Prediction markets function economically like gambling venues but operate in a regulatory gray zone with weak AML controls; meanwhile, banks and payment processors must assess their risk based on actual behavior, not labels, to address potential financial crime exposure
Key insights:
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Prediction markets sit in a regulatory gray zone — Prediction markets’ economic function often looks much closer to gambling than traditional finance.
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That ambiguity creates an AML blind spot — This blind spot allows potentially weaker controls around KYC, source of funds, sanctions screening, and suspicious activity reporting.
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Banks and payment processors should focus on actual risk, not labels — Reputational, legal, and financial crime risk exposure can arise long before regulators clarify the rules.
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Prediction markets have grown into a multi-billion-dollar ecosystem, offering the ability to enter into a contract to predict the outcomes on everything from elections and sports games to economic data and weather events. Yet as these platforms expand, they operate in a regulatory gray zone that raises serious questions for banks, payment processors, and compliance professionals.
Yet, the classification question that regulators and financial institutions continue to debate is not merely academic. It determines whether prediction market platforms will face the same anti-money laundering (AML) and know-your-customer (KYC) obligations as casinos and sportsbook venues, or whether prediction markets can continue to operate with minimal compliance oversight. This distinction has real consequences for the financial system.
“Prediction markets are not just a classification problem, they represent a structural gap in how financial crime risk is currently understood and managed,” says James Lephew, Founder & CEO of Anti Financial Crime Group (AFC Group), a Charlotte-based consulting firm that serves major gambling operators and financial institutions globally.
Clarification is required in classifying this sector
Prediction markets occupy an ambiguous middle ground. Market operators position their platforms as financial derivatives or forecasting tools rather than gambling venues, emphasizing price discovery and statistical analysis over chance-based wagering. A contract on the outcome of a presidential election or a sports event, they argue, reflects crowd-sourced probability estimates grounded in information aggregation, not gambling luck.
Yet the fundamental mechanics raise legitimate questions. A user who buys a contract predicting that a candidate will lose an election is, in economic terms, wagering money on an uncertain outcome. The distinction between betting on a football game and trading a contract on the outcome of that same game becomes difficult to defend from a regulatory standpoint — and this classification matters enormously.
The distinction between betting on a football game and trading a contract on the outcome of that same game becomes difficult to defend from a regulatory standpoint — and this classification matters enormously.
If prediction markets are treated as gaming operations, they trigger Title 31 obligations under the Bank Secrecy Act, including currency transaction reporting, suspicious activity reporting (SAR) requirements, and comprehensive KYC procedures. If on the other hand, prediction markets are classified more akin to financial markets, these requirements may not apply. Currently, many prediction market platforms claim financial market status, allowing them to operate outside gaming regulations and with potentially weaker AML controls.
There is a compliance gap
Without clear regulatory classification, prediction markets create a significant AML blind spot. Casinos must report cash transactions exceeding $10,000, conduct source-of-funds reviews, and maintain detailed customer profiles. Sportsbooks face licensing requirements, geolocation checks, and responsible-gaming safeguards. Prediction market platforms, by contrast, often operate with minimal reporting obligations.
This gap introduces concrete risks. Digital wallets and cryptocurrency channels can obscure the source of funds. Structuring and layering of sources become easier without robust verification, further clouding who exactly playing in these markets. Collusive trading through multiple accounts allows value transfer that may go undetected. And VPN use and foreign payment channels can enable sanctions evasion.
Further, without mandatory SAR reporting, suspicious patterns tied to money laundering, terrorist financing, or market manipulation may never reach law enforcement.
“What we’re seeing is an AML blind spot,” says Lephew. “Platforms enabling financial flows with characteristics of gambling, but without the controls that regulators would normally expect.” Until classification catches up with the technology, he adds, this blind spot remains open — and exploitable.
Why this matters for banks and processors
Banks and payment processors that support prediction market platforms may carry significant reputational and legal risk if they haven’t conducted thorough due diligence — and they cannot rely on a platform’s self-classification as a financial market or forecasting tool. Nevada and other jurisdictions are actively examining whether these platforms constitute gambling, echoing concerns from the American Gaming Association that products carrying similar economic risks deserve similar regulatory treatment.
If a product allows participants to wager on uncertain outcomes and creates risk that is substantially similar to gambling, it should face AML and customer identification requirements proportionate to that risk.
“Risk must be assessed based on how the product actually behaves, not how it is marketed,” Lephew explains. And that means evaluating whether a platform applies robust KYC procedures, verifies the source of deposits and beneficial ownership, screens against sanctions lists, reports SARs to the government, prohibits contracts on high-risk events such as assassinations or terrorism, and uses geolocation controls to block users in restrictive jurisdictions. Those answers matter far more than whatever label the platform chooses, Lephew says.
The path forward
Regulators have several options. One approach applies gaming regulations uniformly, treating all prediction markets with economic characteristics similar to gambling as gaming operations subject to Title 31. A second approach creates explicit financial market classification with statutory AML obligations and enhanced scrutiny of high-risk contracts. A third option adopts a tiered or risk-based framework, classifying contracts on lower-risk events such as economic data or weather under financial market rules, while sports and election markets could face enhanced scrutiny. Violent outcome markets would be prohibited entirely.
Regardless of which path regulators choose, the principle should be the same: Classification should follow economic function. If a product allows participants to wager on uncertain outcomes and creates risk that is substantially similar to gambling, it should face AML and customer identification requirements proportionate to that risk.
Financial institutions should not wait for regulatory clarity. They should apply rigorous due diligence now, treating prediction markets with a heightened level of scrutiny appropriate to their actual risk profile rather than their claimed legal status.
The goal is not to eliminate prediction markets, but to ensure they operate within a framework that prevents money laundering, terrorist financing, and market abuse. “If it looks like gambling, behaves like gambling, and carries the same financial crime risk, it should be regulated accordingly,” Lephew notes. “Anything less creates systemic exposure.”
You can find out more about the challenges financial institutions face in their anti-money laundering efforts here
