A special South Korean investigative agency in Seoul has successfully used Artificial Intelligence (AI) to unravel a cryptocurrency Ponzi scheme that defrauded 56,000 people of more than $18.7 million.
The fraudsters targeted people who had little to no idea of how cryptocurrency worked and lured them in with juicy bonuses and free cryptocurrency, the Korea Joongang Daily reports.
Following the arrest of 12 people behind the scam, the Seoul Special Judicial Police Bureau for Public Safety revealed that the vast majority of the fraudulent scheme’s victims were elderly people between the ages of 60 and 70 years. The CEOs of the Ponzi scheme identified only as Lee and Bae were arrested after the agency created an AI to track keywords related to Ponzi schemes and internet fraud.
Elaborately Designed Crypto Ponzi Scheme
Explaining how the AI works, Hong Nam-ki, section chief of the bureau’s second investigation team said:
Through keywords such as Ponzi, loan and recruiting members, we were able to teach the AI patterns of Ponzi schemes, the program can also identify advertisement patterns and identified the enterprise in question, which [was caught] with evidence provided by an unnamed informant.
The Ponzi scheme which started in May 2018 had about 201 offices that it operated from, offering huge incentives to managers and members who brought in other people to join in a classic pyramid scheme format. Lee and Bae made the bulk of their money from selling an unlisted cryptocurrency called M-coin at $.087 per token, promising members that the fake crypto would rise as high as $.52, representing a profit of about 600 percent.
The pyramid scheme also pulled in funds through membership fees which ranged from $287 to as high as $863 for premium membership, which purportedly included discounts on funerals, lodgings and weddings. The scheme’s promoters also promised cash incentives up to $100 for every new member introduced to the network by a downline.
Unlike typically flashy and visible ponzi scheme promoters, Lee and Bae stayed under the radar, keeping a tight lid on any information about the scheme’s cashflow and members. According to the agency, they went as far as hiding all of their accounting information on a server in Japan and moving to a private house when they found out that the police were on to them. To all intents and purposes, the founders intended to keep it running for as long as possible, in a departure from the typical slash-and-run approach of crypto scammers.
The elaborate scheme even had a members-only shopping website, designed to make it more convincing to potential victims, as well as a crypto exchange based in the trendy Gangnam district of Seoul.
Good Sign for Regulation?
This case may well mark a watershed in the ongoing global back-and-forth surrounding cryptocurrency regulation. Several governments have been introduced to cryptocurrency adoption through the unfortunate means of crypto ponzi schemes, which has negatively colored their impression of the technology. India for example, continues to project a broadly hostile regulatory stance on cryptocurrency following the damaging outcomes of several Indian crypto scams like Bitconnect.
For these countries, which are often led by barely competent and often overstretched governments, the added danger of financial collapse presented by the widespread adoption of cryptocurrency scams makes them firewall any attempt o create regulation aimed at helping adoption. The reasoning is that it is much easier and cheaper to simply issue a blanket ban or refuse to officially acknowledge crypto than to embrace it and deal with the cost implication of creating new crime-fighting and law enforcement organizations to deal with a new type of threat.
The successful use of AI to fish out crypto scams, however, could significantly alter this picture. If the technology becomes widely available, it would mean that such governments no longer need to detail overstretched law enforcement resources to deal with an added threat, which greatly reduces the potential cost of crypto adoption.
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