As recruitment becomes more tech-driven, organisations must adopt direct-source validation & data screening to stay ahead

Moonlighting is not really a grey area, it is quite black and white. The clarity must come from the organisation’s policy. Every company has a different stance. Some permit external engagements with disclosure and approval, others prohibit dual employment altogether.

Our role as verification partners is not to judge intent, but to verify facts. If an individual has had dual employment in the past, that information should be validated and reported objectively,” says Major Vibhav Kapoor, CEO, Vibrant Screen in an exclusive interaction with Bizz Buzz

With the current discrepancy rates in white-collar hiring and gig roles, what is really driving this spike in integrity risks? Is it economic pressure, candidate overconfidence, or gaps in employer screening systems?

The spike in integrity risks stems from a mix of economic pressure, employability gaps and inconsistent screening practices. We closely track hiring patterns across industries and what we are witnessing is a structural imbalance. In India, nearly 1.5 million engineers graduate each year, yet only 10-30% secure roles aligned with their skills.

Even at premier institutions like the IITs, placement rates in some cycles have been around 60%. This results in underemployment, resume gaps and mounting pressure, increasing the temptation to enhance credentials.

At the same time, rising lifestyle aspirations and financial expectations are reshaping workforce behaviour. Moonlighting, in many cases, is not rooted in misconduct but in economic cushioning. However, when transparency is absent, it shifts from a personal choice to a governance and risk concern for employers.

The responsibility does not lie solely with candidates. Organisations also create gaps by accelerating hiring, limiting verification depth, or treating background checks as a compliance formality. The way forward is balance, combining technology-led screening with thorough human verification, supported by clear policies and consistent standards. Integrity risks are rising because pressure is rising.

How has the rise of AI-generated resumes changed the verification landscape? Are you seeing more sophisticated fabrication, and how should organisations adapt without penalising genuine candidates?

AI-generated resumes have definitely made the landscape more complex. Profiles today are sharper, more aligned to job descriptions and technically very well written. But in some cases, AI is also being used to overstate roles, stretch timelines or fabricate project exposure. This has increased the difficulty in spotting discrepancies through basic checks.

Ironically, we are leveraging AI-infused technologies to detect tampering, identify inconsistencies and cross-verify data more intelligently and efficiently. AI-enabled verification allows us to move faster without compromising accuracy.

I believe we must not penalise genuine candidates who use AI responsibly for structuring or refining their resumes. The real issue is factual integrity, not presentation.

As verification professionals, we have a moral responsibility to flag red candidates based on evidence and clear discrepancies, not suspicion. The objective is to protect organisations while ensuring fairness and trust remain central to the hiring process.

In your experience, which elements of a candidate profile are most commonly manipulated today: credentials, tenure, compensation, job titles or something else entirely?

Outright fake profiles are far less common today than subtle manipulations. What we are increasingly seeing is strategic exaggeration. Tenure and job titles are among the most frequently stretched elements, extended employment dates to bridge gaps, or upgraded designations to suggest a larger scope of responsibility.

Compensation inflation is another common area, particularly in competitive sectors where salary benchmarking drives offers. We also see elective project claims, undeclared dual employment and selective omission of short stints.

As per our experience over the years and recent internal insights, nearly 4% of profiles fall into what we classify as “red cases” requiring deeper scrutiny. Among these, the top five discrepancies typically relate to tenure manipulation, inflated titles, compensation misrepresentation, overlapping employment (including moonlighting) and unverifiable project exposure.

Gig and on-demand hiring, is expanding rapidly. Is the discrepancy rate higher in these segments? If yes, why and what specific safeguards should platforms and enterprises implement?

Gig and on-demand hiring have expanded rapidly over the past few years, particularly with the rise of quick commerce and platform-led models like Amazon and Swiggy. The scale and speed of hiring have naturally increased because the ecosystem itself is built for speed.

From my experience, the discrepancy rate in gig is not necessarily higher than other segments. What changes is the context. Gig roles often involve shorter tenures and high attrition. As hiring is volume-driven, organisations sometimes limit checks to accelerate onboarding. That is where risk exposure can increase.

