Real or fake? This is a question that is relevant in all walks of life. It is now being asked with increasing urgency in professional life.
About 8% of employees pose fraud risk, says a recent report on background verification insights from IDfy, an integrated identity platform. The report analyses 2.5 million background verifications across industries in the past year.
Background checks include verification of address, qualification, experience and for criminal records. IDfy performs these checks and flags discrepancies at three levels — red, amber and green.
Companies have a reason to be concerned. “We are witnessing a spurt in employee frauds, both as a result of remote working as well as increasing personal financial pressures and pressures to perform at work,” says Jayant Saran, Partner-Forensic, Financial Advisory, Deloitte India. “These can manifest in frauds for personal gain or for furtherance of one’s business or career.”
Sector-specific details
The IDfy report finds that industries seeing the highest percentage of high-risk cases include BFSI (banking, financial services and insurance), e-commerce and staffing, at an average of 7.8%. In BFSI, address verifications and experience checks led to a large number of such red cases — 10.7% and 9.5%, respectively.
IDfy tells ET Digital that employee fraud comprises about 75% of all frauds experienced by lenders. So it is crucial to give trusted employees the responsibilities of handling large sums of cash; interacting with customers; and roles that can influence the outcomes of loans and other assets.
For the staffing and recruitment industry, it reports 15.48% of red cases due to address verification and 14.62% due to experience verifications. The report highlights the importance of reputation being built on the calibre of people hired and, hence, the criticality of ensuring dependable talent solutions.
For e-commerce, the report says 70% of checks are done on off-roll people during hiring of seasonal gig workers, specially before festivals. Address checks are again an issue at 15.25% fraud detection, given many people come to cities from far off places and some might genuinely find it difficult to provide verification or have an address before moving to the next gig.
The underlying issue
Highlighting the depth of the issue, the company says that for just Rs 10,000-12,000, you can get a set of fake experience letters, payslips and even a “pay hike” letter thrown in for good measure. It is very hard to detect these kinds of frauds unless you are working with an experienced background verification provider.
Ashok Hariharan, CEO and co-founder of IDfy, says, “Integrity and diligence in recruiting methods are critical aspects that firms must consider as we negotiate the complexity of today’s recruitment landscape.”
What actions can leaders take
The company points out that leaders need to be cognisant that risk is never static but always keeps evolving. This means senior leaders need to stay abreast of fraud trends and evolving techniques to catch them; while also ensuring existing BGV processes are not becoming stale and ineffective. This also means that they need to ensure periodic re-evaluations of employee risk, and perform background checks periodically on senior hires and those in sensitive roles.
The level of risk profiling needs to be pertinent for the role the person is being hired for — deeper checks for senior/sensitive role hires and lighter checks for others. Since a majority of the candidates are going to be marked as green, there is a need to ensure that the background check process provides for a great user experience and doesn’t leave them dissatisfied. In addition to these points, senior leaders must be alert to various employment frauds that are prevalent in the industry.
Can AI help in fraud detection?
Saran clarifies, “Our clients are paying greater attention to spends, e.g. spends where machine learning techniques are being applied to identify fraudulent claims. This is facilitated by many organisations moving to electronic expense management systems. Greater attention is being paid to automating due diligence on counterparties and vendors to identify red flags faster. These can help identify potentially bad players and possibilities of conflict of interest.”
Process mining techniques are being used to find deviations from standard operating procedures as in various processes like procurement and order to cash, says Saran. And finally, there is a greater use of AI on unstructured data, including email traffic, to identify red flags or risks relating to individual employees or elements that can impact organisations as whole. There are also industry and issue specific applications of ML and AI on data, voice and facial recognition to detect and prevent fraud. These apply across recruitment, KYC, access to sensitive premises, etc.
