SEC complaint: $12.3M raised, only 3% used for crypto. Fuller admitted Ponzi in bankruptcy. Checklist of red flags for AI trading frauds.
The Securities and Exchange Commission filed a complaint against Nathan Fuller in the US District Court for the Southern District of Texas, alleging he ran a Ponzi scheme disguised as an AI-powered crypto trading operation. Fuller raised $12.3 million from about 150 investors through his company Privvy Investments, LLC and his assumed business name Gateway Digital Investments. Only $380,000 – roughly 3% of the total – ever touched a crypto exchange.
The scheme ran from at least October 2022 through mid-2024. Fuller told investors his proprietary AI-driven trading bots could deliver returns exceeding 100% in as little as 21 days or over 50% within 30 to 45 days. He framed the investments as low-risk, citing a supposed 3% stop-loss feature that would protect against downside.
To build trust, Fuller manufactured credentials that any experienced investor could check but that his targets apparently did not. He claimed to hold a money transmitter license that did not exist. He told investors his venture carried FDIC insurance, which applies only to bank deposits, not crypto trading ventures. He also produced fictitious performance statements showing returns exceeding 334%.
Key insight: Any investment promising 100% returns in 21 days with 'low risk' is almost always a fraud. A money transmitter license can be verified with a state regulator. FDIC insurance covers deposits, not trading profits.
Fuller solicited investors through word-of-mouth referrals, a public website, and social media campaigns. He promoted what he called 'joint-venture opportunities' in a supposed crypto asset trading venture. Crypto market analysis shows that genuine AI trading products typically show consistent single-digit monthly returns, not tripling in weeks.
The numbers show how the scheme worked. Of the $12.3 million raised:
| Use of Funds | Amount | Percentage |
|---|---|---|
| Crypto asset purchases | $380,000 | 3% |
| Personal use (estimated) | >$6.15 million | >50% |
| Ponzi payouts to earlier investors | Remainder | ~47% |
No profits were generated from the small amount of crypto trading Fuller actually conducted. Instead, more than half the funds went to his personal expenses. The rest went to earlier investors to maintain the illusion of a functioning business – a classic Ponzi scheme structure.
The scheme unraveled when Fuller filed for bankruptcy in 2025. During those proceedings, he reportedly admitted to operating a Ponzi scheme. The bankruptcy court denied his discharge because of the fraudulent operations of Privvy Investments, LLC. That admission is central to the SEC’s case.
The SEC is now pursuing permanent injunctive relief against Fuller, along with disgorgement of profits and civil penalties. The case remains in its early complaint phase, meaning no final judgment has been entered.
For traders and investors evaluating similar crypto or AI trading claims, the Fuller case provides a checklist of red flags:
The thesis that this is a fraud is confirmed by the bankruptcy admission. The thesis would weaken only if Fuller could demonstrate actual AI trading results that were withheld, or if the SEC’s complaint is dismissed for lack of evidence – unlikely given the admission.
When vetting any broker or platform, use the best crypto brokers guide to compare regulated options. Unregulated ventures claiming AI-driven returns should be met with extreme skepticism.
Fuller’s case is a textbook example of how fraudsters exploit hype around AI and crypto. The numbers are damning: 3% of funds used for the stated purpose, zero trading profits, and a sworn admission in bankruptcy court. For the 150 investors, the lesson is brutal. For the wider market, the case reinforces that due diligence on credentials and business model remains the only reliable defense.
Prepared with AlphaScala research tooling and grounded in primary market data: live prices, fundamentals, SEC filings, hedge-fund holdings, and insider activity. Each story is checked against AlphaScala publishing rules before release. Educational coverage, not personalized advice.