News linked to both this project and an event.
the U.S. Securities and Exchange Commission (SEC) has filed a lawsuit against Texas resident Nathan Fuller, alleging he fraudulently raised approximately $12.3 million from about 150 investors through a fake "AI crypto trading bot" project.The SEC stated that from October 2022 to mid-2024, Fuller offered and sold crypto investment joint venture interests through entities named Privvy Investments LLC and Gateway Digital Investments. He claimed to use an "AI high-frequency arbitrage bot" for crypto asset trading and promised investors "guaranteed returns" of 40% to over 100% within 21 to 45 days.Regulators allege that Fuller also falsely claimed investment funds were protected by FDIC insurance, surety bonds, and professional liability insurance. In reality, the purported trading bot did not operate as advertised. The SEC charges that Fuller misappropriated at least $6.2 million of investor funds for personal expenses and used approximately $5.5 million from new investors for "Ponzi-like payments," while misleading investors through fake account statements and fictitious institutional communications.The SEC has filed a lawsuit in the U.S. District Court for the Southern District of Texas, accusing Fuller of violating securities offering and anti-fraud laws, and is seeking permanent injunctions, disgorgement of ill-gotten gains, and civil penalties.
as AI trading agents enter financial markets, structural problems in retail trading are facing potential transformation. The current business models of exchanges and brokerages rely on customers trading frequently. Regardless of whether the customer profits or loses, the platform profits through commissions, spreads, and order flow. Research shows that 74% to 89% of retail traders ultimately lose money, and the Payment for Order Flow (PFOF) mechanism hidden behind zero-commission trades ensures that the platform's profits are unrelated to customer returns.Independent, programmable AI trading agents can change this structural contradiction: by linking the agent's returns to the customer's portfolio returns, they encourage disciplined trading rather than trading frequency. Agents can choose to reduce positions, avoid impulsive moves, and protect customer assets in highly volatile markets, achieving true alignment of interests.As the US eliminates minimum asset requirements for day trading and the EU prepares to implement a PFOF ban, traditional exchange models are facing regulatory pressure. Meanwhile, AI agents are restructuring trading infrastructure through innovative channels such as on-chain payments, gas-free transactions, and decentralized exchanges, providing retail investors with transparent, fair, and verifiable trading intermediaries. (CoinDesk)
Polymarket, a crypto prediction market platform, has become embroiled in an insider trading controversy due to predictive trading centered on US President Donald Trump's related policies and statements. Data shows that from April 5th to April 8th alone, markets related to the situation in Iran generated approximately 413 million predictions, involving funds exceeding $100 million.Analysts point out that Trump's highly unpredictable decision-making style has significantly boosted activity in the prediction market. Topics such as whether he will take military action against Iran or push for a ceasefire have become high-frequency trading targets. Related trading volumes surged rapidly following his social media posts.Notably, Donald Trump Jr. was revealed to hold shares in Polymarket while also serving as an advisor to another prediction platform, Kalshi, sparking external questions about potential conflicts of interest and insider trading. Industry data indicates that political predictions have become the second-largest category in prediction markets, trailing only sports. Despite the escalating controversy, the overall attitude of US regulators remains relatively lenient, driving the continuous expansion of this sector. (Fortune)
According to Cointelegraph, the blockchain payment network XRP Ledger (XRPL) has partnered with zero-knowledge infrastructure provider Boundless to integrate its zero-knowledge technology into the underlying network, aiming to enable confidential and compliant on-chain transactions for banks and asset management firms. Shiv Shankar, CEO of Boundless, stated that the solution protects sensitive information—including transaction size, frequency, and counterparty details—through selective disclosure and role-based access control, while ensuring regulatory authorities can audit related activities. This integration is expected to drive adoption across multiple institutional use cases on public blockchains, including cross-border corporate payments, treasury management, over-the-counter (OTC) trading, tokenized asset issuance, and decentralized finance (DeFi). Industry observers believe that striking a balance between privacy and compliance is becoming a key factor in driving institutional adoption of public blockchains.