May 19, 2022 | Case Study
Clifford Chance is one of the world’s pre-eminent law firms. Based in London, it is one of the ten largest law firms in the world both by number of lawyers and revenue.
When reviewing documents in a data room during a sale or purchase process, legal advisors traditionally conduct a limited sweep of a sample of documents. In a typical M&A deal, they are constrained by the amount of documentation, which is time-consuming and adds costs in terms of lawyers’ time to the process.
The concept of using a limited sample of data in a due diligence process is well-established, but it is also fraught with risk in case a crucial element is missed that the acquiring company may come to regret.
Machine learning technology is now being used to read large amounts of documents and recognize certain legal concepts.
Nigel Wellings, co-head of the corporate practice at Clifford Chance in London, says it can save valuable time and costs. “Machine learning tools assist hugely in preparing or reviewing first drafts; but currently they are limited to the more standard documentation. One example is helping to automate the mark-up of a standard confidentiality agreement letter that meets the requirements of the British Venture Capital Association.”
Using tech for best delivery
The use of AI can save valuable time in the due diligence process particularly at a time when deals take longer to close due to regulatory reviews. It also frees up senior M&A advisors to work on the more complex aspects of the deal.
AI is useful when reviewing a large number of contracts that are similar and can reduce transaction costs, but it is no substitute for human intervention as the deal process advances, according to Mark Dean, a senior legal technology advisor at Clifford Chance: “AI won’t do the job for you. M&A deals have a degree of standardization, but each deal also has its own complexities and challenges.”
Those complexities increase on big cross-border deals. There, the emphasis is on using technology to improve workflow and deal management. “The focus of our technology effort in M&A is on ‘best delivery’ because on big cross-border deals it’s important to work as seamlessly as possible,” says Dean. “Using tailored workflow systems is more efficient than email, which we try to avoid on M&A deals because it creates bottlenecks and information overload.”
Becoming embedded in due diligence
Law firms are increasingly adopting machine learning to increase the speed and depth of the due diligence they can conduct on deals. This reduces the burden at all levels of the organization, with hard-pressed junior associates freed up from repetitive manual tasks such as document review and data entry. There is also a cost benefit in terms of reducing lawyer time.
AI is still in its infancy and is best suited to high-volume standardized tasks, but it is becoming embedded in the due diligence process, in the same way that virtual data rooms did a decade ago.
“There’s a lot of scope for technology to improve the M&A process in other ways,” says Wellings. “For example, completion and signing meetings that are run remotely still rely largely on email, rather than deal room technology, as parties are more comfortable with that method of reviewing final form documents. That’s something that could be refined in the coming years.”
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