They help organisations move from high-risk manual screening to automated validation and identity verification that plugs compliance holes, streamlines your process, and mitigates fraud risks earlier in your process.
Additionally, in a traditional screening process, most pre-employment checks are conducted once a candidate reaches the offer stage. But with modern background check software, these checks are continuously running, helping to flag fraud signals from the moment an application is submitted all the way through to onboarding.
There are three simple ways you can adjust your hiring process to strengthen your resilience to synthetic candidates:
Synthetic identities are getting easier to create and more convincing. When all you’re thinking about is a candidate exaggerating their previous experience, you aren’t going to pick up sophisticated, criminal enterprising AI fraud designed to bypass your process (at least not without some high-tech support!).
Use this guide to understand the risks in your business and adjust your hiring process to build resilience to synthetic candidate fraud.
