Fraud factories, where perpetrators themselves become victims who help perpetuate the system, pose a significant challenge to the health of global financial networks, resulting in an estimated $75 billion in financial losses over the past four years. There are losses.
Clare Green, a payments risk expert at the Federal Reserve Bank of Atlanta, highlighted in a recent paper that these fraudulent factories primarily operate in developing markets such as Cambodia, Laos, and Myanmar. blog postadded that tens of thousands of these individuals are confined to their premises and forced to conduct online scams targeting unsuspecting foreigners.
“These frontline actors themselves may become victims of human trafficking, be tricked or kidnapped, or forced to work as cogs in larger criminal organizations,” she said. It pointed out.
Such scams often use fake online identities to initiate fake romantic relationships and persuade victims to transfer large sums of money through fraudulent cryptocurrency schemes. The practice, known as “pig butchering,” requires weeks of gaining the victim's trust before being exploited, much like fattening a pig.
As PYMNTS wrote last March, “[Pig-butchering] scam Mix elements of romance scams In investment scams, scammers create social profiles or personas to manipulate victims into investing in cryptocurrencies or sending money. Rather than waiting for a victim to arrive, scammers will solicit, snoop, and actively reach out to apps and texts to find new targets. ”
An example of this is when federal authorities $9 million The “pig butchering” scam involving virtual currency trust occurred in November last year.
at that time, Nicole M. ArgentieriThe acting assistant attorney general of the Justice Department's Criminal Division said scammers are targeting retail investors by setting up websites that falsely assure victims that their investments are producing profits. “The truth is that these international criminals are simply stealing cryptocurrencies and leaving their victims with nothing,” she added.
The challenge for payment service providers is effective risk management and compliance. The cross-border nature of operations makes tracking and tracing fraudulent transactions extremely difficult. This complexity directly impacts traditional anti-money laundering (AML) and know-your-customer (KYC) protocols, along with cross-border regulatory frameworks.
And as scams evolve and become more sophisticated, scam factory techniques also evolve and become more effective.
In a recent interview with PYMNTS, kate frankishChief Business Development Officer and Anti-Fraud Officer Pay.UKDigital technologies such as artificial intelligence (AI) deepfake images allow fraudsters to imitate individuals with such high accuracy that even tech-savvy individuals have difficulty discerning what is real. He pointed out that it was happening.
“The more sophisticated these types of scams become, the harder it becomes for even the most knowledgeable people to understand that this is not actually true. It's not real,” Frankisch said. , added that the line between truth and deception has become blurred, making victims more vulnerable to threats.
Embracing innovative technology is critical for businesses and financial institutions (FIs) looking to stay ahead of these ever-evolving strategies. And more companies are achieving this by prioritizing investments in advanced fraud detection and management systems, according to PYMNTS Intelligence data.
In the past year, nearly 70% of financial institutions with more than $5 billion in assets deployed AI and machine learning (ML) solutions to fight fraud and financial crime, and that rate will nearly double from 2022. became. Additionally, the study found that 97% of companies with assets were followed by companies with assets of $100 billion or more.
The good news is that financial institutions using these technologies are seeing positive results. Research shows that institutions that adopt AI or ML are more likely to see a decrease in overall fraud rates and less likely to see an increase in fraud.
