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
Using AI to predict future outcomes
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
Roundtable: Will AI transform private equity?
Ludovic, you explore the use of AI to predict future outcomes – in the realm of fund performance. What can LPs learn from your research when it comes to manager selection?
“Our research shows that investors currently focus too much attention on quantitative information and not enough on qualitative information, possibly because quantitative information is easier to convey to an investment committee. Using AI, we have been able to show that qualitative information is the stronger predictor of future fund performance, so sidelining this material is a big mistake.”
Ludovic Phalippou
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