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Chapter 3.8 | Automated Working & A.I (Artificial Intelligence)

The Value of Automated Working

With a Smart M&A Platform, automated working capabilities allow teams to spend less time reporting and more time working on the things that matter most. For example, sophisticated dashboard reports with chart & graph functionality and linked reports and drill-downs can be configured and updated with a few clicks – making reporting on the status of a deal a process that takes minutes, rather than hours. Additionally, reports can be scheduled for automatic emailing to deal team members or archiving – making stressful preparation for the Monday morning progress meeting a thing of the past.

The Application of Artificial Intelligence in M&A

M&A is time-consuming and resource heavy – typically involving the requesting, review, analysis and summarizing of 1000s of documents. For particularly large-scale deals, the volume of information can be so burdensome that some documents may be given no more than a high-level glance (meaning that a significant issue may go uncovered). To increase efficiency, reduce costs and lessen the risk of key issues not being flagged, organizations are increasingly incorporating the A.I functionality offered by a Smart M&A platform into their knowledge work. 

Using Artificial Intelligence for Information Processing

In an M&A context, A.I can offer the following functionality:

  • Natural language processing can help with the review of a large number of contracts in an automated way – with the ability to flag and categorize clauses (based on user specifications – e.g. flag all change of control clauses);
  • Predict issues and risks across due diligence based on the business case in question – e.g. in the example of a tech acquisition in France, a Smart M&A Platform can suggest specific risks a deal team should be alive to across due diligence and predict issues that may be encountered (and even suggest mitigating action);
  • Suggest potential synergies based on the business case in question – e.g. where procurement savings may be achieved;
  • Auto-assign tags to issues as they are added to the Issues Log and improve accuracy over-time via re-enforced machine learning capabilities;
  • Provide an indicative valuation of a target based on comparable company analysis and similar deals captured within the Platform;
  • Suggest additional acquisition targets based on the profile of targets currently sitting in the pipeline.