Smarter screening techniques should be used to mitigate risks across all roles. For blue-collar positions, robust identity validation and criminal record checks are fundamental. For white-collar and gig workers, while these checks remain important, additional focus should be placed on data security risks, potential dual employment or moonlighting, and statutory compliance, always conducted with informed consent and clear governance standards.

Fake documentation and unverifiable credentials appear to be on the rise. How are fraud tactics evolving, and what technological or process innovations are needed to stay ahead?

Fake documentation today is far more sophisticated than it was even a few years ago. It is no longer restricted to spotting poorly edited certificates.

We are seeing digitally altered documents, cloned letterheads, fabricated email domains, AI-generated reference identities and highly polished but questionable project portfolios. The shift is from obvious forgery to intelligent manipulation designed to pass surface-level checks.

To stay ahead, organisations must move beyond basic document collection. Technology-enabled verification, including database cross-checks, API integrations, digital footprint analysis and forensic screening, is essential.

Moonlighting has become a grey area, especially in hybrid and remote setups. From a risk and compliance standpoint, how should organisations balance productivity, trust and policy enforcement?

Moonlighting is not really a grey area, it is quite black and white. The clarity must come from the organisation’s policy. Every company has a different stance. Some permit external engagements with disclosure and approval; others prohibit dual employment altogether. From a risk and compliance standpoint, the key is transparency.

Our role as verification partners is not to judge intent, but to verify facts. If an individual has had dual employment in the past, that information should be validated and reported objectively. Whether it impacts the current role depends entirely on the employer’s policy, the nature of the engagement and any conflict of interest or data security risk.

Many companies still treat background verification as a final compliance checklist. What are the strategic risks of that mindset, and how should BGV be integrated earlier into the hiring lifecycle?

Treating background verification as a final compliance checklist is one of the strategic mistakes organisations make. What is even more unsettling is that some organisations consider onboarding candidates before the final BGV status is confirmed.

Background verification is not paperwork, it is risk mitigation. We don’t insure our car after an accident; we take precautions beforehand. Hiring should be viewed the same way. The purpose of BGV is to establish facts and enable informed hiring decisions.

Have you seen real cases where inadequate screening led to financial loss, reputational damage or regulatory exposure? Without naming clients, what patterns can you share that would serve as a cautionary lesson?

One common pattern that I have often noticed over the past 24+ years is over-reliance on unreliable verification sources. For example, fake certificates have been marked genuine because confirmations were obtained from unauthorised third parties instead of directly from universities or official bodies.

In other cases, HR confirmations were taken at face value from organisations that were later identified as high-risk or non-desirable employers. Surface-level green signals can sometimes mask deeper risks.

As hiring volumes surge during peak season, organisations often prioritise speed. How can they maintain rigorous screening standards without slowing down talent acquisition?

When hiring volumes surge, organisations have the pressure to move fast. Business targets don’t wait, projects can’t stall and teams need manpower. But in my experience, the real challenge is not speed, it’s how that speed is designed.

I’ve often seen organisations slow themselves down because their processes weren’t built for scale. Background verification should not begin after everything is finalised. It should run quietly in parallel, integrated with the ATS and HRMS, so momentum is never lost.

Risk-based approach is critical. Not every role carries the same exposure. A warehouse associate and a data-privileged analyst cannot be screened with a one-size-fits-all model. Intelligent document validation, API-led source checks and automated workflows allow us to move fast without cutting corners.

Looking ahead, how do you see recruitment integrity evolving over the next three to five years? What should HR leaders and CXOs start preparing for today to build a more resilient hiring ecosystem?

Recruitment integrity over the next three to five years will become far more technology-driven and risk-aware. AI-led fabrication is only going to get smarter from refined resume manipulation to digitally engineered credentials that can pass basic scrutiny. Surface-level checks will simply not be enough.

Organisations will need direct-source validation, data-backed screening and stronger cross-verification frameworks to stay ahead.

I also see verification moving beyond a one-time, pre-joining activity. For sensitive roles, especially those involving data access or financial authority, continuous or periodic validation will become the norm.

For HR leaders and CXOs, the preparation starts now. Integrity must be embedded into the hiring lifecycle, not added at the end as compliance. Invest in scalable, tech-enabled verification frameworks. Integrate screening seamlessly into hiring workflows. Most importantly, adopt a risk-based mindset.