This month, the Ontario Securities Commission
(OSC) in collaboration with Ernst & Young LLP
published its first report (the Report) on
the adoption and use of artificial intelligence
(AI) in Ontario’s capital markets. The
Report canvasses the ways AI is currently being utilized to support
capital market processes including asset allocation, price and
liquidity forecasting, hedging, trade order execution and
surveillance, high-frequency trading, futures market analysis, and
sales and marketing.

The Report notes that the current AI landscape in Ontario is
already strong and internationally competitive, citing Vector
Institute Reports which noted significant spending on AI research
and development in Ontario as well as over $2.8 billion in venture
capital investment in Ontario’s AI ecosystem from 2021-2022.
The influx of spending on AI related applications, the uptick in
new AI companies founded in Ontario and the corresponding increase
in AI-related jobs all suggest that supporting the responsible
development of AI systems can be a significant contributor to
economic growth in Ontario.

Through interviews conducted with Ontario capital market
participants, the Report identified three overarching purposes for
which market participants are adopting AI systems –
efficiency improvements, revenue generation, and risk mitigation.
The Report found AI could contribute to improvements in
efficiencies for firms through things like improved pre- and
post-trade processes automation, execution quality improvement
through better liquidity forecasting, and improved customer
services through the use of customer support chatbots which can
interface with customers and help address common questions.

With respect to revenue generation, the Report found that firms
were leveraging AI’s ability to draw insights from previously
untapped datasets, to provide deeper insights into client
relationships and clients themselves, and for the development of
sales strategies and bespoke marketing materials. The Report also
found AI was being effectively used as a risk management tool for
things like AML, trade surveillance, hedging, and onboarding
processes.

The Report also comes with a word of caution noting the various
challenges and risks associated with the burgeoning adoption of AI
applications. “Explainability,” for example, has proven
to be one of the main hindrances to the broader adoption of AI
models in capital markets. Given the complex workings of AI models
and significant difficulties explaining how certain computational
systems function, AI models may not garner the trust of parties who
are uncomfortable relying on a system that cannot be cohesively
explained.

There are also significant data-related concerns including
difficulties for organizations in terms of data aggregation,
quality, and consistency. The reliability of AI models is
predicated on the quality and reliability of the data being
synthesized, all of which occurs under a complex data protection
and privacy framework which requires specific consent for the use
of customer data. The Report also identified various risks unique
to AI models which require specific governance measures beyond
those traditionally employed by firms. The Report suggests that an
AI-specific governance framework can be an important tool to ensure
that the culture of accountability and compliance extends to the
responsible use of AI. This can help address a situation where an
advisor is too reliant on AI tools and is unable to recognize if
flawed data is providing poor or biased recommendations that are
not in a client’s best interest.

The Report characterizes the adoption of AI in Ontario’s
capital markets as being at an intermediate stage with varying
levels of adoption, integration, and maturity across different
functions. As capital market participants continue to embrace AI
innovations, the Report reminds market participants that enthusiasm
should be tempered with a sensible implementation approach which
prioritizes the protection of investors and the integrity of
Ontario’s capital markets.

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