Meta recently announced it was finally taking its first major step toward protecting its users from pig butchering scams on its platform.
Estimated to have cost victims over $4.4 billion in 2023, these elaborate scams utilize emotional manipulation and fake identities, making them difficult to infiltrate and stop.
As Big Tech moves to take a more active approach to combating these scams, some experts are concerned that it will not fully address the growing issue.
Last week, Meta said it was dedicating a team staff to identify fraud scammers and would take down over 2 million accounts this year.
In September, the FBI announced that crypto investment fraud saw $4 billion in losses last year, a significant jump from $2.57 billion in 2022.
Meta shared in a blog post that it would begin automatically flagging potential scam messages when strangers message people over Instagram, Facebook, or WhatsApp.
“On WhatsApp, if you’re added to a group chat by someone you don’t know, you’ll now see a context card giving you more information about the group.”
“It’ll show who added you, how recently the group was created and who created it so you have context on this outreach.”
Meta added that, in addition to working with law enforcement around the globe, it would also share threat information with industry peers.
Pig butchering scams are an elaborate form of online fraud where scammers build trust and emotional connections with victims before manipulating them into making financial investments.
The name comes from the analogy of “fattening up the pig” before slaughter–scammers take time to gain their target’s trust before taking their money.
These scams often start on dating apps, social media, or messaging platforms, where scammers pose as friendly or romantic interests.
After establishing a close rapport, the victim is usually introduced to a lucrative investment opportunity, often involving crypto or other financial schemes.
Pig butchering scammers often provide convincing evidence, such as fake platforms and doctored screenshots designed to make the scheme seem legitimate.
Pig butchering scams are especially difficult to tackle because they exploit human psychology.
Scammers often invest weeks or months building trust with their victims, creating emotional and financial dependencies that make their eventual betrayal all the more devastating.
This prolonged grooming process can make victims reluctant to believe they are being scammed, even when warned.
Roman Bieda, Head of Investigations at Token Recovery, believes pig butchering scams should be changed to “romance scams” or “romance investment scams” due to their dependence on emotional connection.
Bieda told CCN that Meta’s planned removal of 2 million fraudulent accounts is a positive step but is insufficient to combat romance scams.
“Scammers continuously evolve their tactics, requiring not only account removal but also proactive monitoring, user education, and close collaboration with law enforcement.”
This evolution of tactics is mainly through the use of more convincing technologies, such as AI.
“Previously, they relied on hiring real individuals or models to create convincing fake profiles. Now, AI enables them to generate highly realistic fake profiles entirely from scratch, including photos and even videos,” Bieda said.
The utilization of deepfakes to create new profiles and conduct convincing video calls has made it harder for social media platforms to catch scammers.
Blockchain analytic tools are one of the most powerful ways to disrupt fraudulent networks. These tools can analyze transaction patterns and link wallets associated with scams – something not currently possible on existing social media platforms.
Meta’s attempts to combat pig butchering scams could help deter individual cases, but many scammers operate on several different communication lines.
Blockchain can support this drive by implementing mandatory know-your-customer protocols on cryptocurrency exchanges, enhancing public awareness through user education campaigns, and imposing stricter penalties for crypto-related fraud.