AI Tools in PE

I’ve been seeing a lot of AI tools in PE lately, but how do you figure out which ones are useful? I’ve talked to a few companies, but their products didn’t deliver as promised. What are some impactful use cases for AI in PE workflows?

13 Comments
 

Based on the most helpful WSO content, here are some impactful use cases for AI in Private Equity (PE) workflows:

  1. Data Processing and Analysis:

    • Sentiment Analysis: Running sentiment analysis on earnings call transcripts to gauge market sentiment.
    • Image Recognition: Using neural networks to count the number of cars in a parking lot, which can be an indicator of business activity.
    • Text Extraction: Extracting text from scanned paper receipts to streamline data entry and analysis.
  2. Quantitative Stock Screening:

    • Utilizing machine learning models trained on years of fundamental data to surface interesting investment opportunities.
  3. Risk Management:

    • Employing advanced statistical techniques to hedge out correlations and unwanted factor exposures from a portfolio manager's stock selections.
  4. Deal Origination and Due Diligence:

    • Ingesting large amounts of structured and unstructured data to output standardized reports within minutes, automating approximately 50% of these functions and improving over time.
  5. Portfolio Company Value Creation:

    • Implementing AI solutions for market monitoring, sales optimization, computer vision, automation, and operational efficiency to increase exit valuations.

For more detailed insights and discussions, you can refer to the live Q&A session with Arctic AI on Wall Street Oasis: https://www.wallstreetoasis.com/forum/private-equity/qa-ai-will-automat…</a">Q&A: AI will automate many roles in the IB/PE world.

Sources: Q&amp;A: AI will automate many roles in the IB/PE world. A live Q&amp;A with Arctic, who are recruiting finance professionals to help manage that change, Q&amp;A: AI will automate many roles in the IB/PE world. A live Q&amp;A with Arctic, who are recruiting finance professionals to help manage that change, AI in fundamental investing, What job to take if you best want to ride the generative AI wave over the next couple of decades. Serious question., Will robots replace your consulting or financial career?

I'm an AI bot trained on the most helpful WSO content across 17+ years.
 
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I get that, but it's also quite hard to find a good overlap of both IB and CS/ML/AI skills. The point is always getting the product right. Without cs skills you don't know what's possible to build, without ib experience you may build a useless product. 

... and I am working on something. I would like to hear what you think: aurelioterminal dot com

I come mostly from fundamental research

 

Virtually all the companies in this area are not founded by people with front office IB/PE experience, so it's not really surprising they suck. They are built by people who have no clue about the industry.

You should look for tools where this is not the case. There are a few I am aware of and they seem to do more interesting and directly useful things than just generic text oriented DD stuff. Like automating specific model workflows, or automating data cube cuts. 

I do expect modelling to become highly automated in PE very quickly. I recently demoed a tool that could do LBO and merger models more accurately and >100x faster than anyone I ever met in finance. It can't do like complex stuff (the type of modelling that would happen in further due diligence) though. But was excel to excel so you could just download and iterate in excel. 

 

Can you share the tool? Would love to have something that makes it quick & easy to throw together the basics and use that as a base. 

"If you don't have any enemies in life you have never stood up for anything" - Winston Churchill | "It's a testament to the sheer belligerence of the profession that people would rather argue about the 'risk-adjusted returns' of using inferior tooth cleaning methods." - kellycriterion
 

There are a few firms now with internal ChatGPT-based platforms, including at mine. They are extremely helpful in summarizing CIMs/presentations and proofreading IC memos, meeting notes, and other written output. I use it mostly for proofreading and generally helping my written output flow and read a bit better. But otherwise, not that many use cases. Maybe we are just not good with prompt engineering, it's all about finding the right prompts

 

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