TRM Labs, a leading provider of cryptocurrency risk management solutions, has revealed that bitcoin BTC 1.69% transactions currently account for only 19% of total illicit cryptocurrency activity. This is a significant shift from 2016, when Bitcoin dominated 97% of illicit transactions.
This decline can be attributed to the changing tactics employed by criminals, who are now exploring alternative blockchains and employing tactics such as “chain hopping” to launder money and evade detection.
However, this trend is not just a transition from Bitcoin to other blockchains. It covers new threats arising from the proliferation of fraudulent schemes. According to a recent report, fraud will cost around $9.04 billion in 2022 alone.
Not only do these activities pose risks for retail investors, but they also raise new national security concerns as we rapidly enter the expanding digital battlefield.
The diversification of illicit cryptocurrency activities means that there is a need for increased regulatory measures and improved monitoring systems. Law enforcement and financial institutions must adapt to the changing landscape and combat criminals’ changing tactics.
John Doe, Global Policy Director at TRM Labs, emphasized the importance of collaboration between the public and private sectors to effectively address these challenges.
Cryptocurrency adoption has surged in recent years, driven by the potential of decentralized financial systems and the growing popularity of digital assets. However, this growth has also attracted criminals who seek to exploit the anonymous and borderless nature of cryptocurrencies for illicit purposes.
As criminals continue to adapt their tactics, it is critical to develop robust mechanisms to detect and prevent illicit activity in the cryptocurrency space.
TRM Labs, known for its advanced blockchain analytics and compliance solutions, is at the forefront of this effort. The company’s platform helps businesses and regulators fight financial crime using artificial intelligence and machine learning algorithms to identify suspicious transactions and patterns.
