This is the problem statement I set out to explore by starting out on the ambitious ground up research project with Synpulse last year.
But best for who? I quickly realized that there are at least three different audiences: retail investors, looking for modern automated ways to manage their wealth; private banks and asset managers, looking for a robo to adopt in their operations; and institutional investors, looking for investment opportunities in Fintech as part of their P/E portfolio allocation.
Hence, robo-advisors’ “model inputs” methodology, I have developed, targeted to introduce a common denominator, which would allow various audiences to get the most understanding of the robo-advisory market in Asia.
After I have analyzed 16 robo advisors’ survey data, interesting results transpired.
For retail investors
Rather alarming trend that I noticed post study completion that in my view all retail investors must be aware of is that 31% of all surveyed robos are using 3rd party (outsourced) portfolio construction models. Most of them are B2C and B2HNWI robos, targeting retail and accredited investors.
It would not have been an issue if all of them showed robust and in-depth understanding of the outsourced models. However, survey showed otherwise.
Among all retail focused robos, the only solution that truly stood out and showed the maturity of an enterprise player was Stashaway. Since then, I have invested with Stashaway and also recommended their market cycle investment strategy as a satellite or thematic allocation to my clients on top of the core portfolio they have with me.
For private banks and asset managers
My study found that there is a distinct correlation (0.89) between how mature robos are in their asset allocation models and how much functionality they need to build to expose their models to the clients. This correlation is not 1.0 mostly because some study participants, whose robo solutions are known for their technical teams’ expertise, scored low in portfolio allocation maturity.
In my view, this is mainly because they also belong to the 3rd party group (31%). These players commented in DigFin’s article “Apples and oranges: comparing Asia’s robo advisors” that my methodology is flawed and I can’t compare them to other players. I disagree with this argument as all participants of the study fit the globally accepted definition of a robo: “automated portfolio construction software that is fully distributed online”.
The approach I took in the study is to look at how all the players are practically interpreting the fundamental inputs required in constructing any portfolio/asset allocation. Questions in the survey were targeting not the knowledge of the portfolio construction theory as it was not the point, the main objective was to see how each participant implemented and found practical workarounds to the known limitations of the theory.
The ranking was entirely based on the score received for portfolio construction maturity. Functionality sophistication, although considered in the study, was not contributing any weight to the final score. The primary reason for that is I personally believe it is paramount to have industry experience and expertise in managing actual money first, and brilliant technical team able to implement this expertise – second!
Four players emerge as clear leaders among robo-advisors that were surveyed. They are from the Enterprise group. Led by industry veteran founders, they build advanced portfolio models and other features based on clear insight into what clients need and how they deliver these solutions.
Prive Managers, Lumiq, Quantifeed, and Additiv are my top picks for banks and asset managers who are looking for partners for their digital advisory implementation journey. Of course, financial institutions need to consider their own unique situation and requirements before making the final call.
For institutional investors
Look for fintech robo solutions that are mature and have founders with hands on asset management experience. Good questions to ask when profiling a robo to buy or invest in?
- How many years of experience do you have managing assets/money?
- Which asset management/hedge fund/mutual fund have you worked for before?
- How much AUM did you manage directly?
These are the core questions I would ask to gauge if the robo solution you are considering to buy/invest in has any chance of survival in the market!
If you are keen to read a full report, Kaplan has helped to publish it and now offers both paper and digital version for purchase on their website here
