A Secretive Robot Is Helping Investment Firm Stripes Pick Winning Bets
Investment firm Stripes is getting closer to perfecting the art of not losing.
(Bloomberg) -- The robot at Stripes enjoys reading. From the investment firm’s Manhattan offices, it consumes everything it can on the 13 million private companies it tracks. When it finds one it likes, about 0.006% of the time, human co-workers start the often years-long process of relationship building.
High frequency trading this isn’t. But the unusual marriage of algorithms and shoe leather has scored Stripes some big wins. Now, it’s getting closer to perfecting the art of not losing.
Robots in finance aren’t new. Hedge funds have been using them to beat humans for decades, building algorithms able to dip in and out of an investment several times before you finish this sentence. Yet in private equity, where swagger and a monogrammed shirt are still the most reliable way to source deals, artificial intelligence hasn’t caught on.
Stripes’ recent cyborg successes could make a strong case for that to change.
This story is based on documents, filings, and interviews with several people familiar with the inner workings of Stripes and its technology. Most wished to remain anonymous discussing non-public information. A spokesperson for Stripes declined to comment.
The firm's investments in Swiss sneaker-maker On Running and workplace software business Monday.com Ltd., both of which went public this year, have, respectively, netted Stripes 18 and 22 times their original investment. Money transfer app Remitly Global Inc. and online education platform Udemy Inc., have delivered similarly splashy returns.
But while the wins are impressive, it's the losses — or rather the lack of them — that stand out.
One measure of a fund's performance is known as its loss ratio. In investing, the bets that have a capacity for huge returns are also the ones most likely to crater when things go wrong.
Stripes has recorded a loss ratio of around 5% since investing its first fund — about average for firms investing in high-growth businesses. There were some bad bets, including a 2010 investment in Sandata, a healthcare IT company. Although Stripes eventually got out with only moderate losses, it sucked 10 years of resources away from the firm, people with knowledge of the investment said.
Since 2015, however, when Stripes started deploying its third fund, the robot — known internally as SONAR — has been speeding up. Spinning an ever-larger web of data, it’s been learning not only the art of catching winners, but also how to avoid duds.
That fund now has 17 investments and a loss ratio of 1.6%. For the fourth fund, launched in 2017, the ratio has dropped to below 1%.
People familiar with Stripes’ investing decisions say the success is partly born of SONAR’s ability to put the right investment in front of the right investor. When it identifies an opportunity, the robot doesn’t look at the prospects for growth in isolation, but also identifies where the firm’s personnel and existing network can add most value.
Cookies, Underwear
By modern private equity standards, Stripes isn’t big. The New York-based firm had $7.5 billion of assets under management as of June and staff of less than 70, only a handful of whom are investors.
Still, since launching in 2008, Stripes has generated an aggregate internal rate of return, net of fees, of 46%. Its fourth fund was running at more than 62% as of June 30, putting Stripes at the top of 100 similar sized and focused funds, according to data compiled by Bloomberg. That number has since risen to closer to 90%, people with knowledge of the fund said.
The firm’s approach is that the best product will win, regardless of the market. Its portfolio, with stakes in businesses as unalike as Israeli cybersecurity firm Axonius Inc., underwear-maker Parade and iconic Manhattan cookie store Levain Bakery Inc., attests to that belief.
That any of them rose to the attention of SONAR, which trawls for information on every private company it can identify outside of China, is a feat in itself. Currently, around 500 of the 13 million companies that it tracks rate well enough for it to pass onto Stripes’ investment team.
The scoring formula is tightly held, but the robot pulls from a diverse universe of information, including credit-card scans, company filings, news reports, consumer-engagement numbers, employee-retention data and cohort performance. What's clear from talking to those familiar with its development, however, is that much of SONAR’s time is concerned with a puzzle unique to investing in private companies.
Where algorithms that trade public securities have the luxury of accessible and standardized information, SONAR depends on glimpses. To the extent that private companies disclose anything, it is often incomplete, long after the fact and without useful comparisons. Overcoming this asymmetry is where the humans come in.
Lake Zurich
Ken Fox, Stripes' founder and chief executive officer, built the firm on the idea that while technology enables, it's relationships that deliver. However golden the opportunity, SONAR can only point it out. Then it’s up to Stripes’ investment team to start the long game of finding a way in.
In the case of On Running that meant, predictably perhaps, going for a run.
In the summer of 2017, Fox flew to the company's Zurich headquarters feeling as if he already knew the brand. During the two years Stripes had tracked it, SONAR had flagged On six times as a perfect fit.
Arriving at the offices, Fox was encouraged by On’s co-founder David Allemann to join him for a jetlag-beating jog along the shores of the city’s lake.
“We’re running and talking and I’m thinking: this guy is an athlete,” recalled Allemann. Sunk amid the Swiss Alps, Zurich holds its heat, and the two men soon stopped running and dived into the lake’s cooler waters. The investment pitch followed.
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“As a startup consumer brand, we got offered money from either west coast venture firms, who are all about your tech and how fast you can build your direct-to-consumer offering, or east coast private equity who want to build a traditional consumer product,” said Allemann. “Stripes is both”.
As well as being focused on maintaining the product’s quality, Stripes tries to provide a one-stop shop for every need that its target company might have as it grows. Internally, Fox, who declined to be interviewed, refers to this approach as being "of service."
The 51-year old Philadelphia native knows a bit about success — and failure.
In August 1999, Internet Capital Group, the tech investment business that Fox founded, listed on the Nasdaq. Its value doubled during its first day of trading to hit $3 billion, and by December it was worth more than $50 billion. Then came the dotcom crash, wiping out 99% of ICG’s value within a year.
When the rollercoaster derailed, Fox went from being the kid everyone wanted to know to running a full-time liquidation empire. At 29 years old, he quit and moved to New York.
Fox began investing his own money; cash he’d parked during the IGC days in something called Stars and Stripes LLC. He dropped the Stars, figuring the name sounded too imperial.
At first, Stripes backed small companies, where Fox felt he could use his operational experience to turbocharge growth. But by the mid 2000s, he wanted a bigger platform and sought out his old mentors, including legendary venture capitalist Michael Moritz of Sequoia Capital.
Growing Businesses
Five years ago, Levain Bakery co-founders Connie McDonald and Pam Weekes started speaking to investors to help grow the brand they started in 1995. Most, they felt, only wanted to know figures. Stripes' first question was what the founders feared most about expanding their business.
“We told them it was walking behind someone in the street as they passed one of our stores and overhearing them say ‘remember when that place was good?’ They got that,” said McDonald.
“Some investors we spoke with, that would actually have happened,” added Weekes.
Insiders say the plan has always been to become a sort of self-propelling operating business, with SONAR picking investments and the investment team focusing on helping them grow. As it learns, the robot will be able to find more and more companies for those humans to back.
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