The human touch gives robo-advice threat the brush offSeptember 14 2017
Financial planners with the right business model, placing strong relationships with clients at the centre, can breathe easily in the face of any threat posed by robo-advice.
That’s the perspective of the chief executive, chief investment officer and lead portfolio manager for Magellan Financial Group, Hamish Douglass, who told the company’s 2017 adviser roadshow in Sydney on Tuesday that robo-advice is a solution for clients who don’t have any money to start with.
“That’s what they’re trying to solve for – they’re trying to automate things where it’s too expensive for individuals,” Douglass said. “Your business model isn’t just creating an investment solution, your job is to be the counsellor to your clients in probably the most important thing in their life, which is their financial wellbeing and their children’s financial wellbeing.”
Douglass said that when it comes to dealing with issues of a deeply personal nature, people “don’t want to go and ask a robo-adviser that question. They want to ask a real person that question, whom they trust and who’s going to give them objective advice.
“I would argue that if you think… you are really there as a counsellor and consultant on something that’s deeply important to your clients, you don’t have anything to fear [from] robo-advice.
“But if you don’t think of that as your business, and you never speak to your client and you’re not interested in them, I just say you deserve to be disrupted by robo-advice.”
Douglass said there is great potential in artificial intelligence (AI) and machine learning technologies to mine vast amounts of data to gain new investment insights, but the key to doing it effectively is to mine the right data in the first place.
“The datasets are the critical things, and [for] the key data you want, some of the datasets just are not public information,” he said.
Douglass said the Renaissance Technologies hedge fund business, founded by US mathematician and philanthropist James Simons, was a good example of how using AI and machine learning to create the right datasets could lead to improved investment performance.
“They use machine learning and they get incredible datasets and they’re some of the wealthiest people in the world, so do I think it could actually do something? Yes, I do,” Douglass said.
“But data that would tell us something, datasets that we could learn from – we’re not seeing those datasets [made] public…on a scale so that we could actually do something that would be meaningful in the way we manage money.”
Nevertheless, Douglass said, developments in AI and machine learning could herald the day when investment managers are made redundant.
“Eventually that could happen,” he said. “But I’m not losing sleep it’s going to happen tomorrow.”