From Amazon to Intel: How AI is used in business
The past few years have seen an explosion of business applications for AI (artificial intelligence). The global market for AI in 2021 was US$327.5 billion. The same year saw over $20 billion in funding for AI-based startups.
AI is big business, both for those selling AI-based services and for companies that are integrating those services into their process.
AI in business falls into one of three categories:
- Process automation allows businesses to streamline basic processes that might otherwise have required excessive manpower. For example, financial services such as billing.
- Cognitive insight gives businesses the ability to predict what a customer might buy. The most common example is the Amazon function that suggests products based on past purchases.
- Cognitive engagement enables businesses to offer personalized, responsive communications through automation. Chatbots are the most frequently used application.
A vote of confidence: Executives endorse AI
As AI has found applications in industries as varied as high tech, telecommunications, financial services, healthcare, and pharmaceutical, executives in all industries are increasingly becoming comfortable with the idea of integrating artificial intelligence into their business.
In a survey by MIT Sloan Management Review, over 84% of business executives said that they think that AI will help them gain a competitive edge in their niche. Harvard Business Review found that 75% of executives in companies that have adopted AI believed that using AI technology would substantially transform their companies within the next three years.
As this versatile technology has the potential to impact many processes, executives are looking to AI to enhance their business in a variety of ways. One survey found that 35% of executives anticipated that AI would help them make better business decisions, while 36% were looking to optimize their internal business operations.
The new frontier: AI in due diligence
With so many applications for AI-based technology, AI is being deployed to automate tasks that were once considered the sole preserve of human administrators. Due diligence background checks performed on either the company or an individual are one such area.
With vast amounts of data now available in the public domain, performing background checks requires sifting through a vast quantity of information and correctly assessing the results. The capacity to analyze thousands of data points in a matter of minutes clearly gives AI the edge over human analysts, but it is more than speed that is allowing AI-based background checks to disrupt the due diligence market.
Finding the right needle in the haystack: AI pinpoints the correct individual
Identifying the correct individual is an essential part of performing background checks. But what happens when the individual has a very common name, such as John Adam Thompson III? Human analysts are hard-pressed to distinguish the records of the person in question from their similarly named relatives. Producing a background check suddenly transforms into a task wildly susceptible to the prospect of misleading or blatantly incorrect findings via human error.
Identifying the correct individual is an essential part of performing background checks. But what happens when the individual has a very common name?
An analyst working on the example of the Thompson report would have searched his legal records in the counties Thompson is associated with, finding a few speeding tickets and nothing more. The analyst also would have discovered that Thompson’s cousin of the same name was involved in many lawsuits. Most good analysts would be able to distinguish between the two. However, with the combined powers of AI and experienced analysts on the case, a bigger story was uncovered.
Amidst the many files associated with Thompson’s similarly named relatives, a case of insider trading was discovered relating to the “correct” John Adam Thompson. The intricate structure of the algorithm had the capacity to conduct an exhaustive search on all of Thompson’s related addresses – not only his associated counties – thus singling out his connection to a certain limited liability company that was implicated in the insider trading case.
Screening individuals for potential risk requires the utmost attention to detail alongside the ability to review copious amounts of data; a challenge which is inevitably subject to human error but suited perfectly for the use of artificial intelligence.
Seeing the woods for the trees: AI removes confirmation bias
Humans also fall prey to psychological biases (such as confirmation bias and the illusion of control) which AI systems are able to successfully overcome. Often, without being cognizant of it, analysts will make assumptions and fit all corresponding events into that story. When it comes to comprehensive background checks, confirmation bias is an unavoidable psychological anomaly, even for the most seasoned research analyst.
For instance, one of the most important elements of the background check process is pinpointing legal records that are relevant to the subject of the search. A research analyst will comb through large amounts of data to duly match records that correspond to the individual in question. Intermittently, analysts come across lawsuits that list modified versions of a subject’s name as a party. Through additional identifying factors, an analyst can determine if the modified variations of the individual’s name correspond, in fact, to the same individual they are researching. If all signs point to it being the same person, analysts should re-run the modified name through all of the corresponding databases.
However, often confirmation bias comes into play. Without being consciously aware, the analyst may often reject the idea that this modified name is an alias for the fund or portfolio manager being researched. Instead, they will choose to stick with the information that confirms the story they have already created for the subject in question.
This vulnerability highlights the fundamental difference between human scrutiny and automated analysis. The algorithm permeates through the ocean of data that exists in cyberspace and extracts data points that it has learned to be important, relevant, and meaningful, without the psychological pitfalls facing a human analyst. The analysis is therefore far-reaching and pertinent, providing the decision-maker with a larger quantity of data as well as a more comprehensive review in order to make an informed, optimal decision.
Read more about the dangers of confirmation bias in due diligence >>
Beyond the office: AI overcomes physical restraints
Not only does AI assist in subduing psychological interferences, but it also overcomes physical restraints. Due to the circumstances of human limitations, companies struggle with maximizing the work that can be accomplished within a certain time frame. On the other hand, AI automates arduous tasks and repetitive duties, thus ensuring time is used more productively and efficiently.
A study by PwC showed that 54% of executives reported a dramatic increase in productivity after implementing technologies that leverage artificial intelligence. In fact, an analysis by Deloitte suggests that an analyst working in conjunction with an AI system could save as much as 364 hours a year. For operational due diligence managers, time is of the essence as other teams are awaiting their input regarding investment decisions.
For example, the Intelligo Clarity platform is able to produce comprehensive background checks at a rate multiple times faster than industry standards by leveraging AI data analysis.
AI’s sophisticated algorithms are designed to derive accurate data, far surpassing the proficiency of manual research alone.
It is not enough for automation to expedite time-saving output if it isn’t supplemented with a higher degree of accuracy. Precision provides a competitive advantage on those operating with AI-powered systems. One of the many advantages of automated, artificial intelligence systems is the ability to sift through stacks of data and scrupulously extract relevant information. AI’s sophisticated algorithms are designed to derive accurate data, far surpassing the proficiency of manual research alone.
Another benefit of using AI in conducting background checks is its ability to interpret data above human limitations. Unlike human beings, AI can comprehend information in hundreds of different languages, as well as process dialogues and semantics. In addition, AI can use facial and fingerprint recognition technology, or search aliases to identify individuals who have left both personal and professional footprints across the globe. This is especially relevant with individuals who have common names and thus identification matching is needed to verify the person under analysis.
Key Takeaways
Artificial Intelligence is enhancing processes throughout the business world. In the areas of due diligence screening and background checks, the impact is vast. Using millions of data points from various data structure forms around the world, AI can deliver accurate results in minutes – sometimes even seconds – essentially beating human analysts to the punch on the retrieval and analysis of information. AI offers a new level of accuracy, and therefore trust, in background checks.
