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DOJ Targets ‘Fake It til You Make It’ Tech Startups

Mar 19, 2024 - pymnts.com
Ismail Ramsey, U.S. attorney for the Northern District of California, is reportedly targeting tech startups, particularly in the artificial intelligence (AI) sector, that defraud investors before their initial public offering (IPO). Ramsey stated that startup founders might be tempted to mislead investors about revenue base, product readiness, and customer reach to increase interest in a potential IPO. He also noted that AI is fertile ground for fraudsters to make false and exaggerated claims.

The U.S. government has been increasing its scrutiny of the AI sector, with the Securities and Exchange Commission recently fining two investment advisers for making misleading statements about their firms’ AI capabilities. The Federal Trade Commission has also seen a rise in AI scam advertisements on social media. However, AI technology is also being used to combat fraud, with 60% of financial institutions using rules-based algorithms, AI, and machine learning to deal with fraud.

Key takeaways:

  • Ismail Ramsey, U.S. attorney for the Northern District of California, is reportedly targeting startups that defraud investors ahead of their initial public offering (IPO), particularly those in the artificial intelligence and tech sectors.
  • Ramsey stated that such 'fake it til you make it' pre-IPO frauds erode the integrity of public and private financial markets, and that startup founders could be tempted to mislead investors about revenue base, product readiness and customer reach.
  • The U.S. government has been increasing its scrutiny of the AI sector, with the Securities and Exchange Commission recently fining two investment advisers for making misleading statements about their firms’ AI capabilities.
  • Despite AI being used to facilitate fraud, it is also being used to combat it. Research by PYMNTS Intelligence shows that rules-based algorithms, AI and machine learning are among the technologies most used to deal with fraud, especially among larger lenders.
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