Machine learning startups are trying to establish a deeper presence on Wall Street.
The latest move comes from Aiera (pronounced like “era”), a New York- and Boston-based company that announced today it took in $3.5 million in seed funding. Flybridge Capital Partners led the investment and was joined by Macquarie Group, Innovation Endeavors, Fin Venture Capital, and WGI Group.
Aiera, which stands for “artificially intelligent equity research analyst,” wants to use A.I. technologies to help active investment managers make decisions, in part by forecasting stock performance and recommending whether to buy, hold, or sell particular stocks. Aiera’s software uses deep learning models, a branch of A.I. that learns using so-called neural networks that mimic the way the human brain learns. The company says its software absorbs hundreds of thousands of publicly available documents and media each day, including news articles, social media chatter, SEC filings, videos, and transcripts of public companies’ calls with investment analysts. The system crunches that data and applies investment decision-making techniques to spit out insights and recommendations.
Deep learning technologies have led to advances in A.I. in recent years, but it has been difficult for their developers to understand and explain how the models arrived at their conclusions. That’s one thing that makes Aiera intriguing: Co-founder and chief technology officer Bryan Healey claims the company has had success reverse engineering its A.I. system’s predictions and producing “human-readable research” reports that explain them. The company’s approach involves using probabilistic models to make educated guesses about which market signals were likely used to arrive at the stock investment recommendation, Healey explained in an August interview with Xconomy in downtown Boston.
“It’s been challenging and fun to try to get neural networks to cough up their answers,” Healey said at the time.
Aiera’s predictions have generated some buzz this year, although the picks have been a mixed bag. The New York Times reported that Aiera’s bot made a “sell” recommendation on Facebook (NASDAQ: [[ticker:FB]]) stock in fall 2017, several months before the social media giant’s stock price tumbled in the wake of the Cambridge Analytica scandal and renewed concerns about the way it handles user data. Meanwhile, Aiera’s software incorrectly predicted Boston would win the bid for Amazon’s (NASDAQ: [[ticker:AMZN]]) second headquarters; instead, the New York City and Washington, DC, areas were picked. (New York reportedly did make Aiera’s top-five list, however.)
Aiera is part of a bevy of startups applying A.I. tools to finance, the theory being that there’s a ton of data to crunch, and money to be made if software can help make better decisions more quickly. Other companies in this arena include Indico, which pulled in $4 million in venture funding in January; Forge AI, which raised $11 million from investors this month; and Kensho Technologies, which was acquired for $550 million by S&P Global in March.
It’s too early to tell whether Aiera will catch on with institutional investors, but the company has cash in its coffers and a team with a solid pedigree to bolster its sales pitch. Healey previously was a software development manager on Amazon’s Alexa team and director of A.I. at Lola, a Boston-based travel technology startup. His co-founder, Aiera CEO Ken Sena, was the global head of Internet equity research at Wells Fargo Securities and Evercore ISI, as well as vice president of equity research at Credit Suisse.
In August, Healey said Aiera is positioning its software as a tool to automate the background research that takes up so much of investment analysts’ time.
“A good part of their job is just keeping up with the world,” Healey said. “It’s hard to keep track of everything to understand what matters, what doesn’t matter.”
When asked if the eventual goal is to replace investment research analysts’ jobs, Healey said “we’re not trying to pitch it that way.” Aiera’s software is “continually adapting and getting better,” he said. “But for now, that’s not the mission,” he added.
When asked about the automation question this week, Healey said in an e-mail: “We believe strongly in the marriage between human and A.I. as an efficiency tool and performance enhancer, and not in using A.I. as a straight replacement” for analysts.
