Quant VC and What it Means for Startup Investing
How Algorithms Shape the Future of VC
👋 Hi, I’m Andre and welcome to my weekly newsletter, Data-driven VC. Every Tuesday, I publish “Insights” to digest the most relevant startup research & reports, and every Thursday, I publish “Essays” that cover hands-on insights about data-driven innovation & AI in VC. Follow along to understand how startup investing becomes more data-driven, why it matters, and what it means for you.
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The venture capital industry has started to massively professionalize in the past years. We have seen various new models evolving such as boutiques vs asset aggregators, specialists vs generalists, early vs growth vs multi-stage firms, solo vs micro GPs, and a lot more.
One dimension that cuts horizontally through all of these different models is digitization and the use of data & AI. It took 70+ years to start moving from the traditional all-human handcraft setup with manual, inefficient, and oftentimes ineffective workflows to a data-driven model where algorithms and automation augment humans who stay in control of the outcome.
Though less than 1% of VC firms had internal initiatives and experts dedicated to their digital transformation in 2023, we already see the first purist players pushing the limits even further: Quant VC firms. A model that takes the human out of the equation and exclusively relies on data and algorithms, just like Quant Funds did when disrupting the hedge fund industry in the 1990s.
I wrote about the three different models “handcraft VC”, “augmented VC”, and “quant VC” about a year ago here. Since then, I had several controversial discussions about the future of VC and the role of data & AI. While I’m personally a strong believer in an augmented VC approach for early-stage lead investors, I truly enjoy it when others challenge my perspective and have strong arguments to back up their convictions.
Today, I’m incredibly excited to have Guy Conway, the Co-Founder of Quant VC firm Koble.ai who will also join us as a speaker at the Data-driven VC Summit 2024 in early May, share his worldview and why he believes that pure quant strategies will win.
Thank you Guy for your thought-provoking write-up below🌶️🌶️
The AI Backlash Has Already Begun
In recent weeks, negative news headlines have started to proliferate. It seems the media can't make up its mind; journalists hypothesize that AI means death for our species, whilst also claiming that AI is a massive bubble. The schadenfreude from armchair skeptics and full-blown luddites is palpable. It’s almost as if people want us to fail.
What is true, is that the hype around artificial intelligence is normalizing.
According to data compiled by Bloomberg and Apollo chief economist Torsten Sløk, mentions of “AI”, “Machine Learning”, or “Generative AI” on earnings calls decreased from 517 instances in Q4 2023 to just 198 in Q1 2024.
This is healthy, and a net positive for the tech industry, since it reflects the maturation of AI and its wholesale adoption. Just as companies do not claim to be “Internet-driven”, they should not claim to be “AI-driven”, either.
Data Extremism
As the corporate narrative around AI is maturing, so too is the way investors think about integrating data and AI into their operations. The application of Data Science to the dark art of Venture Capital – and its impact on the investment process – is still nascent, and will take many years before its true impact can be measured and understood.
VCs have made decent progress in adopting tools to streamline operations and bring more rigor to the investment process, which remains stubbornly human. But how much further can Data-driven VCs go before hitting a ceiling in terms of how much internal spending can be allocated to refreshing the data stack?
And even if spending on data was unlimited, there is still the immovable (and seemingly ubiquitous) belief that data is the input; only humans can run the Investment Committee. How strange that we let AI discover new drugs for us, and then diagnose us with the illnesses with which those drugs should treat us, but the widely held industry belief remains that AI can’t tell us if a startup investment is the right one!
A growing subset of investors is calling for a more hardcore approach – one that excludes humans from the investment process entirely. But this camp is very much in the minority.
Full automation of the startup selection process requires technology that’s orders of magnitude more complex and capable than that which is currently accessible to mainstream VCs. But purist (some might say, extremist) “Quantitative VCs” are quietly building in the background.
Going Beyond the Consensus
AI is perfectly suited to helping humans manage informational overabundance, and deconstruct the Power Law to demystify the “miracle” of Venture Capital. Use cases are plentiful and well documented: