Prediction Market Data and Economic Nowcasting: A 90-Day Compliance Plan
Prediction markets let participants trade contracts whose payoff depends on future events such as elections, central-bank decisions, or economic releases. Prediction market prices are often presented as implied probabilities, which can potentially be useful or harmful or both to securities firms and their clients. For Canadian securities firms, the core questions are how these data derived from prediction markets enter securities firms, what they are allowed to influence, and what steps legal and compliance teams should take to address them now.
Two questions should be analyzed separately: (i) whether the firm may use prediction-market data in client-facing activities, investment processes, valuation, and governance; and (ii) whether employees may personally trade or wager on prediction markets where they have access to sensitive or market-moving information. The practical response is to separate firm-level use rules from employee-conduct rules and to define disallowed, tightly controlled, and limited permitted activities for each.
Why the data matter and why they are risky
Prediction-market data update continuously and can appear to offer real-time probabilities for macro, policy, and event outcomes between conventional reporting cycles, which can make them attractive to research, trading, and strategy teams. But many contracts are thinly traded, motives for traders range from hedging to profit-seeking to pure entertainment, and participation may be concentrated or opaque, so an apparently precise number may rest on fragile or distorted market structure.
The compliance concern is that these prices can look authoritative while relying on venues that are hard to validate, supervise, or explain to clients, auditors, and regulators. Thin liquidity, pseudonymous activity, and the possibility of manipulation all raise questions about source reliability. Some contracts concern outcomes that can be anticipated or influenced by a small group of insiders, creating material non-public information (“MNPI”) and insider-trading risks. Canadian regulators have also signaled that event contracts that are securities or derivatives must comply with core securities-law requirements.
Client-facing use
Client-facing use covers research distributed to clients, advisory and suitability processes, discretionary management, product design, valuations, and any recommendation that may influence client outcomes. For most securities firms, prediction-market data should not be used as a direct or primary input in these activities, because they are not required to discharge regulatory obligations, and they may add more risk than value.
Firms should consider very carefully any use of prediction-market data to drive client recommendations, suitability determinations, investment decisions, valuations, or product-governance outcomes, ensuring that client disclosures are current and robust. Firms should bar them from marketing materials, newsletters, research notes, and webinars that might treat the numbers as authoritative. If any client-facing use is permitted, it should be exceptional, extensively disclosed, and tightly controlled, for example as one clearly labelled indicator of sentiment in institutional research rather than a trade trigger.
Internal firm use
Internal use covers desk discussions, strategy meetings, dashboards, research decks, and non-public tools that do not directly face clients. Firms should seriously consider barring uses where prediction-market data would feed into production trading signals, order generation, risk limits, live hedging, valuation methodologies, or formal governance processes.
A narrow set of tightly controlled internal uses could be allowed, such as horizon scanning or scenario planning by macro or strategy teams, provided sources are approved, the data are not treated as authoritative, their use is disclosed to clients, and there is a rule against migration into production decisions without explicit approval. The most defensible generally permitted use is likely informal horizon scanning, where prediction-market sentiment is treated like media commentary and cannot alone drive a decision, recommendation, valuation, or client communication.
Employee personal use
Even if firm-level reliance is banned, employees may still open accounts or place wagers on prediction markets, so codes of conduct need to address these activities expressly. Policies should prohibit using confidential commercial, operational, regulatory, governmental, counterparty, customer, issuer, or transaction-related information for personal gain through prediction markets and should bar trading or wagering on contracts tied to the firm, its clients, active mandates, pending offerings, or sectors where the employee has access to sensitive information.
Some firms may adopt a complete prohibition on employee participation, especially for high-risk roles, while others may permit limited activity subject to pre-clearance, account disclosure, restricted lists, blackout periods, and certification that expressly covers event-contract accounts.
Training, governance, and surveillance
Training should clearly distinguish firm use from employee conduct. Front-office, research, and product personnel need concrete guidance on when the firm may not use prediction-market data in recommendations, suitability, or valuations, while all employees need practical examples of prohibited prediction market participation based on confidential information, even where the contracts do not look like traditional securities.
Governance should also start from the separation of client-facing use, internal use, and employee conduct. Firms should maintain a register of approved and prohibited sources, specify where any approved source may be used, conduct ongoing vendor diligence on provenance and market-integrity controls, and link communications surveillance with trade surveillance to test whether unusual moves in event-contract prices precede unusual trading or recommendations.
A practical 90-day plan for firms
For implementation, firms should distinguish from the outset between client-facing restrictions and employee-conduct controls, focusing on keeping speculative event-contract signals tightly controlled or entirely absent from product review and investor communications while extending employee-conduct rules to personal event-contract trading.
Days 1 to 30: discovery and immediate containment
Designate an owner, likely the Chief Compliance Officer or another senior compliance lead, and form a small working group including legal, compliance, risk, supervision, and relevant product or distribution personnel. Inventory where prediction-market data appear or are likely to appear in research notes, investment committee materials, sales decks, KYP files, suitability tools, vendor feeds, internal chats, and employee processes, while pausing any client-facing use and reminding employees that existing MNPI and conduct rules apply to event contracts.
Days 31 to 60: define allowed and disallowed activities
Draft or revise policies so that prediction-market rules are clear, producing a matrix that separates disallowed and allowed client-facing uses, tightly controlled internal uses, disallowed employee activities, and any limited employee activities subject to pre-clearance and disclosure. Prediction-market data should ordinarily be disallowed or extremely tightly controlled and disclosed in product approval and external communications, with only narrow non-binding internal uses and either prohibition or strict pre-clearance for personal trading.
Days 61 to 90: implement, train, and validate
Approve revised policies and procedures, update supervisory procedures, and embed controls into product-review templates, client-facing content, restricted list processes, disclosure requirements, and surveillance lexicons. Deliver targeted training, obtain attestations from relevant personnel, and conduct a follow-up review to confirm that high-risk uses have been removed, exceptions are documented, and uses are disclosed.
Practical compliance position
For most Canadian securities firms, prediction-market data are best treated as a speculative and potentially suspect source of sentiment or idea generation, not a dependable input for trading, suitability, valuation, or client recommendations. A clear separation and containment strategy—bright lines around disallowed uses, narrow documented internal uses if any, and explicit coverage of prediction markets in MNPI, account-disclosure, and code-of-conduct frameworks—offers the strongest and most defensible compliance position until the Canadian framework and market-integrity controls mature.
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Next Steps with North Star Group
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About the Authors
Michael Holder (B.A. Western, LL.B. Windsor, MBA, Western) is the Managing Partner of North Star Legal, bringing more than 20 years of wealth management, legal, and compliance experience in Canada’s financial services sector. Having acted as Associate General Counsel and Chief Compliance Officer of Wealthsimple, Senior Legal Counsel at BMO Financial Group and a partner of one of Canada’s largest firms, Michael combines his practice and advisory work with teaching Fintech and Disruption of Banking at Ivey Business School.
Read Michael’s full bio here.
Martha Rafuse (B.A. Western, LL.B. Osgoode, LL.M London School of Economics), Counsel at North Star Legal, brings more than two decades of securities regulatory experience across the financial industry, private practice, and government. Before joining North Star Legal, Martha led large compliance teams for both Canadian and U.S. firms, including RBC Phillips, Hager & North Investment Counsel Inc., and RBC Dominion Securities Inc. (Retail). As Legal Counsel at the Ontario Securities Commission, Martha developed legal solutions for novel regulatory issues and led significant policy initiatives.
Read Martha’s full bio here.