Google Engineer Charged Over Alleged $1.2 Million Polymarket Insider Trading Scheme

A Google software engineer has been charged in New York for allegedly using confidential company information to make more than $1.2 million in trading profits on Polymarket. The U.S. Attorney’s Office for the Southern District of New York said Michele Spagnuolo, also known online as AlphaRaccoon, faces charges of commodities fraud, wire fraud, and money laundering.

Prosecutors allege that Spagnuolo used nonpublic Google data tied to the company’s 2025 Year in Search campaign to place a series of profitable prediction market bets. The trades allegedly focused on Google-related outcomes before the information became public.

The case matters because it shows how confidential corporate data can create insider trading risk beyond stock markets. Prediction markets can also turn internal business information into financial value when employees have privileged access.

What Prosecutors Allege

Spagnuolo worked as a software engineer at Google and had access to internal data systems through his role, prosecutors said. One internal tool allegedly displayed a red “Google Confidential” banner and gave him access to nonpublic search trend data.

The data was connected to Google’s annual Year in Search 2025 campaign, where Google publicly releases trending search lists from the year. Prosecutors say Spagnuolo used that internal information before publication to trade on Polymarket.

According to the DOJ, Spagnuolo created the AlphaRaccoon account on Polymarket in May 2024. Between about October 15 and December 4, 2025, he allegedly risked approximately $2.75 million on markets linked to Google’s internal information.

Case detail	Information
Defendant	Michele Spagnuolo
Online alias	AlphaRaccoon
Employer	Google
Trading platform	Polymarket
Alleged amount risked	About $2.75 million
Alleged profit	More than $1.2 million
Trading period cited by DOJ	October 15 to December 4, 2025

Why Google’s Search Data Was Valuable

Google’s Year in Search lists are public once released, but prosecutors say the internal data behind the campaign was confidential before publication. That gave the information potential trading value on markets tied to future search rankings.

The Associated Press reported that Spagnuolo allegedly placed bets on who would appear in Google’s most-searched people list for 2025. The report said he adjusted trades as internal search data shifted before the public release.

Reuters reported that some bets involved long-shot outcomes on Google’s most-searched list. The Reuters report said the DOJ complaint alleged that the AlphaRaccoon account profited after the public data was released and the related markets resolved.

The Charges and Potential Penalties

Spagnuolo is charged with one count of violating the Commodity Exchange Act, one count of wire fraud, and one count of money laundering. The DOJ said the Commodity Exchange Act charge carries a maximum sentence of 10 years in prison.

The wire fraud and money laundering charges each carry a maximum sentence of 20 years in prison. The final sentence, if there is a conviction, would be decided by a judge.

The DOJ also stressed that the complaint contains allegations. Spagnuolo is presumed innocent unless proven guilty in court.

Charge	Maximum penalty listed by DOJ
Violating the Commodity Exchange Act	10 years in prison
Wire fraud	20 years in prison
Money laundering	20 years in prison

Google and Polymarket Responded to the Case

Google confirmed to AP that Spagnuolo had been placed on leave. The company said the employee accessed marketing material through a tool available to all employees, but using confidential information to place bets violated company policy.

Polymarket said it cooperated with authorities in the investigation, according to Reuters. The company also said its blockchain-based trading model is transparent and traceable.

The case arrives after Polymarket published a market integrity policy that says insider trading is prohibited. The policy says users may not trade on contracts when they possess confidential information about the outcome and using that information would violate a duty of trust or confidence.

Why Prediction Markets Create New Insider Threat Risks

Traditional insider trading cases usually involve securities. This case shows how prediction markets can create similar risks when employees use private company information to bet on event outcomes.

A company does not need to be publicly traded for internal information to have market value. Search trends, product launch dates, regulatory outcomes, marketing data, private metrics, and operational decisions can all become tradable signals if a prediction market exists for the outcome.

This creates a new challenge for compliance and security teams. Insider risk programs need to cover more than stock trades and merger information. They also need to address event contracts, crypto-based markets, and platforms where employees can monetize confidential business data.

What Companies Should Learn From the Case

• Review which employees can access sensitive marketing, search, product, and analytics data.
• Add prediction market restrictions to insider trading and ethics policies.
• Train employees that confidential business data cannot be used for betting or event contracts.
• Monitor unusual access to internal data before major public releases.
• Use just-in-time access for sensitive internal dashboards where possible.
• Flag large downloads, unusual queries, and access patterns outside job duties.
• Coordinate insider risk monitoring across legal, security, HR, and compliance teams.

The Role of Internal Access Controls

Insider cases often involve legitimate access, not stolen credentials. That makes prevention harder because the user may have permission to open the tool, even if they later misuse the information.

Organizations should not rely only on access approvals. They also need logging, data classification, alerts on unusual access, and clear rules about using confidential data outside approved business tasks.

For major public releases, companies should consider tighter controls around pre-release data. That includes smaller access groups, temporary access windows, and additional monitoring before publication dates.

Prediction Markets Are Facing More Scrutiny

Prediction markets allow users to trade contracts tied to real-world outcomes. The price of a contract can reflect the market’s view of how likely an event is to happen.

The problem arises when some traders know the answer before everyone else. The Polymarket market integrity policy directly addresses this by banning trades based on stolen confidential information, illegal tips, or the ability to influence an event outcome.

Google’s public Year in Search page shows the final 2025 search lists after release. Prosecutors allege Spagnuolo traded before that information became public, when the internal data still gave him an unfair advantage.

The Bottom Line

The charges against Spagnuolo show how insider trading enforcement is moving into prediction markets. Prosecutors argue that confidential business information cannot be used for personal profit simply because the trade happens outside traditional stock markets.

For companies, the case is also an insider risk warning. Confidential data can create financial incentives in more places than before, and employee policies need to reflect that shift.

The AP report said Google is cooperating with law enforcement, while the DOJ announcement said the case is being handled by the Securities and Commodities Fraud Task Force.

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