AI in capital markets – exploring use cases in Ontario
From the trading floor to the back-office, capital market participants are leveraging diverse AI systems to do things faster, better, cheaper by streamlining complex tasks, optimizing processes and uncovering hidden insights and trends, all while learning and refining their capabilities. At the same time, the disruptive nature of AI has raised important questions about the role of regulation and governance in managing risks and the potential for malicious use.
The information on this page is derived from a report on AI in capital markets prepared in collaboration between the OSC and EY. The report explores current AI use cases, value drivers and challenges. By exploring these use cases, we aim to raise awareness of the many ways in which AI is starting to transform capital markets and help Ontario’s market participants, innovators and policy makers as they grapple with the transformative potential of AI.
Key insights
Capital market participants are currently using AI to enhance their existing products and services rather than creating new ones.
AI is at an intermediate stage of adoption in Ontario’s capital markets.
The key value drivers of AI adoption in capital markets include:
- Enhanced capacity to extract information and insights from enormous volumes of structured and unstructured data.
- Greater automation of manual processes that involve handling and managing data.
- More precise predictive analytics.
- Better liquidity forecasting and hedging.
- Increased end-user satisfaction through more personalized service.
The most mature use of AI in capital markets is focused on three principal areas:
- Improving the efficiency and accuracy of operational processes.
- Trade surveillance and detection of market manipulation.
- Supporting advisory and customer service.
Areas such as asset allocation and risk management show less maturity in Canada.
Scale is important for the development of AI models: larger firms appear to be developing in-house solutions and using AI in areas with financial risk more than smaller firms.
AI development primarily occurs in-house within Ontario.
While capital market participants continue to employ and explore a range of AI techniques, natural language processing is the most commonly used.
Major challenges remain for AI adoption, including data constraints, accessing skilled labour, corporate culture and governance.
AI use cases in capital markets
Currently, capital market participants are primarily adopting AI systems for three overarching purposes: to improve efficiency, generate revenue and manage risk.
AI solutions are being rolled out in a phased approach, prioritizing low-risk applications such as generating news summaries and policy insights. Higher risk applications, like those that fall under the categories of risk management and revenue generation, are being used in a limited way or for comparison purposes with human supervision.
AI GRAPH ENThe role regulators can play
Right now
AI has the potential to impact processes and stakeholders throughout our capital markets from investors to businesses, professionals, intermediaries and marketplaces. This research provides a foundation for us to consider how to best support responsible innovation and adoption in Ontario’s markets including the extent to which oversight, regulation or guidance can support this objective.
AI innovation may offer significant efficiencies, enable new solutions and new entrants, and attract investment to Ontario’s AI businesses. These gains to productivity, competition and capital formation can ultimately contribute to economic growth for Ontario. At the same time, the disruptive nature of AI systems has raised important questions about the role of regulation and governance in managing risks as well as the potential for malicious use.
While AI can be a meaningful asset to the extent it is used to prevent, detect, and deter unfair and fraudulent practices, it is essential for regulators to consider how to best protect investors from its dishonest use by unscrupulous actors. Likewise, it is important for both regulators and market participants to understand the potential for AI to impact markets to ensure that appropriate safeguards are in place to maintain the continued stability of our financial system.
Through a proactive approach to technological innovation and the building and sharing of knowledge, we can continue to foster innovative and globally competitive capital markets in Ontario that put investors first, help innovative businesses succeed and attract investments from around the world. As we do so, collaborating with other regulators and governments is key to ensuring consistent and effective regulation of this space.
Moving forward
Capital market regulators are one of many bodies whose standards will impact how responsible AI is adopted in Canada. Consistent regulation requires ongoing collaboration among federal and provincial governments, securities regulators and financial services regulators. In addition to cross-Canadian collaboration it also requires international dialogue through global forums, such as the International Organization of Securities Commissions, which is ongoing.
AI’s adoption in Ontario’s capital markets is still growing, with varying levels of maturity across different functions. Right now, it’s mainly used to make operations more efficient in areas with low-risk, cost, and regulatory constraints.
As the use of AI grows, so too does the risk that some actors will seek to exploit it for malevolent purposes. Regulators need to understand AI’s uses prior to wide-scale industry adoption to be better equipped to assess and mitigate risks while supporting its responsible deployment.