How Technology Is Changing Background Screening Process for Good

How Technology Is Changing Background Screening Process

As technology continues to impact several vagaries of business worldwide; Background Screening, one of the integral parts of human resources has joined the bandwagon for good. It only makes sense when one gets to witness how technology firms like Intelligo, an Israeli Business Intelligence start-up is harping heavy on the use of Machine Learning (ML) and Artificial Intelligence (AI) to embark on almost ninety percent accuracy for the process. Precisely, they make use of a model driven primarily by SaaS for due diligence, something that’s integral to all background screening process. The model is strategically named “Clarity” which seeks to deliver fast results making use of ML, AI as well as text analytics.

In the past ten years, there has been a massive increase in recruiting shenanigans as candidates manage to slip past the background check, without raising an alarm. When you take compliance and regulatory changes into account, the need for the hour becomes more pertinent.

There are still a few countries, like India for instance, where the penetration rate for background screening in the industry is at the lowest levels. However, only tech can alter such shortcomings and turn around things in a befitting manner. Here’s a look at six such ways technology is changing the ground for dirt-digging background checks for organizations at large.

Speed Is of Paramount Concern

In majority of cases, where background screening is involved, speed of the process plays a crucial role. Sometimes, due to lack of speed and outdated technology, the background checking process of a candidate goes on for over days, even after the joining and onboarding process is complete only to come out with dissatisfied results, resulting the job and the company in jeopardy. Thanks to AI, situations like these are jarred dreams of the past. With AI in picture, prominent organizations have now resorted to a digital environment and minimal use of pen and paper, thus opening up avenues to work and process a massive amount of data in the shortest possible time.

In other words, background checks are now more concise and insightful and things are being worked at a pace that human limbs can seldom claim to achieve. A few years back Software firm Vervoe came up with an ingenious platform that made use of ML in an effective way to predict candidate skillsets thus automating the entire employee verification on background check process. The algorithm offered a unique perspective of multilayered approach where individual candidate feedback and employer preferences were tallied and matched to hire the best talent in town. With such ML algorithms in place, employers are now at liberty to evaluate no less than 10,000 profiles in one go, thus realizing the goals of scalable requirement across multiple verticals.

Read More: Why Brands Need to Own Their Technology and Data Assets

Insightful Analysis That Impacts Results

Both AI and ML working together has redefined the way employee verification checks were conducted in the past. Not only the coverage of dataset is wider compared to what it was before, but the incorporation of multiple ranges of data points has also made it possible to work and function within a de-cluttered scenario. In other words, recognizing trends, patterns and connections have now become more seamless helping organizations take an informed decision without having to depend on people-oriented research.

How Technology Is Changing Background Screening Process for Good

Handling Inherent Risks

Mapping of possible affiliations, intersections and links for any employee considering recruitment in a particular company has now become easy with AI operated systems in place. Thus, any suspicious activity now comes into notice more readily and helps an organization flung a wider net and asses all inherent risks involved with the hiring process. Thus, the legal and regulatory bulwarks remain protected, no matter what the ill or the odds are.

Shifting Focus on Crucial Data Points

Background screening demands you work with truckload of data from several different sources, including the past history of the candidate and professional streams. ML helps to focus on working with important data points to cleanse, analyze and interpret candidate information, thus ousting duplication and harboring resourceful insights harboring in a concentrated manner.

Real-Time Analysis

With AI, it has now become possible to address any such shortcoming which otherwise could be overlooked in a traditional employee background screening process. Apart from relying on historical data, AI helps one to browse through multiple databases and keep it updated with the latest inclusions and modifications if any.

In this context, you can use a tool like IDVerity designed by Cisive that can readily perform real-time background screening of a candidate by resorting to forensic evaluation by authenticating govt ID and comparing the same with candidate supplied information and documents. The tool is powered by AI and has a special “liveliness detection” along with live verification and facial recognition that takes background screening to a whole new level.

How Technology Is Changing Background Screening Process for Good

Data That’s Available Globally

With the help of AI, organizations have been able to run background screening processes for a plethora of sites, locations, and streams in tandem. This has helped firms hire the right talent with genuine background for remote working and work from home hire as well. Taking a drift from traditional employee background screening process, the advent of AI has made it possible to look past a pen and paper powered process that was mostly managed by third-party agencies incurring additional cost and long turnaround time.

Furthermore, AI has managed to garner a wholesome experience to help stimulate the tough process of an analyst while they work towards locating meaningful connections, seeking output and also raise red flags as and when required. Any such data that is collectively gathered from social media, legal records, adverse media, and blacklists are all analyses via an algorithm that help companies reach an unbiased decision with their hiring.

Wrap Up

These days, tech firms along with proprietary databases and delivery platforms facilitate companies to exist within an environ that bespeak trust and transact with confidence. In days to come, technology advancements will help employers to effectively filter individuals who pose a threat to an organization or put a business in jeopardy.

Read More: Shaped by AI, the Future of Work Sees Soft Skills and Creativity as Essential

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