Find out how robo-advisors differ from their human counterparts
Until recently, when it came to deciding on and executing an investment strategy, your choice was essentially: (i) hire a fancy, expensive private wealth advisor; or (ii) do it yourself. But for the past decade there’s been another option.
Robo-advisors, which emerged in 2008 and became popular around 2011, use artificial intelligence to direct wealth management decisions. They include various standalone platforms such as Betterment and Wealthfront; banks and other financial institutions, who have been using software to automate asset allocation for years, have responded with their own AI wealth advisors.
An AI costs less to employ than a human, so fees can be generally quite a bit lower, as can be the minimum assets invested. Elliott Shadforth, Asia-Pacific Wealth Management Leader for accounting and professional services giant EY, says uptake among HNWIs generally runs at about 10 to 20 per cent, but is far higher among the middle-income bracket.
Where robo-advisors excel
And there are a few things they’re likely to better at than people: keeping emotion out of investment decisions, sifting through vast quantities of data, and responding to customer requests instantaneously. You might also trust them not to direct you towards products for which they receive a commission; although, of course, machines could equally be calibrated to do just that for a particular company.
“Companies need to be consistent in the advice they give,” says Shadforth. “The use of humans creates inconsistencies; people have unknown biases. Putting all your clients on a consistent digital platform solves a lot of regulatory issues. Also, clients have historically preferred face-to-face, but now they’re showing more of a preference for digital contact,” particularly the younger generation.
See also: 5 Ways Millennials Invest Differently
Who they're suited for
At the moment robo-advisors are mainly of use to people with relatively straightforward investment requirements and relatively little investment experience; estate planning, for example, not so much. An AI’s decisions, of course, are still only ever as good as the information the client provides it with. And they might struggle with the human dimension when investments don’t go according to plan.
