This scenario may seem all too familiar: your firm is working on a new deal and hundreds of documents are dumped into a virtual data room. Many aren’t correctly identified. Some have no connection to the matter at hand. There may be five copies of the same document, all of which are missing the same page. Attorneys are tasked with manually reviewing contracts to extract relevant information — they may spend days trying to get things into a general order.
Too often in this scenario, due diligence runs longer than expected, dragging out the deal process and taking away valuable time advising clients. The average time to close an M&A deal is estimated to have increased by over 30% over the past decade. Younger attorneys are at particular risk of burning out by spending so many hours in document verification, while burdened with fears of committing a deal-threatening error.
This doesn’t have to be the case. Law firms can more adeptly handle the ever-growing volume and complexity of M&A documents by supplementing attorneys’ skills with document review technology based on artificial intelligence (AI). Automating substantial parts of due diligence enables law firms to guide their clients through unforeseen complexities, reduce their risk, and close their deals faster.
What are the steps in an M&A due diligence process?
There are three major steps when undertaking due diligence reviews:
● Identify and organize
● Document review to surface risk
● Report and advise
Using AI-driven document analysis for each step helps the process go more smoothly and accurately, enabling clients to take proactive steps to reduce any risks in their transactions.
Step 1. Identify and organize
Start with the basics. What types of documents are in the virtual data room? Junior attorneys can get weighed down with document review, putting them at risk of performing at the top of their game.
Automating document identification by using software that classifies documents via factors such as date, type — such as invoices, contracts, regulatory documents, etc. — and language makes document intake more efficient.
Next, a law firm needs to organize them for review and analysis. Using AI documentation, a lawyer can upload large volumes of documents exponentially faster than traditional methods. After classifying, documents can be assigned to particular reviewers and security permissions can be applied.
Firms can employ pre-set parameters to quickly organize documents. These custom-made analysis settings address the needs of a specific deal. For example, if a seller’s business is largely in government work, document analysis software can organize documents into local, state, and federal-level contracts, and then further differentiate them via document type, value, and contract length.
Step 2. Document review to surface risk
Once all documents are organized, a law firm must fully assess them with a sharp eye for potential deal risk. Take, for example, language found in non-compete agreements and exclusivity clauses in employee contracts. There could be potential threats from an ongoing lawsuit or from unforeseen tax obligations — among many other factors.
In the past, there was a degree of tradeoff at this stage of the due diligence process. Did a firm urge its attorneys to get through document review as fast as they reasonably could, or did it task them with intensive analysis that would likely delay the deal? Neither choice was ideal. Artificial intelligence document analysis frees a lawyer from having to make that decision.
Automated document review is based on AI and machine learning, which can detect significant clauses from deep within a document where risk could be buried. Within seconds, a lawyer could generate a report tallying up potential red flags and classify them like this:
● Red flags sorted into categories: Commercial contracts, litigation, employee contracts, tax documents, financial statements
● Risk-stratified red flags: Flagged documents ranked low, medium, or high
Step 3. Report and advise
How should a client handle risks associated with its deal? Your firm can show where the most pressing risk lies and advise on how to address and reduce it. This is the type of advisory that attorneys should spend their time on: it’s truly value-added legal work, not just paperwork. By conducting more thorough risk analyses than before, in a fraction of the time, law firms improve the quality of their client conversations.
Preparing a quality risk report is central to this step of the process. Using an AI-generated, easily digestible document analysis tool like Document Intelligence gives clarity to client advisory and enables a law firm to scale its due diligence projects, thus creating a more comprehensive risk analysis.
How do you provide value in M&A processes?
Value today comes from devising innovative strategies and risk analyses for clients. After all, the deal market is more challenging than it has been for much of the past decade. There’s more volatility, more of which is due to unforeseen external factors. Deals have to be done faster and they have to be done smarter, with risk minimized.
Quality M&A due diligence review is core to the success of a client’s deal. A law firm can differentiate itself from the competition via the intelligent use of automated document review technology. By having forensic-level document analysis done at high speed, attorneys can give clients a bigger, sharper picture of the challenges they face.