It wasn’t long ago that, for the layperson, investment automation seemed reserved for hedge funds and investment banks ”monoliths of the investing world that play the numbers with analytics to gain an advantage penny upon penny. If you simply had a casual interest in stocks, the state of affairs wasn’t very encouraging. Big players stood to make a whole lot more than you from a wide variety and volume of investments, as well as lightning-fast, automated trades.
But now things are different. This summer’s news about robo-investing paints a picture of where we are now with big data and investing:
- Betterment, the original robo-advisor, has some 300,000 users and is valued at over $800 million
- Robo-analysts are able to pore over reams of data in financial statements, saving a great deal of time for funds managers and other decision-makers, who can then use the analyses to make stock-buying decisions
- Anyone can use robo-advisors from fintech companies or banks to manage their portfolio
- Fintech robo-advisors are competing with banks, but banks’ robo-advisors may face conflicts of interest in their recommendations, because their algorithms are skewed to prefer companies that pay the banks for marketing
Robo-investing is blowing the door open on a whole new level of trade. Because robo-advisors save time, and some of them are free, more people than ever can do more trading than ever. This could be part of why the stock market hit its 25th record in July of 2017. As CNN points out, corporate profits are looking good, and profits drive stock prices. Robo-analysts can do multiple weeks’ worth of forensic accounting in hours, analyzing corporate profits, valuations, and current stock prices to deliver valuable insights to advisors. Never has it been so easy to get a rigorous analysis of the market, which helps you make decisions on how to invest.
One interesting aspect in all of this is the e-commerce market. It’s not uncommon to see reports on how e-commerce is disrupting brick-and-mortar business. Before long, e-commerce will have the neighborhood mall in (further) shambles, and stores are continually shutting down as Amazon advances towards becoming a monopoly.
Yet, from the investing perspective, because of the data available, the brick-and-mortar retail situation doesn’t look nearly that dire. E-commerce only took 8.5 percent of 2017’s Q1 earnings, during which time the retail sector netted $1.25 trillion in sales. Overall, this speaks to strong consumer confidence, and tells investors they don’t have to pull out of brick-and-mortar retail merely because e-commerce is coming up. In reality, both brick-and-mortar and e-commerce retail are showing improved earnings.
Before robo-analysts, investors had to rely on news headlines and earnings reports, that, according to Forbes contributor David Trainer, could be manipulated. So, an investor could be spooked by sensational reports that e-commerce is spelling the end of retail as we know it. Robo-analysts show investors a complete and unbiased picture, which helps create a market where people don’t sell off their brick-and-mortar holdings purely because of dark clouds on an industry’s horizon.
Big Data, AI, and the Future of Investing
As is to be expected, the sheer volume of all sorts of data from consumers and industries is creating an environment of insanely fast competition at a microscopic level. This means regular investors, although they have access to a ton of standard market data through robo-advisors, will not necessarily have access to alternative data that take a lot of money to obtain.
At a JPMorgan conference in May of 2017, the bank surveyed 237 investors, 80 percent of whom expect a reduction in relevance of traditional data sources. There are alternative data sources popping up, creating a cottage industry of firms that source, process and consult on various data sources.
These alternative data sources include anonymous credit card transaction data, data from digital receipts, and data gleaned from e-commerce transactions. These data take highly advanced data mining and machine learning techniques to process for insights. It’s even tough for huge investors like BlackRock and AQR to afford the services from firms that specialize in alternative data.
It’s easy to see where this is headed. While regular investors feel good about robo-advisors that analyze readily-available data, big money investors know it’s about obtaining the deep data on what consumers are doing in real time. Combined with AI that could potentially analyze consumer spending data in combination with corporate data, and then make millions of automated trades, big investors could dominate the landscape to an unprecedented extent. Regular investors would not be able to afford access to alternative datasets and specialized, proprietary AI programs.
Expect robo-advisors to begin making inroads on alternative data; the more an investor makes through a robo-advisor, the more most robo-advisor software companies make through fees. If you want to be truly competitive in the stock market, it will pay to find the robo-advisor with an eye on the future.
