Can AI Tools Accurately Detect Fake Candidates in Public Sector Job Postings?
Eleanor Hecks is a senior HR and business writer at Designerly Magazine. After growing up with parents who both worked in the public sector, Eleanor is passionate about specifically applying her insights to those in the government and education professions. You can connect with her on LinkedIn or follow Designerly on X for business and design insights.
The job market is tougher than ever as more candidates compete for fewer positions. With increased competition comes an influx of fraudulent applications. While some candidates have embellished a skill or two or fudged their GPA, others fabricate an entire application. This unfortunate phenomenon causes hiring companies a long list of problems, such as wasted resources and increased hiring costs.
As a company currently recruiting, artificial intelligence (AI) could be the solution to spotting these scams. However, it may also come with inconsistencies when indicating a fake candidate. Knowing how it works and the potential downsides could help you avoid them.
How AI Can Spot Fake Candidates
Emmanuel Toutain, CEO of Terefic — a fraud detection software — says that 10%-30% of job applicants are fake. Research has also shown that lying on resumes has increased by 19% since 2022. This increase in fraudulent applications is a worrying factor for many hiring companies.
However, AI tools can save time and money by scanning through large volumes of applications to choose qualified candidates and filter out potential fraud based on a fixed set of criteria. It uses various data points within a resume — such as employment history, education credentials and skills — to spot inconsistencies.
For example, some candidates may inflate their employment history or qualifications on their resume far beyond their actual abilities to meet job requirements. AI tools can, for example, flag gaps in employment history or inconsistencies in qualifications between a candidate’s resume and profiles like their LinkedIn.
False candidates may also use their inflated experience to ask for higher salaries than their qualifications might merit. AI tools can help employers spot inconsistencies between listed salaries and educational qualifications.
For example, the median salary for those who have a bachelor’s degree is $75,000, while those with an MBA make around $125,000. An AI tool could cross-reference salary expectations with the expected range for these degree types and flag any requested salaries that are significantly higher than these averages. If the candidate doesn’t have the work experience to merit this discrepancy, the tool could filter out the applicant altogether or mark the applicant for a manual review.
The Downside of Using AI to Spot Fake Candidates
AI offers opportunities to automate the selection process of qualified candidates. Yet, one major concern of these tools is filtering out some of the top candidates for the job. Some instances involve AI excluding applicants based on their age from the birth date they list. Other issues arise with the data used to train resume screeners.
For example, one firm trained its AI screener on the resumes of current employees and gave extra points to candidates who listed hobbies associated with more successful staff, typically men. This would include hobbies such as baseball or basketball. Conversely, those who mentioned hobbies like softball — often associated with women — were downgraded.
AI presents issues in biases, leading to an unfair advantage for certain candidates. It also leads to a missed opportunity for companies to hire top talent in a competitive job market era. Researchers expect labor shortages to rise, especially as retirees will increase by 40% by 2050. Leaders must find a way to apply AI ethically in a way that helps them make fairer decisions in hiring long-term, successful employees.
AI presents issues in biases, leading to an unfair advantage for certain candidates.
ELEANOR HECKS
How to Manually Assess Applications for Fake Candidates
The best way to move forward is to implement AI tools with human intervention. Recruiters must also use their judgment during screening to reap the full benefits of technological and manual assessments.
The Resume Indicates Keyword Stuffing
Many candidates know that resumes must pass through applicant tracking systems (ATS). Therefore, they will use keywords to ensure their resumes stand out. However, fake candidates often go overboard, overselling themselves with excessive keywords.
This tactic can be a red flag. A resume overly packed with buzzwords suggests an attempt to game the system. Double-checking resumes can spot these inconsistencies, and if something feels off, a closer look is warranted to verify its authenticity.
Cross-Confirm Resume Details
Cross-referencing is another effective way to handle applications with potential fake candidates. For instance, a resume could be full of specific details that do not align with a candidate’s professional profile on LinkedIn. Many users maintain detailed profiles on professional networking sites that can be a reliable source for verifying employment history, education and endorsements.
Comparing their profile information can help you spot inconsistencies. For instance, the candidate could be fake if they say they were self-employed without further context. Cross-confirming these details ensures the candidate has real experience that is aligned with the job description.
Incorrect Work History Dates
Fake candidates try to inflate their professional experience by falsifying the dates of their previous employment. They might list jobs they never held or extend the duration of their actual employment to appear more experienced.
To spot a fake applicant, you must double-check the dates on their resume. Look for overlapping employment periods that seem suspicious. Verifying these details with previous employers can confirm the candidate’s work history and ensure you hire a qualified candidate.
Balancing AI and Human Efforts in Recruitment
AI tools can be extremely useful for detecting fake candidates, but they have some inconsistencies. It is important to manually check applications to ensure a fair and thorough hiring process. By balancing technology and human intuition, hiring companies can ensure they consider only the most qualified candidates.
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