As robo advisors increasingly jostle for market share, a reoccurring question has focused on how firms will differentiate their offerings.
Those that can clearly communicate their platform's risk tolerance determination rather than hiding it in fine print will gain a competitive edge, particularly among savvy young investors, a new report suggests.
They will be able to "resist the ongoing trend to the commoditization of portfolio management, and indeed, command a price premium," writes Will Trout, head of wealth management research at Celent.
"As for a price premium, I'd say 30 or 40 basis points would be about right," he notes in an email. "Add that to the usual robo advisor fee which is around 25 basis points, and you get a fee that is above the standard robo price, but significantly less than the 1% a standard advisor would charge."
Some firms have already adopted the tactic to cull prospects from the younger investor pool, Trout adds.
"The concept of portfolio risk is not intuitive to the lay or novice investor," he says. "That is why firms like [European platform] Scalable Capital are targeting more sophisticated young investors, with whom such a concept will resonate."
AI-POWERED RISK MANAGEMENT
A regularly critiqued characteristic of robo advisors is their reliance on client risk tolerance determinations. Detractors find them flawed since they largely are done through short online questionnaires.
"Investors need a lot of help understanding what their true ability to take risk is. Firms can't expect them to fully articulate it themselves," says Min Zhang, CEO and co-founder of risk management tool provider Totum Wealth.
But digital advice firms say they are getting better at modeling portfolio risk and understanding their clients through data, even applying new technology to improve their client assessments and portfolios, particularly machine learning.
"Some of the additions we are making to our platform include machine learning-based risk profiling and asset allocation, [neuro-linguistic programming]-based support and bots, and predictive analytics," says Mike Kane, CEO of Hedgeable. "We believe this will be the next fast follower approach in the market a few years from now."
Trout agrees AI and machine learning have the potential to expand the ability of portfolio risk management tools.
"AI can be used to calculate practically unlimited possibilities for risk, even around Black Swan events which would not fall within the normal range of probabilities," he says. "The 2008 crisis was in fact a so-called one-in-10,000-years event, which clearly it was not!"
UP AGAINST ALGORITHMS
Trout's report exhorts human advisors to follow suit and add such tools to their services if they haven't already to remain competitive. But Aaron Klein, CEO of Riskalyze, argues advisors will continue to attract clients.
"Wealth management firms that provide a compelling value proposition beyond ‘designing the pie chart’ won’t see the fee compression everyone is talking about," Klein says. "Fee compression happens when you are buying commoditized services and it’s not that difficult for human advisors to differentiate from an algorithm.”
Trout acknowledges that despite the number of assurances from digital providers that they can withstand market volatility, their continued reliance on ETFs and low-cost indexed funds means they are vulnerable to crisis.
"Any protracted market downturn, or even a period of unusual volatility, would display to investors the risks of embracing a portfolio composed purely of market tracking instruments," Trout says.
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