How to Mitigate Risk During M&As with AI
With over a decade’s experience in corporate intelligence, John Cushing, CEO and Founder of Qynn discusses below how legal professionals can mitigate these challenges and reduce risk during the M&A process through harnessing automation and Artificial Intelligence.
It’s well known that gathering corporate intelligence during an M&A is a long process that requires extensive knowledge of the companies’ history; including background checks on all directors within the businesses. Yet, while there are over 17 million directors in the UK, 99% of which are associated with the SME market – which itself accounts for 99% of UK GDP – information on the performance of these directors is either disparate at best or simply doesn’t exist.
The same goes for virtually every other essential element of due diligence during an M&A; from creating a complete picture of company group structures, to that of shareholders and assets. While crucial for ensuring the success of M&A transactions, corporate intelligence is notoriously lacking; often causing the entire due diligence process to take significantly longer than necessary, running up thousands of pounds in legal bills. Not to mention the serious risk that is run by making decisions based on incomplete or incorrect information.
Research from Accenture has shown that 48 percent of M&As are now triggered by the need for next-generation technology and 39 percent by the desire to acquire new digital capabilities. Given this, it seems bizarre that the corporate intelligence required for proper due diligence is stuck in the analogue age. Here we will delve into how the risks involved in M&As can be successfully mitigated through harnessing Artificial Intelligence (AI) software.
Avoiding potential write-downs post-transaction and hidden liabilities is vital to an M&As’ success. In the UK, a contract to buy or sell a company is founded in the ‘buyer beware’ principle; meaning it is the buyer’s responsibility to ensure they are happy with what they are buying. As research from the Harvard Business Review has shown, the root cause of the majority of M&A failures is that too many executives don’t put enough detailed focus on the evaluation process that underlies these deals.
The root cause of the majority of M&A failures is that too many executives don’t put enough detailed focus on the evaluation process that underlies these deals.
The use of data analytics and AI software can rapidly reduce the amount of time it takes to review vast amounts of both structured and unstructured information. The ability to search an unlimited number of contracts and internal corporate information, as well as social media posts and company reviews, helps present important issues to legal teams which would otherwise have been overlooked. This in turn can quickly highlight any potential red flags during the reputational and commercial due diligence stage. Through harnessing AI software, human efforts are streamlined without impacting accuracy.
Risk surrounding compliance is particularly high during the acquisition process and here utilizing AI can also support in mitigating potential risk. Sophisticated AI algorithms are able to analyse data which is not traditionally reviewed as part of the process, such as the personal background of directors on the company board. This could include public records, social media or links to other companies where they have held or currently hold the position of director. The insight gained from this analysis can be crucial given the range of compliance liabilities both in the UK and overseas.
In a similar vein, the use of AI software can also lead to the inclusion of online company reviews from the likes of Glassdoor and LinkedIn during the due diligence process. Through analyzing this data, a fuller picture of the company’s reputation with its customers can be created. If required, a plan can be established for mitigating any issues identified that could reduce value post M&A.
During the negotiation phase, AI algorithms can also provide invaluable insights thanks to their ability to pull out key dates, timelines and prices buried within complex clauses. Not only does this reduce the burden on legal professionals, it is also beneficial when contracts cover a wide variety of subjects; as it enables legal counsel to quickly dissect information from across multiple business areas. This can mitigate the risk of not having all variables to hand while negotiating, which could have otherwise resulted in less than favourable sale terms.
As the use of AI algorithms and data analysis becomes more widespread across enterprise, those who delay in harnessing its benefits will be at risk of unsuccessful M&As – whether through unfavourable sale terms or the discovery of hidden liabilities that lead to write-downs. AI software provides legal professionals with the ability to mitigate many of the risks involved, and shouldn’t be overlooked in favour of sticking with the status quo.
