One of the hottest trends in personal finance these days is the so-called robo-advisor, which uses machine learning to help inexperienced investors decide how much of their money to invest and where to put it.
There’s no debating how popular these online tools are. According to Aite Group, the market now boasts 2,148 robo-advisors with approximately $140 billion in assets. That’s still a tiny slice of the $2 trillion investing market, but it has grown 70 times since 2013, when robo-advisors had just $2 billion in assets.
According to a Citigroup report called “Digital Disruption,” Schwab estimates that the U.S. market potential for robo-advisors using machine learning in finance will be worth $400 billion in the coming years.
The market for robo-advisors is exploding, especially among millennials, but as the services have boomed, critics point out a number of important possible shortcomings of this investing approach, raising the question: Should you trust your life savings with a robo-advisor? Is machine learning in finance becoming the new status quo?
The Benefits of Robo-Investing
The advantages cited by robo-advisors such as Betterment and Wealthfront and their fans include: much lower fees than traditional investment advisors; no or very low minimum balances, which makes them attractive to young people just starting out with investing; and investment decisions based on well-established economic theories and financial advice that uses low-cost passive index funds. All robo-advisors using machine learning in finance also are registered investment advisors, a form of fiduciary which requires them by law to put their clients’ interests ahead of their own. Human wealth advisors don’t have to be fiduciaries, except for in retirement accounts.
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Index funds have been shown to deliver better returns than most actively managed mutual funds, which fail to match the market index consistently, have less portfolio churning than managed funds, which avoids transaction costs, and reduce capital gains tax because of the fewer number of transactions.
“Robo-advice fills a void for millennials, allowing them to start building wealth and planning for the future,” said a research paper from Accenture. “This is particularly important at time when other ‘entry level’ investment vehicles such as savings accounts and certificates of deposit no longer deliver meaningful investment returns.” It added that many younger customers like the privacy offered by a digital solution, rather than speaking to a much older human advisor, and value “the ability to learn and to chart their own path.”
Robo-Advisors Have Room for Improvement
Despite these advantages, robo-advisors using machine learning in finance have come under criticism from a number of quarters. One of the main faults is that the initial determination of an investor’s risk tolerance is based entirely on answers to short questionnaires, which tend to quantify risk mainly on the investor’s age and time until retirement. Most don’t ask about assets outside the investment account, liabilities such as student loans, and the time until major withdrawals other than retirement, like paying for grad school or buying a house.
“Robo-advisors do not provide investment advice that is necessarily in the customer’s best interest, are not free from conflicts of interest, do not necessarily minimize investment costs, and do not comply with the fiduciary standard of care under well-established fiduciary principles,” said Melanie Fein, principal at Fein Law Offices, in her paper “Robo-Advisors: A Closer Look.”
In addition, the Securities and Exchange Commission (SEC), the government agency that regulates investment firms, issued a warning to investors to take proper care before using a robo-advisor that uses machine learning in finance. “Be aware that an automated tool may rely on assumptions that could be incorrect or do not apply to your individual situation,” the SEC statement said. “An automated investment tool may not assess all of your particular circumstances, such as your age, financial situation and needs, investment experience, other holdings, tax situation, willingness to risk losing your investment money for potentially higher investment returns, time horizon for investing, need for cash, and investment goals.”
Another concern for investors is that while robo-advisors use similar methods, not all use the exact same method. While Wealthfront asks a number of questions of investors to gauge their subjective risk tolerance — meaning how well emotionally they could stomach a decline — Betterment does not attempt to rate subjective risk. Schwab puts much more reliance on cash than Betterment and Wealthfront, reducing a portfolio’s ability to grow while providing greater stability in a crisis.
Integrating Technology for the Future of Banking
Regardless of potential risks associated with robo-advisors, it’s clear that the industry has started to invest in the technology and is willing to implement more applications for machine learning in finance to help shape banking. This industry shift gives financial service providers a chance to integrate new technology into the average consumer banking workflow — from new mobile tools to in-bank tablet kiosks.
This inclusion of technology across the banking sphere is signaling a new future within finance: one that combines personalization with a baseline level of automation for a holistic customer experience.
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