SVLTI meetup on how to evaluate a Robo-advisor platform?

On 25th of February, SVLTI (Silicon valley long term investors) conducted a meetup on the topic of how to evaluate a Robo-advisor platform? The meetup was warmly received by the audience as evident from the strength of the attendees. The term robo-advisor has become a hot topic in investment community in the last few years. It was only natural that SVLTI conducted a meetup on this topic sooner rather than later.

We began the meetup with the usual introductions and soon moved to discussion of what a robo-advisor essentially means. The term robo-advisor refers to a computer based financial advisor that makes asset class based portfolio recommendation for the long-term investing. Robo-advisors allow a client to simply enter information such as age, income, current portfolio value and risk tolerance and output a portfolio in a matter of minutes if not seconds. It was thought that the economic value of such an activity should be no more than 1 or 2 basis points and the participants were shocked to learn that some current Robos are charging as much as 35 bps for this activity. The group was also not pleased with the idea of proportional fees model that current crop of Robos employ. A fair criticism in this regard was pointed to by one of the members. That an automated asset allocation tool run by a computer based algorithm should be charging proportionate fees was considered a rip-off of the ignorant investors.

In contrast ETFscale's model was lauded by some members in that this company actually tries to inform and educate the investors following the mantra of give a man a fish and you feed him for a day; teach a man to fish and you feed him for a lifetime. Most of the current Robos have taken millions of dollars in venture capital money and they have hired the well known people in investment community as a marketing tool. Now the VCs are salivating with the possibility of huge returns while the ignorant investors are fleeced by the marketing machine of these Robo unicorns.

Moving on to the discussion it was pointed out that the market for the Robos are investors with smaller asset amounts, who are typically shunned by the human advisors. Robos are also being adopted by millennials with their love for technology based solutions; Investors who are comfortable with technology, and investors who have had bad experiences with traditional advisors.

A Vanguard study found that the asset allocation decision was responsible for 88% of a diversified portfolio’s return patterns over time. Constructing a diversified portfolio based on various asset classes' expected risk and return, given the user's position on the risk spectrum, is what the automated computer algorithms are good at doing. Add to that periodic rebalancing updates and more goodies like tax-loss harvesting and voila you start calling that a Robo-advisor. Nothing wrong in that when you can also convince some VCs to plunk down millions in funding. Only the time will tell the fate of the current crop of the proportional fees based Robo-advisors.

Current Robos have a very simplistic portfolio allocation model. Based on some behavioral based questions a risk tolerance score is found. Each risk tolerance level results in a particular portfolio. Asking an individual some behavioral questions and assuming their answer is correct amounts to asking a person what is their favorite color and inferring some part of their personality from that; This might not turn out to be correct. Most people have much more complicated investment situations in their life.