The following is a guest article by Susan Mathews, Principal & Founder of Madigail Consulting, LLC a securities compliance consultant providing research and ethics compliance, training and external GC and CCO services to Wall Street research firms. Susan was previously an Enforcement Attorney at the SEC and was the Regulator Liaison for the independent research portion of the SEC’s Global Research Analyst Settlement.
The Compliance Trap: Insider Trading Rules Fail Prediction Markets
State and federal regulators may be locked in a stalemate over how to police prediction markets, but Wall Street cannot wait for the dust to settle. Financial institutions owe a fundamental duty to their clients to safeguard information and ensure employees do not convert workplace insights into personal profits. For research providers, this obligation is paramount; premium clients expect the proprietary intelligence they pay top dollar for will not be compromised by internal trading. Driven by a broad ecosystem of trust, Wall Street employees must uphold their duties of trust and confidence by thoroughly securing all information they acquire on the job.
Current legal and institutional guidance regarding employee prediction market trading is dangerously inadequate. Rather than providing actionable frameworks, regulators, law firms and the prediction markets themselves rely on conventional insider trading definitions, forcing a square peg into a round hole by attempting to evaluate whether information is “material” or banning certain users based on their employer. Respected regulated entities like JPMorgan Chase have taken a defensive posture, advising employees to restrict their participation in these markets simply to mitigate the “perception” of information misuse. These legacy compliance strategies fail to address the core risks inherent to event trading. While this article recommends the safest policy is to prohibit employee event trading completely, it recognizes the need for an alternative, more permissive policy given the realities of current marketplace.
Mounds of Information
Prediction markets allow users to trade on the outcomes of future events – – aka “event trading.” For example: Will Apple beat quarterly earnings? Will GameStop acquire eBay? The thrill of event trading lies in the fact that absolutely any piece of information can be the catalyst for a wager. The information does not have to be a secret to make it tantalizing.
The unique complexity of this market lies in its fragmented information landscape. Rather than relying on auditable documents, information can be derived from decentralized, real-world observations. Take a “channel check” like tracking foot traffic or parked cars at a retail store: an employee could easily use this data to place an event bet on the store’s upcoming earnings. Under traditional insider trading laws, this would be permitted because observations are rarely deemed legally “material.” Yet, because financial services professionals are bound by heightened ethical and fiduciary standards, trading on any job-acquired insight fundamentally violates their duty of trust to their clients and employers. Thus, the employee should not place a bet based on this information even though it passes insider trading tests.
Attempting to police an infinite flow of information is a losing battle for compliance. Even AI has not solved the compliance struggle of defining and detecting “material” information, failing to effectively narrow the universe of data relevant to an insider trading inquiry. Consequently, firms should shift their focus away from information controls and ill-suited insider trading rules. Instead, prediction market compliance should be based on basic concepts of fairness and trust.
Kalshi’s recent decision to mandate employment disclosures for certain users is a well-intentioned but also a fundamentally flawed approach to policing these markets. This initiative fails to account for the expansive nature of information that can be used to commit fraud. Employees do not merely possess sensitive data about their own employers; they regularly gain material insights into partners, vendors, and clients. Consider a Google employee who, by virtue of their role, has access to proprietary information from the platform’s advertising clients. Under Kalshi’s current framework, that individual could trade on confidential client information while remaining entirely undetected. By focusing narrowly on primary employment, the policy fails to capture the true matrix of informational asymmetries in prediction markets. Since the prediction markets themselves have failed to establish safeguards against misappropriation and fraud, Wall Street entities need to take independent action.
Research providers, like all financial entities, are bound by rigorous fiduciary obligations that help our clients trust us. Key elements of these duties include safeguarding client information and never using client information for personal gain. It would be unfair to allow an analyst to personally benefit from information s/he obtained on the job. More broadly, with respect to predictive markets, compliance policies must focus on employee behavior upholding the industry’s core principles of trust and confidence. Conduct-focused policies should be effectuated now, enabling firms to manage risk immediately rather than waiting for regulators to construct a labyrinth of ill-fitted rules derived from insider trading law.
Focus on Conduct, Not Information
While traditional insider trading laws rely on a complex distinction between “material” and “confidential” data, the ethics and compliance policies for prediction markets should be straightforward and easily understood. Your policies should make clear that for event trading, all information an employee acquires during the course of employment must be treated as confidential and proprietary. As such, compliance inquiries should completely bypass legacy insider trading tests, such as public domain status or whether the data would influence a reasonable investor, and instead, focus on whether the employee breached a duty.
If compliance discovers an employee placed an event bet that could be problematic, your policies should establish that the presumption is that the employee breached a duty unless proven otherwise. If the bet touched on any client, competitor, deal, covered company, research report, analysis or any other type of information present within the firm, then the presumption will be that the employee had access to this information and s/he should not have placed a bet that in any way related to it. The presumption has to be in favor of the firm’s clients and the information will be imputed to the employee because it was accessible within the four walls of the firm.
The only way a firm can maintain the higher standard of trust and confidence in a system in which any and all types of information could be relevant to a bet is by imputing knowledge to all firm employees and vowing to protect that knowledge with the due care required to maintain ethical integrity. In practice, this policy will naturally discourage most employees from participating in prediction markets.
Conventional Piecemeal Approaches Fail
Current published legal and compliance approaches offer little practical utility for the unique structure of prediction markets. Some law firms recommend requiring preclearance for all employee event trading. Because the universe of relevant information for event trading is so vast, attempting to preclear a trade presents insurmountable administrative challenges. Compliance officers cannot realistically audit every employee across an organization to determine who possesses relevant information for a future event, making this model unenforceable.
Other guidance suggests implementing heightened reviews of completed employee trades. This backward-looking approach is ineffective as post-trade analysis cannot reveal the specific information an employee possessed at the time s/he placed the bet.
Given the current regulatory uncertainty surrounding prediction markets, the risk of misappropriation and fraud remains high. In the absence of effective legal guidance, firms should proactively institute comprehensive prohibitions on employee participation. Absent an outright ban, firms should implement enhanced compliance controls focused on upholding duties to clients and employers.
Compliance Enhancements
Compliance departments should strictly prohibit employees from engaging in event trading connected to their employment, effectively banning any bets related to the firm’s business. This is a broad compliance mandate. For independent research providers, policies must explicitly define this restriction across their entire coverage universe, industries, and client base. To ensure clarity, firms should provide concrete examples of both prohibited activities and permitted (e.g., wagering on the World Cup, provided no clients or proprietary information overlap with FIFA). Ultimately, these enhanced policies should focus on upholding ethical and fiduciary duties rather than traditional information controls.
Wall Street entities cannot remain silent as prediction markets evolve. Employee participation in prediction markets is already occurring, and these markets present novel compliance challenges that firms need to address proactively. The most effective approach to reduce risk to your firm is to implement clear, forward-looking policies that address prediction-market activity now, while preserving flexibility to adapt as regulatory expectations evolve. A robust prediction markets policy must focus on the unique duty of trust and confidence expected of financial professionals for whom maintaining ethical integrity is paramount.
For more comprehensive legal guidance and compliance policy enhancements, please contact Susan Mathews at 202-486-5716 or MadigailConsulting@gmail.com.
Bio: Susan Mathews leverages more than three decades of financial industry expertise to advise Wall Street entities on critical legal and compliance issues. A former SEC Senior Counsel in the Division of Enforcement, her practice focuses heavily on the unique compliance challenges facing expert networks and independent research providers. Susan brings a wealth of practical leadership to her clients, having served in dual capacities as General Counsel and Chief Compliance Officer for global organizations.