Background checks have become a staple of modern business, being performed, for example, before firms hire employees, before banks allow accounts to be opened, before investors give their money to businesspeople, and before people rent their resources to others through "sharing economy" type systems. For many years, the process of performing background checks has remained essentially the same, with humans performing analysis of data derived from multiple data sources, be they paper or electronic. Today, however, artificial intelligence (AI) is transforming the background check process - making it faster, more accurate, and more efficient.
I recently asked Shlomo Mirvis, CEO of Intelligo, which specializes in background checks and professional due diligence utilizing AI and machine learning, how AI is transforming the background check industry. Here are 7 ways that he shared with me:
1. Better analysis
AI and machine learning enable performing background checks with much greater efficiency than was previously possible, and with much larger dataset coverage. AI also provides the ability to analyze and match orders of magnitude more data points than was done in the past. The same availability of extremely large amounts of information that was often a liability to traditional background checkers - overwhelming them with irrelevant items - is a tremendous asset to AI. Additionally, AI assists with the identification of connections and patterns between different data elements - something that is difficult, if not impossible, when employing traditional background check processes and technology.
2. Better understanding of various risks
AI and machine learning algorithms can retrieve and profile companies and other organizations with which a person is directly or indirectly affiliated - thereby allowing hiring firms to develop a better understanding of any potential conflicts of interest or negative behavior patterns. As such, AI can also conduct various forms of regulatory and legal analysis on a job candidate - a process that has historically been difficult to perform.
3. Focusing attention on the right data points
Because of the availability of large amounts of data, many traditional background checks produce huge reports. AI can help companies pick out the relevant insights and actionable points from data mountains - increasing their odds of finding the right "needles in the haystack," rather than being overwhelmed by staggering amounts of information. AI can also remove duplicate alerts and reduce false positives in reports.
4. Much greater speed
AI greatly speeds up the process of performing background checks - which is good for both job candidates and hiring companies. Automation of search and analysis procedures, for example, can sometimes condense the delivery time for reports from as much as 10 business days to one hour. Furthermore, because AI can pick out the most relevant data nuggets and help companies draw proper conclusions (as described in item 3 above), AI effectively encourages a movement from lengthy reports to concise summaries, which also improves efficiency and reduces the amount of time humans need to spend on the background check process.
5. Keeping reports current
One of the shortcomings of traditional background checks is that they have a short lifespan - the day after a check is completed, the information starts to age, and the report loses its relevance due to potentially outdated information. AI introduces the ability to continuously assess and analyze a vast corpus of data to ensure that checks remain current, and that red flags on individuals and companies are uncovered in real time.
6. Utilizing data from around the world
AI can check data sources that traditional background checkers may be unable to utilize. For example, AI may be able to pull and automatically process records in numerous languages from countries across the globe - a process which human-based analyzers often find difficult, if not impossible.
7. More granular risk analysis and scores
AI can produce risk scores far more easily than can manual processes - so, rather than simply producing a yes-no decision or a single score, AI can tell a company of a person's risk level in multiple areas, helping hiring managers make better informed decisions.