JAKARTA - Meta, a giant social media company from the United States, announced that it has removed about 8,000 scam advertisements using celebrity images on Facebook and Instagram. This move is part of a joint effort with Australian banks to suppress the increasingly rampant fraudulent practices.
This scam usually takes advantage of celebrity images generated by artificial intelligence to deceive consumers into investing in fake investment schemes. Since April, Meta has received 102 reports from the Australian Financial Crimes Exchange, an intelligence agency managed by major banks in Australia.
This fraud problem not only occurs in Australia, but Meta is facing greater pressure in the country, especially with the government's plan to introduce a new anti-fraud law. The bill will set fines of up to 50 million Australian dollars (approximately IDR 520 billion) for social media, financial, and telecommunications companies that fail to take firm action against fraud.
The number of fraud reports in Australia rose by nearly 20% in 2023 with a total loss of USD 2.7 billion. Previously, in 2022, the Australian Competition and Consumer Commission (ACCC) also sued Meta for failing to stop cryptocurrency advertising using celebrity images such as Mel Gibson, Russell Crowe, and Nicole Kidman.
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Meta is also facing another lawsuit from Australian mining billionaire Andrew Forrest, who accused the company of facilitating thousands of fake ads showing its face. Forrest has warned Meta of this scam since 2019, but losses continue.
David Agranovich, Director of Meta Threat Disruption, stated that cooperation with Australian banks is still in its early stages. "High-value signals can help us identify broader frauds," he said.
When asked about Meta's views regarding Australia's draft anti-fraud law, Agranovich said the company was still studying the regulation and would provide further responses at a later date.
Total Luo, Head of Strategy at the Australian Financial Crimes Exchange, stressed the importance of this industry initiative to anticipate fraud before regulation is implemented.
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