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Managing your client’s M&A risk with A.I.


October 1, 2018   by Greg Meckbach


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Mergers and acquisitions come with risks for buyers, and one law firm uses machine learning to help clients manage at least some of those risks.

One risk to a buyer is when the target company has liabilities – such as taxes, polluted land or contractual obligations to employees. Transactional risk insurance – such as representations and warranties – is available from commercial insurers and can cover a buyer who takes on unexpected liabilities when acquiring another company. The market is growing, with Marsh reporting it placed 406 policies in the United States and Canada in 2017, up 45% from 280 in 2016.

Lawyers are using machine learning – a type of artificial intelligence in which computer software does something without being explicitly programmed to do so – to identify potential liabilities in contracts. AI lets computer programs learn from experience and identify patterns, Strategy Meets Action notes.

Both technologies can help with searching large volumes of documents, reports lawyer Mark Young, a partner with Cassels Brock, which advises corporations negotiating a merger.

When one firm is negotiating to buy another, the liabilities that the buyer would take on are not always obvious, Young said in an interview.

For example, some lease agreements have clauses with restrictions on when the tenant can assign a lease or how the lease terms change if there is a change of control over the tenant, Young said.

“If you are buying that tenancy, you are going to want to make sure you still have your office premises without interruption the day after closing,” Young said.

But running documents through simple keyword searches won’t always detect such risks.

“It is very infrequent that a document actually says something happens if there is a change of control. There’s a whole bunch of different ways change of control could be described in a document,” said Young. A contract might instead refer to “shareholding percentages” or “ultimate ownership” or “beneficial ownership,” for example.

AI can train document management software to look for phrases that are commonly used to describe change of control or assignment or termination of leases, Young said.

The traditional way of looking for liability risk in a merger or acquisition is to have a room full of boxes of documents, with a dozen or so people going through those documents.

Without artificial intelligence, a law firm would need articling students or new associates to read several thousand documents just to narrow it down to hundreds that would need close scrutiny by more senior lawyers, Young suggested.

AI can review documents by looking for concepts, rather than specific key words, to flag documents that might need lawyers to review them in detail,  said Young.