By Bobby Monks and Kathleen Campion
Not everyone needs sophisticated financial counsel. Think of it this way. You’re 27 with a BA in marketing, earning $63K with no dependents and no savings, but, no substantial debt either, apart from that glaring AMEX balance. Still, you would like to start saving and investing. A house, maybe kids, even retirement are beginning to float into your thinking.
Enter the robo-advisor, a low-cost, automated investment platform that relies on technology and some management algorithms to help sort out what’s best for you to do.
Let’s hit the pause button here. This snapshot of the archetypical robo-investor is fading to sepia as we write it. While robo got its start attracting this gang of millennials with little in the way of assets, enough serious money is now on the move to suggest robo is capturing a different class of the investor pool.
A little history: Before 2008, the year of the financial crisis, and, not coincidentally, the Genesis year of the robo advisor, the wealth management software that underpins the hundreds of robo services blooming now, was only sold to traditional investment advisors. They used it to manage investment accounts, and collected rich fees, 1-3% of assets under management, plus much more in hidden fees and soft dollars. They had a lock on the technology and they only managed clients with substantial assets.
In the aftermath of the financial crisis, the investor class was well and truly shaken. Billions traveled out of managed accounts and into passive instruments. Index funds, where the investor simply rides the ups-and-downs of a given index, and pays a relatively low fee, flourished. Investors asked their pricey advisors: What am I paying you for, if you can’t even beat the S&P 500?
As is true in most managed accounts, the asset allocation looked pretty much like this: 30% in fixed income, 60% in equities, 10% in cash. Even the “risky” portion here, the 60% in equities, is risk-lite. In fact, most robos still stick to ETFs and other passive investments.
Now that there are hundreds of these shops, each is trying to capture market share, by differentiating itself in the disrupted marketplace. What’s more, the software has evolved. Where robo was once limited to asset allocation, it’s now picked up some of the other services traditional advisors offered.
Personal finance site NerdWallet offers a nifty breakdown of the leading robo companies, and points to some advances in services. Wealthfront has a direct indexing service and purchases individual securities to zero in on tax-loss harvesting opportunities. Combined with daily tax-loss harvesting, included in all taxable accounts, the company says the service can add as much as 2% to performance.
BlackRock opted to “buy it not build it” and picked up FutureAdvisor last year. This in-house robo offers two tiers of service. Free tools include direct management of college savings plans and many Fidelity 401(k)s. On the fee side, they offer management of IRAs, tax-loss harvesting, and indirect access to human advisors.
Blooom fills a gap in the landscape. Most online shops will manage IRAs, few handle 401(k)s. Blooom is set up to manage employer-sponsored plans.
And the returns? Even the most aggressive robo portfolios track broad indexes, and returns are comparable to those the broad indexes report, comparable to the Vanguard Total World Index, for example. Still, as robo adds services, significantly tax-loss harvesting, they are not really comparable to index investing, while the fee structure can be.
Transaction fees are all over the lot. Most robo-advisors charge an advisory fee as a percentage of the investor’s account value. This advisory fee is in addition to the required expense fee for owning a fund. Some robo-advisors may also charge for trades, add-on services or account maintenance. However, many robo-advisors only charge an advisory fee and use that to pay for any trades and maintenance needed on an account. The average advisory fee, regardless of account size, is 0.40%.
As robo “builds out” it is expected to capture trillions in assets. Consulting firm A.T. Kearney expects robos to manage as much as $2.2 trillion by 2020. A report from Deloitte released in December estimates robo services will manage $5 to $7 trillion within a decade, up from under $100 billion today.
It is a measure of robo success that it’s already captured enough of the business to force the larger, traditional, low cost players — Vanguard, Fidelity, and Schwab — to offer competing robo advisor services. The banks, rattled by outflows, are playing catch up. Morgan Stanley CEO James Gorman and the boss at Wells Fargo, John Shrewsberry, are on record saying their firms must build robo-advisors.
Kendra Thompson, a managing director at Accenture, tells Bloomberg:
“It’s real money moving. You’re seeing experimentation from people with much larger portfolios, where they’re taking a portion of their money and putting that in these offerings to try them out.”
Betterment says more than half of it’s $3.3 billion under management comes from people with more than $100K at the firm. Wealthfront says more than a third of its nearly $3 billion in assets is in accounts requiring at least $100K. At Schwab about 15 percent of those in automated portfolios have at least $1 million at the company.
Right now, the robo models are in the ascendancy, grabbing market share, while the old bulls are hustling to build competing products. Heeding DeepThroat’s counsel-following the money-it’s increasingly obvious that investors a tier or two above the millennial are buying-in to robo investing. If we accept that the move out of the traditional wealth manager model and into the new, new thing is the beginning of a paradigm shift-that change begets change, and technology will do whatever it can do-the obvious question is what comes next? Ultimately, how good does robo get? What does robo look like when it grows up?
High frequency trading platforms use complex algorithms to predict very short term advantages in price, and find their advantage in executing trades at high speed.
A more traditional leveraging of computer capacity, quantitative analysis, has been informing professional trading for decades. These “quants,” Wall Street’s nerds, build large statistical models to guide trading. While access to more data has made those models increasingly complex, they remain static, that is, they don’t change or learn.
Artificial intelligence, specifically machine learning, has long been the stuff of science fiction — think HAL, Kubrick’s Heuristically programmed ALgorithmic computer, and more recently HER, Jonze’s perfect woman. A fiction no longer, machine learning is the golden fleece of today’s heroic chase, the investor’s edge. And hedge funds are piling in.
The article was originally published by SeekingAlpha.com on April 6th, 2016.