Meta is tackling “pig butchering,” a colorful name for a type of scam being perpetrated by organized crime groups around the world.

Despite its colorful name, pig butchering is one of the most dangerous types of scams, as Meta describes in a blog post.

One of the most egregious and sophisticated fraud scams, ‘pig butchering’ is all about building trusted personal relationships online with someone only to manipulate them to deposit more and more money into an investment scheme, often using cryptocurrency, and ultimately lose that money.

The company says the groups behind the scam “are mostly based in Asia,” but they target victims globally and force individuals to work for them.

The scale and sophistication of this threat is unprecedented, with the US Institute of Peace estimating that up to 300,000 people are forced into scamming others around the world by these criminal groups, with about $64 billion dollars stolen worldwide annually as of the end of 2023.

For over two years, our teams have been focused on investigating and disrupting the activities of the criminal scam centers in Southeast Asia. While our initial focus was on scam centers in Cambodia, we have since worked to keep pace with the expansion of these groups as they began to appear in places like Laos, Myanmar and more recently the United Arab Emirates. At the outset, we actively engaged with expert NGOs and law enforcement partners in the US and Southeast Asia to better understand the modus operandi of these criminal groups, including in places like Sihanoukville in Cambodia, which is reported to be a hotbed for Chinese organized crime-linked scams.

Meta has established teams and formed partnerships to disrupt scam operations.

To counter these scam compounds globally, we rely on our DOI policies as the most effective and appropriate set of measures for disrupting organized crime. Using both our internal subject matter expertise and insights from external stakeholders, we are continuously investigating and assessing criminal organizations involved in this activity for designation. Once designated as DOIs, the entities are banned from our platform and subject to a wide range of enforcement tools.

The company is also working with law enforcement agencies to help tackle the threat.

“The Royal Thai Police has been working with Meta on disrupting criminal scam centers for over two years. We’ve been able to share information so they can investigate and take action against the bad guys and help us hold the criminal syndicates behind these scam centers accountable.”

— Police Major General Teeradej Thumsutee, Commander of the Investigation Division of the Metropolitan Police Bureau, Royal Thai Police

Meta is also working with industry peers, including OpenAI, to share threat information and disrupt the operations of scam groups.

When possible, we’re working to share threat information with our industry peers who are focused on preventing criminal syndicates from targeting people on our respective platforms. As an example, recently, our team disrupted malicious activity that appeared to originate from a newly stood up scam compound in Cambodia attempting to target people in Japanese and Chinese languages. We began investigating this activity based on information shared with us by our peers at OpenAI, who detected and disrupted the actors’ efforts to use their tools to generate and translate the scammers’ content. We also shared threat information about the scam centers we have disrupted to enable further investigations across the internet.

In addition, last week, as part of the Tech Against Scams Coalition, we co-convened a Summit on Countering Online Criminal Scam Syndicates. It included international law enforcement, government officials, NGOs and tech companies that came together to discuss ways to make further progress in tackling this transnational threat. The Coalition includes companies across dating apps, social media apps, financial institutions and crypto platforms, like Coinbase, Ripple, Meta and Match Group, the parent company of Tinder and Hinge.