Private Equity Findings, Issue 20 | Coller Capital

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25 July 2024 Publication
Research & Insights

Private Equity Findings, Issue 20

Topics
Foreword By the numbers
Retrospective: A bigger picture
Overview Understanding LPs performanceThe role of academic research in PEThe most influential pieces of academic researchThe affect of the 2006-07 credit bubble Resilience of the PE industryThe the growth of private debt fundsAreas of current researchAreas of research opportunities?
What’s at stake?
Roundtable: Will AI transform private equity?
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
Time for a new model?
Overview Time for a new model: The research viewpointTime for a new model: The investor viewpoint
The side letter arms race
AI origination for VC investments
Foreword By the numbers
Retrospective: A bigger picture
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?
Roundtable: Will AI transform private equity?
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?
Time for a new model: The research viewpoint Time for a new model: The investor viewpoint
The side letter arms race
Roundtable: Will AI transform private equity?
Does that include the use of AI to originate VC investments?

“Some VCs have exceptional quantitative capabilities that they use to identify potential investments. Of course, that is  often helped by the digital footprints tech-centric companies tend to leave.”
Joshua Lowe

 

 


““It can be hard to quantify just how widespread the use of AI is in VC. A 2018 survey by PitchBook indicated that around 22% of VC firms were incorporating machine learning in their investment decision-making. But my research, which takes the hiring of data scientists and engineers into account, suggests the adoption of data technologies in VC is hovering at around 4% to 5%, with a more pronounced adoption among early-stage investors. Looking ahead, however, projections from Gartner suggest that by 2025, more than 75% of VC investor reviews will be informed using AI and data analytics.”
Maxime Bonelli

“There has always been a spectrum in the VC world, with some firms more focused on number-crunching and others openly relying almost entirely on gut feeling.”
Léa Stern

 

 


“I am surprised to hear that the use of AI is more prevalent for deal origination among early-stage venture capitalists. I know some firms are using AI to support origination, but they tend to have a later-stage strategy. These things are only worth doing where sufficient data is available, and in private markets that data is tightly held. Certainly, the companies we go after have no data. There are no revenues or costs. It is just a group of people and an idea.

“I am also aware of growth investors attempting to harness public data to help prioritise which deals to go after, but the quality of the available data is questionable. One of the problems with AI, as with all computing, is the old maxim of garbage in, garbage out. If you don’t have a clean set of data to begin within, I am not sure how helpful AI can be.”
Anne Glover

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