Chinese national Jianfei Lu sentenced to 15 years in US$92m drug money scheme
Summarized and contextualized by DistantNews.
At a glance
- A Chinese national was sentenced to 15 years in prison for laundering over US$92 million in drug money.
- Jianfei Lu was part of a money laundering network with ties to Mexican drug gangs.
- US officials highlighted the growing threat of Chinese money laundering networks enabling cartels.
A Chinese national involved in a large-scale money laundering operation has been sentenced to 15 years in prison in the United States. Jianfei Lu, 31, was ordered to pay US$25 million for his role in laundering more than US$92 million in illicit funds over a two-year period.
The US Justice Department described Lu as a "prolific" money launderer who collected funds from US-based drug traffickers. He then deposited this money into shell company bank accounts, using both real and fake identities. Lu pleaded guilty as part of a larger indictment against six individuals.
Chinese money laundering networks have become a key enabler to the Mexican cartels. This emerging and enormous threat to the United States has only become more complex.
Assistant Attorney General Tysen Duva stated that Chinese money laundering networks have become a significant enabler for Mexican cartels. He emphasized this emerging and enormous threat to the United States, noting its increasing complexity. Special Agent Jae Chung of the Drug Enforcement Administration added that criminal organizations cannot operate without access to their profits, and those who help conceal drug trafficking proceeds become integral to the enterprise.
Todayโs sentence reinforces an important principle, criminal organisations cannot operate without access to their profits. Those who knowingly assist in concealing and legitimising drug trafficking proceeds become an integral part of the criminal enterprise.
Originally published by South China Morning Post. Summarized and contextualized by our editorial team with added local perspective. Read our editorial standards.