The global venture capital market had a cracking start to the year. Coming off a 2020 high, VC totals in the United States, in Europe, and among competitive verticals like insurtech and AI are on pace to set new records in 2021.
The rapid-fire deal-making and trend of larger venture checks at higher valuations that The Exchange has tracked for some time require private-market investors to make decisions faster than ever. For venture capitalists, the timeline for reaching conviction around a startup’s thesis and executing due diligence has become compressed.
Some venture capitalists are turning to data to move more quickly. Some are spending more time preparing to be vetted themselves. And some investors are simply doing the work beforehand.
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We were tipped off to the concept of pre-diligence during the reporting process for a look into recent fundraising trends in the AI/ML space. Sapphire investor Jai Das, when asked about how he was handling a competitive and swiftly moving market for AI startup investments, said that “most firms are completing their due diligence way before the financing actually happens.”
How does that work in practice? Per Das, startups that raise quick Series A and B rounds are “tracked by [early-stage] investors as soon as they raise their seed financings. So there is no need to do any due diligence during the financing and hence most of these financings are pre-emptive.”
Venture capital: Now more about sales than ever before!
This morning, The Exchange is digging into the question of how VCs are handling diligence in a world where the most attractive deals can open and close faster than ever, and old models of deep diligence and paced deal-making are outmoded.
Getting to yes
One way that investors are betting on themselves in a bid to speed their diligence and decision-making is by investing in their own tech. That may sound obvious, given that venture capital dollars often land in the accounts of tech-focused companies, but in a business that was previously known for its relationship focus — more on that shortly — the trend is worth considering.
For example, European early-stage venture capital firm Creandum is putting effort into the technology it uses to source deals. Creandum general partner Fredrik Cassel said in an email that his firm, “like most others, keep[s] investing in [its] tech stack to power us up appropriately to help [it] get well prepared in front of exciting opportunities early.”
A recent Wall Street Journal overview noted that Correlation Ventures and EQT Ventures are using machine learning and artificial intelligence, respectively, to help source and vet deals. The thesis is simple: Computers are faster than humans at everything short of creativity and speech recognition, so tooling upgrades should help keep firms — and their competitors executing similar work — closer to the front of the investing curve.
Some venture capital collectives are trying even more exotic methods to seek insight into prospective investments: TechCrunch recently covered how a three-person venture group made up of Bessemer and Google’s Casey Caruso, GV’s Terri Burns and Pantera Capital’s Lauren Stephanian are using a custom algorithm to help make decisions and otherwise inform their investing choices.
In-house tech investments are one way to speed up the decision-making and diligence portions of a venture capital deal, but there are others. One involves simply doing the homework more quickly.
Jenny Lefcourt, a general partner at Freestyle Capital, an early-stage firm, said one of her investments “went out for Series A the first week of January and had a signed term sheet with a top-tier VC with aggressive terms in eight days. That VC did a lot of diligence — [they] just did it quickly.”
Moving with that sort of speed implies both focus — avoiding other deals distracting principals in the possible transaction — and, as Cassel explains, teamwork. The Creandum investor told The Exchange that his firm has “always won deals as a team,” by which he means that they “quickly and broadly mobilize the firm when we meet exciting teams.”
“The ability to quickly rally the whole Creandum network, way outside the team internally and including all the successful leaders across our portfolio, is even more important when process times are shorter,” he added.
So while you can take a tech approach to winnow options and perhaps help make a decision, venture firms can also take an approach from the other end of the spectrum, namely headcount and sweat.
The human element
While tech can undoubtedly help support a more informed process, it can’t do all the work, noted Manuel Silva Martínez, a general partner at Mouro Capital. He notes that “there may be some misconceptions as to what data can and cannot do in practicality.” Most limitations to data-driven approaches show up as one moves down the investment funnel, he said. “I still believe no machine can replace a savvy investor in selecting which company to give a term sheet to.”
With that in mind, VCs still spend a lot of time on relationship-building, regardless of the stage at which they invest. “[Seed-stage AI and ML] companies are still one series too early for us, but we do track them and build relationships with the entrepreneur right after they complete their Series A financing,” Das told us.
This doesn’t apply only to startups, but also to co-investors and other deal sources. “With rounds moving faster than ever, at Canvas we’ve made it a point to build even closer relationships with seed funds and angels,” said Rebecca Lynn, co-founder and general partner of this early-stage firm that recently closed its third fund at $350 million.
However, it is no longer about back-to-back coffee meetings, and the loss of human interaction has proved challenging. As an independent advisor, EY’s U.S. venture capital leader Jeff Grabow discussed the dynamic: “When you’re locked away in your respective corners of the world, there’s a limitation to the organic networking and interactions that allow investors to discover new players in the space. Historically those conversations have taken place at conferences or networking events. Networks get tested in an environment where things shut down.” Still, he’s quick to highlight that he thinks that “entrepreneurs and investors have adjusted well.”
Perhaps unsurprisingly, tech has once again come to the rescue, and fully remote deals that would have been unthinkable are now a reality. More importantly, it isn’t “either/or” as tech comes in to facilitate personal connections. For instance, “relationship intelligence” platform Affinity points out how VCs can use its specialized CRM to “stay in touch with top introducers,” “build relationships with co-investors,” “create watchlists of companies in [their] current network” and “keep track of strategic advisors.”
Pre-diligence, and whose fault is all this?
Echoing Das’s point regarding pre-diligence, AI-focused investor Jocelyn Goldfein of Zetta Ventures previously told The Exchange that her firm has “been investing over the last three years in internal systems to use data to identify startups and potential founders long before they are fundraising,” adding that the resulting “early look” at companies provides her firm with the “option of preempting.”
The result of Zetta Ventures’ in-house AI tech is that it can generate, per Goldfein, a “deeper understanding of the market,” which can, in turn, help the firm “evaluate startups before they reach typical seed traction metrics.”
That’s a lot of work to simply get the chance to put capital into someone else’s company! Back in the day, you had to give up a kidney just to raise a piddling $2.5 million Series A for a 25% stake. How the power has shifted.
Let’s close with a reminder of how we got here: After the 2008 global financial crisis, interest rates crashed. This meant that many traditional debt investment yields fell sharply and seeing negative real yields wasn’t impossible. So, cash began to flow more aggressively into other investment types. Like venture capital. Suddenly venture capitalists could raise more, and more total private-market investors were launching funds from the pre-seed stage to the super-late.
If you were a founder, would you pick the deal that was attractive and available today, or put it on hold to answer 1,000 questions from a different firm offering a similar set of terms? Nope. There are other factors in play, but that’s a summary riff of how we got the point when investors are building their own AI models to try to help them preempt seed deals.
That Tiger Global is now disrupting the venture market by writing bigger checks, faster, and without the traditional venture capital demand of board seats and a say in what their investments do post-deal is simply the next step in a long-running shift in private-market investing norms.
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