EquBot: Democratized A.I. in the Investment ProcessBy Justine Humenansky
There were 2.5 quintillion bytes of data created each day in 2017. No human can possibly collect, scan, and process all this data but it contains valuable information that can be used to make better decisions, particularly when it comes to investing. EquBot was the first company to incorporate AI throughout the investment process within an ETF, allowing retail investors to access the investment insights derived from all of this data. I sat down with CEO and Co-founder, Chida Khatua, to learn more about his vision to democratize artificial intelligence in the investment process.
Overcoming the Limitations of the Human Mind
The idea to create EquBot, founded in 2015, occurred during an MBA class at Berkeley-Haas following a conversation about the criticality of AI to any investment strategy given the rapidly growing amount of market data. Before EquBot was founded, investment insights derived from the use of artificial intelligence were largely restricted to institutional investors, such as hedge funds. The founders of EquBot wondered why non-accredited, retail investors couldn’t also leverage the power of artificial intelligence to build their portfolios.
EquBot uses proprietary algorithms augmented by AI cognitive computing platforms such as IBM Watson and Google Cloud AI to overcome the limitations of the human mind. EquBot’s technology processes millions of news articles, social media postings, and financial statements every day, essentially simulating teams of equity research analysts and a multitude of trading desks working around the clock. While the founders could just as easily have used the technology they created to open their own hedge fund, democratizing the power of artificial intelligence has been at the core of the company’s mission since inception.
Bringing the Power of Artificial Intelligence to All Investors
EquBot participated in the IBM Global Entrepreneur program and is a member of the “With Watson” program. While EquBot is powered by Watson and other AI commercial instances, it leverages the company’s own proprietary algorithms to formulate new investment insights. The algorithms first work to identify mispricings by combing through massive amounts of data to build predictive financial models on over 6,000 publicly traded US companies and 15,000 companies globally. Then EquBot’s technology parses through millions of articles and news sources, while also analyzing company management, to uncover events that might serve as upcoming catalysts to realize this unrecognized value. Finally, EquBot’s technology attempts to optimize timing, determining strategic entry and exit points and actively rebalancing the portfolio to satisfy volatility and risk requirements. Beyond the technology, what is innovative about EquBot’s solution is that now retail investors can benefit from this technology, and with an investment minimum as little as the price of one share.
“AI will become a necessity in the investment industry as the amount of market data grows. Our end goal is to bring this technology to everyone, since the beginning our goal has been to bring access to everyone.”
– Chida Khatua, CEO of EquBot
The company’s first product, launched just over a year ago, was the first AI-powered ETF to market. AIEQ, traded on NYSE ARCA, has outperformed the S&P 500 (gross of fees) and the Russell 2000 (net of fees) YTD, notably weathering the market downturn in February. During this period, AIEQ bought defensive stocks to further diversify the portfolio and also readjusted risk to take advantage of new low price opportunities. This strategy performed well when the market recovered. While the company’s track record is promising, continued outperformance over an even greater variety of market conditions will have to withstand the true test of time.
This past June, EquBot launched its second product, the AI Powered International Equity ETF (AIIQ) which is also traded on NYSE ARCA. This complimentary international ETF utilizes the same technology as AIEQ but incorporates a volatility screen with the goal of maintaining a portfolio volatility comparable to that of the broader developed markets ex-U.S.
The company currently has ~200M in AUM and charges a 0.75%-0.79% fee (depending on product) which is slightly higher than the average open-end expense ratio, according to Morningstar.
First to a Very Large Market
The U.S. registered ETF market was worth $3.4T in 2017 while the U.S. registered mutual fund market was worth $18.7T, according to ICI Global. EquBot believes that ~$5T of this market is addressable. While EquBot was first to market, competitors have followed. Given the size of the market, EquBot believes that there is enough opportunity for players to approach the market from different angles. In other words, EquBot does not view this as a zero-sum game. In addition to two ETFs, the company has also launched the EquBot Platform, through which the company plans to license its technology to large investment managers by providing a platform service at scale.
There has been significant, inbound interest from large institutions that can use the platform to create a new product, test their own portfolios with an AI overlay, and/or receive insight on market signals in order to build their own products. A common concern with AI models is that there is little insight as to how the models arrive at their decisions, but EquBot was designed to be less obscure. Investors can obtain real-time observability reports to understand what is impacting their portfolio, a key differentiator when it comes to AI solutions. As an AI company, EquBot must continually work to maintain data integrity while the sheer volume of data continues to grow and change.
The company has also had to work to overcome general resistance to the use of AI in financial services. While some worry about the human capital impact of incorporating AI into the investment process, the EquBot team views AI as a tool that can reduce human bias and be used to make investment professionals more productive. For example, leveraging EquBot’s products might allow a portfolio manager to manage more portfolios or for an analyst to analyze more companies.
An Experienced Team
Being the first to market with an AI-powered ETF is no small feat and it stands as a testament to the strength of the team behind EquBot. All three members of the company’s executive team received their MBAs from Berkeley-Haas in 2016, leveraging complementary backgrounds with expertise in both technology and financial services. CEO and Co-founder, Chida Khatua, founded a successful ad-tech business and spent 17 years at Intel, most recently as Director of Engineering. COO and Co-founder, Art Amador, is a Certified Financial Planner and spent nine years at Fidelity Investments. CIO, Chris Natividad, previously worked in investment management at Gilead Sciences, Apple Inc.’s Braeburn Capital, and Goldman Sachs. The team believes that the resources they had access to at both Stanford (Mr. Khatua also has an MS in EE from Stanford) and UC Berkeley, including many Berkeley-Haas professors, were instrumental in establishing a support system that has allowed them to succeed.
“We Can Be A Game Changer”
The company has turned $335,000 in angel funding into ~$200M in AUM and its operations are already yielding positive cash flow. Thus far, the company has relied on organic marketing and press but is looking to establish more formal institutional distribution channels now that it has established a year-long track record for AIEQ. The company is excited about the strong inbound interest it has seen for the EquBot Platform and plans to launch several new B2C products in the next year. In order to fuel this future growth, the company is looking to raise additional capital over the next few months.