Beyond traditional verification: How AI is setting new standards for data-driven background checks

By: Jaibir Nihal Singh, Founder, TraqCheck

While employees are invaluable assets for every organisation, they may also contribute largely towards occupational fraud. Businesses tend to lose 5 per cent of their annual revenue owing to occupational fraud, as per the Association of Certified Fraud Examiners (ACFE) report. This is a valid indicator of why organisations, as they increase in size, need to recruit the right people to safeguard their financial success.

From theft to on-the-job violence, incorrect hiring practices present a plethora of issues that cost them inefficiency and ineffectiveness of work. This further results in a substantial decline in revenue generation. Since most financial frauds originate from within, it is thereby essential to safeguard the existing assets from the beginning. One of the most effective solutions to help organisations fulfil this objective is performing background checks.

Traditionally, background checks were performed solely by the human recruiters, posing several challenges like inconsistencies, unconscious biases and delays in the hiring process. Moreover, various candidate screening tools relied heavily on keyword matching criteria, sidelining the qualified individuals whose resumes don’t match the job description. Such challenges led to the integration of artificial intelligence (AI) in the human resources industry.

Here’s a look at some of the ways in which AI is streamlining the background check process:

Sourcing candidates

Organisations can utilise AI technology to find qualified applicants across numerous job boards and sectors, increasing recruiting efficiency. This can even help HR executives save a lot of time that they invest in searching job boards for prospects. Furthermore, AI can be used to analyse every candidate’s personality traits, talents and cultural fit, allowing employers to better understand candidates’ strengths and limitations. As a result, the hiring process becomes significantly streamlined and productive with less effort.

Utilising automated candidate selection (ATS)

An ATS system uses AI technologies like natural language processing (NLP) and machine learning to select the best applicant for the required vacancy. This system works by scanning resumes for certain keywords while evaluating every applicant’s skill set and comparing it to previous hiring practices. This helps in reducing the time and effort required by human recruiters to find the top prospects.

Identifying document forgery

With the proliferation of template farms, fabricating documents has become a viable option for fraudsters to deceive employers. However, by utilising an AI fraud detector, fake documents can be easily spotted in the screening process. As a result, organisations are saved from reputational, financial and professional risks.

Increased speed and efficiency

AI systems can process massive volumes of data at an unprecedented pace. This, in turn, leads to fast turnaround times on background checks, essential in competitive employment markets. These automated AI-focused systems can evaluate criminal records, career histories and educational backgrounds in a fraction of the time that it would take manually.

Enhanced accuracy

Human errors are not acceptable in manual background checks. By employing AI and machine learning algorithms, companies can substantially decrease the probability of errors by applying uniform criteria and tests for all applicants. These systems can detect trends and abnormalities that usually get overlooked by humans, resulting in more accurate and comprehensive background check reports.

Cost effectiveness

Most of the procedures involved in AI-focused background checks are automated. This helps organisations save money while reducing the need for extensive training. The initial investment in AI technology can be compensated by long-term cost savings and improved productivity.

Road to future

As the technologies continue to evolve, the process of background verification is poised to witness significant transformation in the future. Trends like AI-powered document verification, behavioural analysis and consistent evaluation will present potential solutions for individualised background checks across various workforce segments. According to the Markets and Markets report, the global background check market size is projected to reach USD 4174 million by 2027, owing to the integration of AI technologies in the hiring processes. While AI presents numerous advantages to the HR industry, it is imperative to remember that this technology is formed to support and not replace humans. Human cognitive skills like thinking and reasoning will remain at the forefront of the hiring process.