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6 Ways AI and ML are Improving Employee Background Verification

Did you know that Israeli startup, Intelligo, is using AI and ML to make Employee Background Verification 90% accurate? Not just this, advanced technologies can be used to perform protracted processes, in a matter of seconds. With boundless potential and very real on-ground benefits, this could change how you screen your candidates, for good.

At a time when security concerns and cyber threats are plaguing organizations across the global, employee background verification is more important than ever before.

Every recruiter must now carefully scrutinize an applicant’s past records, personal information, previous experience and criminal records (if any). This helps build a greater sense of trust and reliability, in line with contemporary regulatory requirements.

Traditional employee background verification process was a manual and paper-driven process, managed by external agencies, with costs and long timelines. As with other facets of the HR function, artificial intelligence (AI) is transforming this space for good too. Employee background verification is now automated and much more efficient.

Also read: Selecting the Right Background Verification Partner

Here are 6 ways in which AI is changing the game for the employee background verification industry, and for employers as well.

  1. The need for speed – A no-brainer, AI and ML make the employee background verification process faster, smarter, and more effective.
    By moving away from manual and paper-based systems, these technologies can go through huge amounts of data rapidly, offering relevant insights and concise summaries, at a pace that’s impossible for humans to achieve.
    Recently, Vervoe introduced a hiring platform that uses ML to screen and predict skill sets, in addition to automating employee background verification. “Every candidate is different, and so is every employer,” Vervoe Co-Founder and CTO David Weinberg said, “These new AI algorithms offer a totally unique, multilayered approach, allowing bespoke feedback about the candidates and preferences of each individual employer.
    The machine-learning prediction also improves each time an employer manually grades a Talent Trial, increasing the accuracy well beyond 83%. Employers are now able to evaluate 10,000 candidates at the same time it takes to evaluate one, allowing for scalable recruitment.”
  2. Richer analysis – AI and Machine learning (ML) helps to conduct employee background verification and checks on a whole new level. The dataset covered is wider than ever before, incorporating multiple data points, fine-tuning what’s required, and removing external clutter – making the identification of possible connections, patterns, and trends, much more seamless.
  3. Deeper risks evaluation – AI and ML offer algorithms that can acutely map possible affiliations, links, and intersections of any potential employee with suspicious activity, spreading the net far wider and assessing a variety of risks. As a result, a company’s security, regulatory, and legal bulwarks remain protected.
  4. Redirecting focus on key data points – As mentioned, there is a huge quantum of data coming in from various sources, streams, and past histories. AL and ML help to sift through the data, cleanse, interpret, and analyze the same as part of the employee background verification process. This leads to a concentrated and focused insight gathering, removing false positives and duplications.

Also read: Employee Experience, Jobs and Skills: How AI will Impact HR

  1. Real-time analysis – AI can address an important shortcoming of traditional employee background verification – reliance on historical data. Going through documents in real time and regularly updating databases, AI helps keep the search fresh, absolutely current, and aligned with the latest movements.
    In this regard, several tools are already available. IDVerity by Cisive performs level 1 employee background verification completely in real time, forensically evaluating an applicant’s identity via authenticity validation of the government ID and comparing the same to the candidates’ photograph from their mobile device.
    The solution uses AI to verify IDs via ‘liveliness detection’, biometric facial recognition, and live verification to deliver an end-to-end employee background verification system.

Also read: Artificial Intelligence and the Future of Human Labor

  1. The global availability of the data – Today, AI has helped companies gather employee background verification data from a variety of streams, sites, and locations. This is even more important when one considers work-from-home and remote location hires. It also pulls data from social media platforms, tracking all additional digital signatures for potential employees.

Let’s consider the case of Intelligo, and its unique employee background verification capabilities.

The Israeli business intelligence firm uses a SaaS-driven model for automated due diligence and screening. The solution (called Clarity) works at an accuracy rate that’s near 90% using AI, ML, and text analytics.

What’s more, it simulates the analyst’s thought processes – locating connections, determining the meaning and raising red flags wherever necessary. Data is collected from various sources, such as social media, adverse media, blacklists, legal records, and other platforms. The algorithms study all above and help companies come to the right and the most unbiased decision.

This is the era of employee background verification technology and its enlightened application. Like every other sphere of a business, background screening will also be transformed – albeit for the better – by the incredible power of AI and ML!

source: 6 Ways AI and ML are Improving Employee Background Verification

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