Correlation Ventures and WR Hambrecht Ventures, both small to midsize firms, started using algorithms to guide investing about seven years ago. Hambrecht, a boutique firm in San Francisco that’s currently raising its fourth fund, uses algorithms as a second screen once companies have made it through initial vetting and are being considered for investment.
Managing director and data scientist Thomas Thurston takes each startup’s pitch deck and runs it through his algorithm, which draws on both proprietary and public data sources.
Companies the algorithm rates highly will usually get an investment, though humans make the final call. Thurston says the algorithm so far has a 66 percent hit rate, including a 2010 investment in Tango, a mobile messaging service that has since raised $367 million and is valued at more than $2 billion. “It wasn’t on anybody’s radar, but it scored really, really high,” he says.
David R. Coats, managing director at Correlation, says it took the firm three years to get a usable algorithm, which it now employs when deciding whether to join other investors in a deal.
These systems have blind spots. Hambrecht’s can’t yet predict, for example, whether people will buy a startup’s product. “We’re still wrong a third of the time, so it’s not magic,” Thurston says. But it is far better than the 20 to 30 percent success rate for most business startups, he says.
Thurston, who also runs an algorithmic prediction company called Growth Science, says that most VCs “hated the idea of this” back when he started. “There wasn’t even a word for big data,” he says. “A lot of this was alien weirdo stuff to most investment managers.”
Now there are other believers in the venture funding world. Among them: Bloomberg Beta, Correlation Ventures, Mattermark, the Compass Startup Project (which gives startups and their investors a dashboard to benchmark their performance against other startups), and the Startup Genome Project, a nonprofit that gathers data about cities and regions as incubators of startups. Bloomberg Beta uses analytics to identify people likely to start successful companies in the future. The Hong Kong firm Deep Knowledge Ventures has even taken the gimmicky step of putting its algorithm on its board of directors. And some top-tier VCs have begun hiring data scientists.
“I don’t know if [algorithmic investing] is going to take over like it has on Wall Street,” Thurston says. “But it’s absolutely going to find its way into every single major [venture] fund.”
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