Topics
Foreword By the numbers
What’s at stake?
The side letter arms race
Overview
PE embracing AI technologiesAI origination for VC investmentsThe limitations of AI & lack of dataAI in decision makingUsing AI to predict future outcomesDo LPs really need AI to process qualitative information?AI techniques to predict company director performanceDo large networks and directorships mean poor performance?What aspects of PE are ripe for AI disruption?AI for PE: hype vs. reality
Areas of current research
Foreword By the numbers
Retrospective: A bigger picture
Roundtable: Will AI transform private equity?
Understanding LPs performance
The role of academic research in PE
The most influential pieces of academic research
The affect of the 2006-07 credit bubble
Resilience of the PE industry
The the growth of private debt funds
Areas of current research
Areas of research opportunities?
What’s at stake?
PE embracing AI technologies
AI origination for VC investments
The limitations of AI & lack of data
AI in decision making
Using AI to predict future outcomes
Do LPs really need AI to process qualitative information?
AI techniques to predict company director performance
Do large networks and directorships mean poor performance?
What aspects of PE are ripe for AI disruption?
AI for PE: hype vs. reality
Time for a new model?
The side letter arms race
What areas of research are you working on today?
“One area is on the changing fund structures offered by GPs – they are much more bespoke and designed to match the outside options LPs have. We have already established that LP returns are very different even when they have access to the same GPs, and now we are seeing LPs build their own capabilities to make co-investments, parallel investments and direct investments. This is creating even more of a wedge between the more sophisticated investors and the rest. “I’m also conducting research with Josh on the disclosure between GPs and LPs. There is a lot of discretion among GPs about how, how much and how quickly they report to their LPs. We’re using artificial intelligence (AI) to parse reports and determine the techniques of communication and best practice – we want to help LPs understand the evolving risks in their portfolios.” Antoinette Schoar |
“It’s quite a challenge, though. In public markets, you have a lot of structured data; in private markets, you have PDFs, slides, spreadsheets and so on. It is very poorly structured and so you can’t just leave AI alone to go through this. However, we’d really like to see if we can help LPs understand better what is going on in their portfolios.” Josh Lerner |
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