OPINION: Bringing Active Management to Robo-Advisors
Robo-advisory has become short-hand for passive investment advice as robo-advisors, like their human counterparts, recommend investing in exchange-traded funds or index-based mutual funds to their clients.
However, it is important to remember that active management and robo-advisory are not mutually exclusive.
Most of the robo-advisory providers selected to start with passive investment strategies because they are simple to implement and do not require stock-picking expertise.
Of the various vendors bringing this technology to market, employees with asset management expertise usually are a slim minority. The data scientists, software engineers, and coders make up the vast majority of workers at these companies.
Moreover, the immediate goal for these vendors is to hone their AI engines to make their interactions with clients as human-like as possible. They are saving the heavy lift of active management for later iterations of their platforms.
The simplest way to deliver active management via robo-advisors would be switching out the universe of passive funds with actively managed funds.
Asset manager T. Rowe Price announced earlier this year that it would go in this direction with its ActivePlus Portfolios discretionary investment management program for IRA investors. The platform designs a portfolio based on the investor’s risk appetite, goals, and time horizon from 14 actively managed funds including asset manager’s mid-cap growth fund and high-yield fund.
This approach still presents clients with a “set and forget” approach to investing. For customers who wish to take a more active approach to their investing, such as investing in individual stocks or shortening the time that they hold their positions, there are ways to achieve this.
It is not just a matter of bolting a black box stock picker to the advisory platform. The AI engines that would highlight potential trades would have to go beyond identifying when to trade to explaining to explaining to clients why it makes sense and how the AI came to this conclusion.
Sourcing such an engine might prove a little difficult since whoever developed one likely has left their asset management firm or startup to open up a hedge fund of their own.
A second challenge in bringing active management to robo-advisors is making sure that the actively managed offerings are appropriate for clients.
T. Rowe Price has addressed this by requiring clients to have a minimum of $50,000 in investable assets before they can use the firm’s advisory platform.
Bringing active management to robo-advisors is not impossible. It just involves more heavy lifting than passive management.
VeloCity will accelerate fintech tailored to asset management.
Machine learning helps incorporate big data into index calculations.
Using AI is not a choice but a necessity.
Project will explore artificial intelligence and natural language processing.
The index selects its constituents using artificial intelligence technology.