A new report from Carlson Law has highlighted the prevalence of investment scams within the crypto industry, causing a record $2.57 billion in losses during 2022, out of a total of $3.82 billion lost that year. These scams continue to raise concerns about the credibility of the digital asset market and underscore the need for vigilance among investors.
Fraudsters have been increasingly using deceptive tactics, such as reaching out to potential victims online with promises of lucrative investment opportunities. Unfortunately, what may seem like a chance for modest gains quickly turns into a nightmare, as victims discover that their funds are inaccessible due to excuses or delays from the exchange.
The report also points out that scammers are becoming more sophisticated, employing artificial intelligence (AI), including voice cloning, to manipulate victims into believing they are dealing with legitimate investment opportunities. This use of AI has made it difficult for law enforcement to keep up with the evolving techniques used by scammers.
California has been particularly hard-hit by investment scams, ranking first in total losses ($870 million) and second in the average amount lost per victim ($176,463). Investment fraud per capita also places California fifth, with 12.6 victims per 100,000 residents falling prey to scams.
The report identifies several common types of investment scams, including those involving AI-generated deep fake videos, fake crypto initial coin offerings (ICOs), and “pump and dump” schemes. It advises potential investors to be cautious, meet representatives in person, and conduct thorough background checks on anyone involved in investment opportunities.
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To avoid falling victim to investment scams, the report recommends being wary of overnight promises of riches, conducting due diligence on investment opportunities, and seeking expert advice before making any financial decisions. Additionally, investors should scrutinize promotions and websites for signs of DIY marketing and spelling and grammar errors that may indicate fraudulent schemes.
