Prediction markets allow users to trade on the outcome of real-world events. Instead of betting against a bookmaker, participants take positions against one another, with prices reflecting the perceived probability of an event occurring.
These events range from elections and economic indicators to corporate announcements, entertainment outcomes and geopolitical developments. In practice, they operate like simplified derivatives markets, often framed as “event contracts”.
Polymarket is one of the most prominent platforms in this space. It enables users to trade using cryptocurrency, typically via blockchain infrastructure such as Polygon, with transactions recorded on-chain. This gives a veneer of transparency while allowing users to operate pseudonymously.
The combination of real-world events, financial incentives and low friction access has driven explosive growth. For compliance professionals, they present a new category of risk that cuts across insider dealing, confidentiality, conflicts of interest and even national security concerns.
When prediction markets collide with inside information
The core compliance risk is straightforward. Employees who have access to non-public, confidential or commercially sensitive information may use that knowledge to place highly informed bets.
Recent examples illustrate how prediction markets can be used, or at least appear to be used, by individuals with privileged information:
- Traders placed large, well-timed bets ahead of US military actions in Iran and Venezuela, generating hundreds of thousands of dollars in profit
- Blockchain analysis identified accounts that collectively made significant profits by betting on the precise timing of geopolitical events
- Israeli authorities charged a reservist for allegedly using classified information to place bets on Polymarket
Even where insider information cannot be proven, the pattern of behaviour is familiar to any compliance professional who has dealt with market abuse: unusual timing, disproportionate position sizing, and outcomes that are statistically improbable without an advantage of insider or privileged information.
The difference is that prediction markets sit outside traditional financial instruments. Many firms’ surveillance, pre-clearance and restricted list controls do not capture them at all.
Are prediction markets regulated?
Prediction markets currently exist in a contested legal space. Operators such as Polymarket argue that they offer lawful financial contracts regulated at the federal level in the United States. Critics, including state regulators and lawmakers, argue that they are effectively unlicensed gambling platforms exploiting regulatory gaps.
The regulatory picture is shifting quickly:
- Multiple US states have issued cease-and-desist orders or pursued litigation
- At least 20 federal lawsuits are challenging the legal classification of these platforms
- The Commodity Futures Trading Commission has issued guidance on managing manipulation and insider trading risks
- Proposed legislation seeks to restrict or ban certain types of prediction market activity
Platforms themselves are attempting to get ahead of this scrutiny. Polymarket has introduced rules prohibiting trading on confidential information, misuse of position or influence, and tip-based trading.
However there is a structural limitation. Current enforcement largely relies on the platform detecting misconduct in pseudonymous, crypto-based trading environments. That is a very different control environment from regulated securities markets.
How might prediction markets cause a compliance issue?
There’s a difference between individuals without access to privileged information using a prediction betting service, and those that potentially might. It depends whether anyone in your organisation could, potentially, have access to information that could in some way be considered privileged, insider, or in other ways restricted. Because prediction markets are not only focused on traditional betting subjects, but potentially any subject at all, it vastly increases the information areas that compliance should consider as potentially sensitive.
Hypothetical 1: UK-listed firm, market-sensitive information and prediction markets
A senior analyst at a UK-listed retail company is involved in preparing internal forecasts ahead of a trading update. The data shows a significant earnings miss that has not yet been disclosed to the market. The analyst is subject to standard controls. They are on an insider list. They are prohibited from dealing in the company’s shares during a closed period. They have completed insider dealing training.
However, those controls are built around securities trading. Separately, the analyst holds an account on Polymarket. A contract is listed asking whether the company will issue a profit warning within the next 30 days. Using a personal crypto wallet, the analyst takes a large position on “yes”. The profit warning is announced two weeks later. The analyst realises a substantial gain.
The firm’s existing surveillance does not detect the activity. There is no personal account dealing declaration covering prediction markets. No alerts are triggered and the issue surfaces externally. A third-party analytics firm flags unusual trading patterns on the prediction market. The timing and size of the bet stand out. The wallet is linked, through off-chain analysis and exchange records, to the analyst.
Even though the analyst did not trade in securities, the conduct raises serious issues:
- Misuse of inside information under the UK Market Abuse Regulation (MAR), particularly under the misappropriation theory
- Breach of confidentiality and fiduciary duties owed to the employer
- Potential failure of the firm to maintain effective systems and controls under the FCA Handbook
The FCA is likely to focus less on the technical instrument used and more on the substance of the behaviour. The core question is whether inside information was used for personal gain. The firm faces scrutiny on:
- Whether its policies adequately addressed non-traditional trading channels
- Whether training covered emerging risks such as prediction markets
- Whether insider lists and controls were sufficiently robust
Hypothetical 2: International defence contractor and geopolitical prediction markets
A UK-headquartered defence and aerospace company is part of a multinational consortium supplying equipment under a sensitive government contract.
