Younger Canadians in particular are turning to artificial intelligence to shape their finances, a survey released this week shows.
Experts tell Global News there are many tasks that AI is well-equipped to handle when it comes to making money decisions, but there are limits to how Canadians ought to rely on the evolving tech.
The Bank of Montreal tapped Ipsos to poll Canadians on how they’re using AI in their financial planning.
Roughly a third of respondents to the poll said they use AI to help steer their finances, according to the report released Monday.
Most commonly, Canadians are using AI to boost their financial literacy (43 per cent), set up household budgets (43 per cent), figure out new investment strategies (42 per cent) and build their savings (40 per cent).
Gayle Ramsay, head of everyday banking and customer growth at BMO, tells Global News many Canadians might not know that AI is already embedded in online banking tools.
She gives the example of an interface letting a customer know if they’re on track for their savings goals or warning of a possible cash flow issue arising in the next seven days, all based on an AI’s read of a consumer’s habits and regular expenses and deposits.
The survey shows that AI was used to plan for upcoming financial milestones among 55 per cent of gen Z respondents (Ipsos breaks this cohort down as those born 1997-2005).
Ramsay says it’s not a surprise to see gen Z is leading the pack when it comes to asking questions of AI.
Financial anxiety has been particularly acute for the younger generation, with money problems cited as the top stressor for 91 per cent of gen Z respondents. Fear of unknown expenses, housing costs and keeping up with monthly bills were listed as major sources of that anxiety.
“They’re using it for exactly that. They’re asking questions … about finance and they’re leveraging it to help manage their day-to-day,” Ramsay says.
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Ben Felix, head of research at PWL Capital, says portfolio managers at the firm have used AI to wade through the troves of data in a customer’s profile and changes in the market to prepare for client meetings.
“AI can take that information and spit something comprehensible out back to an advisor that would otherwise take them many, many hours of reading notes,” he tells Global News.
Tools like AI are at their best when they have a large pile of data to sift through, Felix says, particularly when you’re looking for information about your own habits. If someone just wants to know where their money is going on a regular basis, “that’s super helpful” and can’t get a consumer into “too much trouble,” he says.
Ramsay says she sees AI thriving in what she calls “lookalike modelling,” where a tool could provide options or suggestions that consumers who “look like you” have found success with previously.
Both Ramsay and Felix warn, however, that an AI is only as good as the information it has access to.
“It’s not like you’re getting objective, impartial advice,” Felix says. “It’s going to have some bias built into it just based on how it was trained.”
While he thinks AI can be helpful to gauge whether a financial plan is on track, he’d push back on households using the emerging tech to come up with that strategy whole-cloth.
“If you’re trying to decide, ‘Should I contribute to my RRSP or my TFSA?’ I’d be, at this stage, a little bit nervous about that coming from an AI,” Felix says.
Felix also doesn’t see publicly available AI models in their current forms as something he would recommend for stock picks, for example.
Choosing investments, if you want to have an edge, requires having access to information or models that the rest of the markets don’t, Felix explains. Some hedge funds’ internal AI models could be trained to help streamline investment decisions, for example.
But much of the data used to train publicly used generative AI applications is dated, for example, and those tools might not have up-to-date information on market dynamics. An app like ChatGPT, for example, might be able to describe the general makeup of a balanced portfolio but won’t be able to access novel stock tips that aren’t already available in public markets.
Felix contrasts this to robo-advisors available from some financial institutions in Canada that typically have a set of human analysts building portfolios behind a software interface that helps an investor decide which mixes of these assets are right for their risk tolerance.
The BMO survey noted that 68 per cent of respondents felt that AI couldn’t understand how emotions influence financial planning, an assertion that Felix pushes back on.
He says AI can indeed be trained on surveys and data that track emotional responses to money, including how behaviour changes in response to market downturns. AI can be trained to help advisors themselves anticipate client needs during times of distress, he says.
Ramsay says the nature of financial management is less about number-crunching and more about a person’s relationship with money.
While an AI might be able to whip up a financial strategy that makes sense on paper, she says Canadians ought to take plans to a trusted adviser to get a human perspective and make sure that the by-the-numbers proposal makes sense for the level of risk someone is willing to take on.
“You may know logically this is what you should do, but emotionally it may be a little bit different. I think that’s the beauty of talking to a financial planner or a banker in terms of getting to have that other perspective.”
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