Robo-advisory: Show me the money
Sometimes, after a couple of beverages on a Saturday afternoon, the conversation among friends turns to managing money. Stories of investments gone wrong emerge. With a bit of coaxing. Levels of service from venerable financial institutions are discussed. Often, there is a sense that much more could have been done. However, there is just not enough time in the average white-collar employee’s work week to evaluate and analyse options. Financial advisory front-line staff from banks and other financial institutions are similarly strapped for time and information. Consequently, despite the best intentions of financial advisors, investors are quite often just not satisfied with the levels of service and savings. There are, of course, stories of malpractice but that is not the norm. All of us want our money to work as hard as we do.
Last week, this column featured peer-to-peer (P2P) lending and how that nascent industry is changing the way some of us choose to handle our savings. P2P lending has a direct impact on interest income, the major revenue source for banks. Fees are the other source of income for banks. Another area of disruption from fintech is directly impacting this revenue line. Robo-advisory services describes a range of algorithm driven models that help sift and select investment options for individuals based on the investors’ requirements and risk appetite. Similar to P2P lending, this technology platform brings the customer closer to the investment. It enriches the information available through graphic rich dashboards and content that allow the investor to see how the portfolio is performing over time as well as versus benchmarks.
Deloitte’s report, The Expansion of Robo-Advisory in Wealth Management suggests that by 2020, the assets-under-management or more simply the amount of money invested via robo-advisors will be somewhere between $2.2 trillion to $3.7 trillion. By 2025, the number is expected to rise to $16 trillion or roughly three times the amount handled by the world’s biggest asset management firm, BlackRock. The report goes on to describe a four stage evolution in robo-advisory. Starting with a focus on the investor handling most of the decisions on where and how much to invest based on limited information. In the next stage, the decision making goes to experts who use the information from algorithms as a key support. Thereafter, the platforms evolve to most of the decision making being performed by the algorithms with oversight from experts. Finally, the algorithms reach a level of maturity that enables self-learning and decisioning.
Platforms are rapidly reaching the fourth stage. However, the model is evolving in two directions. Either as pure robo-advisory and completely self-managed or as a hybrid of algorithm-based recommendations overlaid with human interface and advice. There is no right and wrong answer in this asend-users will be decide based on their level of comfort and competence.
In the study of business, retail is an important area focus. Banks in the 1980s modelled themselves as “financial supermarkets”. This train of thinking led merger-and-acquisition activity that resulted in a handful of really big financial institutions. These massive “financial supermarkets” became the “too big to fail” entities during the 2008 economic crisis. In the study of retail business, the concept of the “Wheel of Retailing” suggests that historically less efficient retailers have given way to more efficient and cost-effective ones. Department stores were replaced by supermarkets and then hypermarkets came in. Now Amazon Go is building a completely new experience. Giant retail entities have collapsed giving way to the next generation or adapted really quickly. In the financial services industry, retail has not followed the same concept. Considerations of financial stability have played an important role in protection against the natural forces of attrition that occur in the openly competitive world of retail. For decades now, consumers have had the ability to shop online and get information about products. This has led to a situation of equilibrium with e-commerce having a low doubledigit percentage share of market but at the same time driving efficiency in more traditional retail. Increasingly, it appears that banks will also adapt to this reality.
Traditional firms such as Vanguard, Deutsche Bank, Fidelity and Charles-Schwab have very quickly moved billions of dollars’ worth of assets-under-management to their roboadvisory platforms. Recently, Business Insider came up with their list of top 15 Robo-Advisors. Charles-Schwab and Vanguard finds a place there. The newer names include Betterment, Acorns, Hedgeable, WiseBanyan and Wealthfront. With zero or very low minimum investments and a choice of completely automated or hybrid models, this seems like a good start to understanding how these firms work. This also appears to be a space for local entrepreneurship to develop and take advantage of the relatively higher levels of sophistication and incomes of residents.