M&A: Using AI on SALE MANDATES
Generative AI can be utilised throughout the deal process, and in this article, we will explain how you can leverage FREE, off-the-shelf tools to enhance your work. We will be using Google Gemini for our examples, but ChatGPT or other Generative AI tools will produce similar results.
This article is ideal for those who are relatively new to AI, providing a solid foundation of use cases in mergers and acquisitions. Be sure to explore our blog afterwards, where you'll find more detailed articles that delve into more complex software and innovative AI solutions designed to make your work life easier.
STAGE 1 - the pitch
Before you begin working on the deal, you will often need to pitch to the potential client in order to secure the project. From my experience, the Partner in the team will typically ask one of the junior members (usually an Associate or Executive) to spend a day or so compiling a research document, as well as preparing a presentation.
There are numerous ways in which this process can be streamlined using Generative AI:
Financial Statement Analysis
AI research models are highly effective at analysing financial statements, identifying risks, and spotting trends. To begin, extract the PDF statement from your usual source (e.g. Companies House, your company’s internal database). Then, upload the document to the AI platform. In your prompt, specify what you would like the Generative AI to do and provide some context regarding your objectives. This context will help the AI generate a more relevant and tailored response. The more detailed and specific the prompt, the better the output will be.
2. Industry Research
Another key element of pitch research is understanding the industry space. For instance, if you want to examine the Waste Management sector in the UK, this is the type of report AI can generate. (The response is significantly longer than the screenshot provided.) For the purpose of this article, we’ve included only the first part of the report:
Everyone appreciates a graph to break up the monotony of text. Therefore, I’ve asked the Generative AI to create a visualisation using publicly available data:
stage 2 - buyer research
Once you've secured your client, the next step is to find a buyer! I would recommend conducting separate searches for different buyer pools, specifying criteria such as:
Location
Industry sector
Size
I can personally vouch for Biffa as an acquisitive buyer, having recently sold a business to them! It’s always reassuring to see AI reflecting what’s happening in the market.
stage 3 - IM Preparation
Each and every IM is different, a CF advisor may collate a long form document of 60 pages, while a broker produces a short-form 15 page data pack.
My point is that I can’t provide a one-size-fits-all approach to how AI will assist with IM preparation (unless you build a CustomGPT, but that’s another article in itself!!)
There are some elements that I would expect to see in an IM that GenAI can easily collate for you:
Business Overview
Financial Summary
Market Position
Who are their competitors?
For the business overview, you could ask the AI to scan the companies website, and social media platforms and extract out all the key information on operations. Here’s what a very basic prompt can get you:
I’ve already shown you how to conduct financial statement analysis, and industry research in this article, so (to make sure I don’t bore you), let’s move onto to the next section!
Stage 4 - redacting pii out of info for the data room
Gemini isn’t very helpful with this, but ChatGPT will redact out information you request. Be mindful that it may be against your companies data security policy to be sharing documents containing personal information with AI applications!
section 5 - decoding legal documents
I really don’t like it when a lawyer shares their first draft of the Share Purchase Agreement, and certain clauses contain very fancy language (often Latin too!), making it time-consuming to decode each one.
What I do now is chuck the clauses that aren’t black and white into GenAI and ask for a simple explanation of their implications. This way, I can start forming my thoughts on the clause quickly, and most likely suggest some amendments!
I would like to stress that this article shows some of the main use cases in M&A. There are more, and also ways in which you can make AI even more effective in all of the above examples.
However, before you open another article, please do take the time to fully experiment with the use cases above, and let us know if you have any questions :)