A programme manager working within the firm has access to restricted briefings indicating a high probability of imminent military action involving a specific region. The information is not public and is subject to strict confidentiality obligations. At the same time, prediction markets are actively trading on whether military action will occur within a defined timeframe.
The employee uses a private crypto wallet to place a series of bets on the timing of the conflict via Polymarket. The bets are large, concentrated and unusually precise. This is picked up among other users and is reported on mainstream news. When military action occurs, the positions generate significant profit.
Law enforcement agencies begin investigating potential leaks of classified or sensitive information. Blockchain tracing links the wallet activity to a crypto exchange account. KYC records identify the employee.
This scenario escalates beyond financial regulation:
- Potential criminal liability relating to misuse of classified or restricted information
- Breaches of national security legislation in relevant jurisdictions
- Serious violations of confidentiality obligations under government contracts
For the firm, the exposure is acute:
- Failure to safeguard sensitive information
- Potential breach of contractual obligations with government clients
- Regulatory scrutiny across multiple jurisdictions
The compliance risk for firms
Perhaps the most critical risk is that prediction markets can actively incentivise insider behaviour. The financial upside for being “first to know” creates a direct incentive to disclose or act on confidential information. In extreme cases, this has raised concerns about national security, where advance knowledge of military action could be monetised or even indirectly signalled through market activity For compliance, prediction markets create a convergence of several well-understood risks in a new and much more dangerous context.
Misuse of confidential information
Employees may use client data obtained under NDA, proprietary research, modelling or analysis or commercially sensitive internal information to take positions on events linked to that information.
Even where the information does not meet the strict definition of material non-public information for securities law purposes, its misuse can still breach confidentiality obligations and internal policies.
Conflicts of interest
An employee who stands to profit from a specific outcome may have their judgement compromised in their professional role.
The conflict can quickly become direct and financial, especially for employees who do not have extensive experience in handling non-public or sensitive information. An individual could be incentivised, consciously or otherwise, to shape advice, delay decisions or influence outcomes in ways that benefit their personal position.
Circumvention of existing controls
Most firms have well-developed frameworks for things such as personal account dealing, restricted lists or insider trading surveillance. However these frameworks are typically designed around traditional securities markets. Prediction markets fall outside their scope. As a result, employees can engage in economically similar behaviour without triggering any controls.
Reputational and contractual exposure
If a firm’s employees are found to have used client or proprietary information to place bets, then client trust is damaged, contractual obligations may be breached, and regulatory scrutiny could easily follow. Firms should prioritise informing their employees that confidential information is an asset. Using it for personal gain is, in substance, a form of theft.
What should firms do now?
This is not an area where firms can rely on generic policies and assume coverage. Any organisation with potential access to confidential information should consider taking a more explicit and targeted approach.
Take a clear policy position
Firms should decide whether to:
- Prohibit employee participation in prediction markets altogether
- Allow it subject to strict conditions
- Treat it as a form of personal trading requiring approval
Update codes of conduct and conflicts policies
Most codes of conduct predate the rise of prediction markets. They should be updated to explicitly address:
- Betting or trading on real-world events using non-public information
- Use of company or client information in any financial context
- Conflicts arising from positions taken on external platforms
Employees need concrete examples. General principles are often too abstract to guide behaviour in new contexts.
Extend insider information controls
Firms should consider:
- Whether insider lists should cover event-based information, not just securities
- Whether certain roles should be restricted from participating in relevant markets
- How material non-public information is defined in a broader, non-securities context
Training and awareness
This is a classic case where employees may not realise the risk. Training should cover:
- How prediction markets work
- Why they create insider trading and confidentiality risks
- Real-world examples of misuse
Without this, firms are relying on intuition in an area where the boundaries are not obvious.
Monitoring and surveillance
Direct monitoring of decentralised platforms is challenging. That said, firms can:
- Incorporate attestation requirements into personal trading declarations
- Monitor for references to prediction market activity in communications
- Track markets that directly relate to the firm, its clients or its sector
This is as much about early detection as it is about deterrence.
Scenario testing and risk assessment
Compliance teams should ask:
- What information do our employees hold that could be monetised on these platforms?
- Where would we be most exposed?
- How would we detect misuse?
This moves the issue from abstract concern to concrete risk management. Firms may not be able to prevent determined actors from abusing insider information, but they can reduce the risk of staff doing so unknowingly or unwittingly. Regulators will expect to see some effort in this area for firms most at risk.
