Despite their continued expansion, robo-advice platforms remain a new and complicated concept for many of Canada’s financial advisors
Despite their rapid rise and continued expansion, robo-advice platforms remain a new and complicated concept for many of Canada’s financial advisors. For advisors to remain competitive and, more importantly, relevant, embracing technology is a must. Many traditional advisors are realizing that adopting a hybrid approach – combining robo-advice and the traditional human touch – could be the bet best for both them and their clients.
“Every client is doing more online now and even traditional advisors are facing pressure to offer some kind of online service,” says Mansi Singhal, co-founder of Qplum. “We’re getting to a point where the value addition comes from the human approach, so it’s almost an oxymoron but there is value addition from dedicated human support. Advisors are taking another close look at the hybrid approach for sure.”
The shift in attitude toward robo-advice is coming from both the client and advisory perspectives. Although clients now have more options in the marketplace, they are struggling to understand exactly where the value lies in each offering. Certain robo-platforms may offer a particular investment methodology, but that granular financial information may not be what the average investor is looking for. “So, for many robo-advisors, having a human advisor to talk to is a great add-on to offer – that’s an immediate value addition the client feels they are getting,” Singhal says.
The robo-advice market is becoming crowded and a lot of the legacy robo-platforms are being forced to prove their value proposition. Many of the 1.0 robo-advisors don’t currently have a lot of assets under management and are not really doing anything more than modern portfolio theories. They are under pressure to prove their worth in a rapidly evolving industry, just as traditional advisors are.
Another trend that Singhal is keeping a close eye on is the expanding machine learning and artificial intelligence (AI) space. Some of the big institutions have revealed that they are using more AI based methods and certain independent robos are also looking beyond the simple modern portfolio theory, which is seen as insufficient for making investment decisions.
“People are very secretive in finance and many of those funds that have developed good learning based and AI asset management strategies don’t want to talk about it because they feel they will give away their secrets,” Singhal says. “It’s a difficult situation because it sounds like something that can add value, but clients are not able to see that because the bigger players have been quiet about it. There is a bit of an education hurdle here and some validation and transparency is needed.”
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