Canadians are using artificial intelligence (AI) to access financial information, advice and recommendations. Find out more about an Ontario Securities Commission (OSC) study looking at retail investor decision-making and the risks and benefits of advice from AI systems.
On this page you’ll find
Why study AI and retail investor decision-making?
Many Canadians are starting to use artificial intelligence (AI) tools in retail investing. Using AI presents a range of both new opportunities and potential risks for investors. As the use of AI increases, regulators around the world, including the OSC, are examining the risks AI could pose to investors while continuing to support innovation.
Improving the investor experience is a key priority for the OSC. That’s why the OSC conducted research to understand how investors react when they think advice is being provided by AI. A behavioural science experiment was conducted to explore the impact of AI on investor decision-making. And researchers identified common uses of AI that impact investors.
Read the full report: Artificial Intelligence and Retail Investing: Use Cases and Experimental Research
How was the experiment conducted and what did it find?
The experiment looked at how the source of an investment suggestion — AI, human, or a blend of the two — impacts whether investors follow that suggestion.
Participants were given a hypothetical $20,000 to invest in an online simulation. Participants who were not in the control condition were introduced to WealthTogether — a fictitious financial services firm, to help them decide how to allocate their funds. They were then introduced to one of three WealthTogether financial services providers:
- A person named Alex.
- A person named Alex who is using an AI tool to inform their suggestions.
- An AI tool named Kai.
After participants received the suggestion, they allocated the full $20,000 across any combination of equities, fixed income, and cash. They did not have to follow the suggestion they were given, but were free to invest the money any way they chose.
OSC researchers then measured how closely participants followed the investment suggestion. People who received the investment suggestion from a human using an AI tool (‘blended’) adhered to the investment suggestion most closely, although this difference was not significant.
There was also no significant difference in adherence to investment suggestions provided by a human or an AI tool. This indicates Canadian investors are receptive to taking advice from an AI system. Canadians may have an explicit or implicit view that the benefits of either human or AI investment advice can be maximized by combining the two.
This research underlines the need to ensure that AI systems investors use for financial information or advice are based on unbiased, high-quality data, and prioritize the best interests of investors rather than the firms who develop them.
How is AI currently being used in retail investing?
OSC researchers examined current investor-facing uses of AI in Canada and abroad through a literature review and environmental scan. Three common uses were identified:
- Decision support: Involves AI systems that provide recommendations or advice to guide investment decisions.
- Automation: Consists of AI systems that automate portfolio and/or fund (e.g., ETF) management.
- Scams and fraud: Includes AI systems that either facilitate or mitigate scams targeting retail investors, as well as scams capitalizing on the “buzz” of AI.
What are the benefits and risks of using AI in retail investing?
Several key benefits and risks were identified in the research.
The benefits of using AI in retail investing include:
- Reduced cost: AI systems can reduce the cost of personalized advice and portfolio management. This can create considerable value for retail investors.
- Access to advice: More sophisticated and properly regulated AI systems can provide increased access to financial advice for retail investors. This is particularly important for people who cannot access advice through traditional channels.
- Improved decision-making: AI tools can be developed to guide investor decision-making around key areas such as portfolio diversification and risk management, as well as tools to assist investors in identifying financial scams.
- Enhanced performance: Existing research has shown that AI systems can make more accurate predictions of earnings changes and generate more profitable trading strategies compared to human analysts.
The risks of using AI in retail investing include:
- Bias: AI models are generally subject to the biases and assumptions of the humans who develop them. For example, an AI system developed by people employed by a specific company may be biased towards promoting that company’s products, even when buying those products is not in the investor’s best interests.
- Herding: The concentration of AI tools among a few providers may induce herding behaviour, convergence of investment strategies, and chain reactions that exacerbate volatility during market shocks.
- Data quality: If an AI model is built on poor data quality, then the outputs, whether advice, recommendations, or otherwise, will be of poor quality as well.
- Governance and ethics: The ‘black box’ nature of AI systems and limitations around data privacy and transparency create concerns around clear accountability in cases where AI systems produce adverse outcomes for investors.
Artificial Intelligence and Retail Investing: Use Cases and Experimental Research builds on the OSC’s existing research in the area of artificial intelligence. It also reinforces the benefit of using behavioural science as a policy tool by regulators. As AI continues to advance in capabilities, more research is needed to help capital markets stakeholders better understand the implications for retail investors.
The OSC partnered with the consulting firm Behavioural Insights Team (BIT) to conduct this research. The experiment included 7,771 Canadian residents aged 18 years and older. Current investors made up 60% of the sample, with 40% of participants being non-investors.
