Chinese police AI algorithm tracks bitcoin money laundering with 90% accuracy
Summarized and contextualized by DistantNews.
At a glance
- Chinese police researchers developed an AI framework to detect illicit cryptocurrency transactions with nearly 90% accuracy.
- The system aims to combat money laundering and other illegal activities facilitated by the pseudonymous and cross-border nature of cryptocurrencies.
- This development follows a report of prosecutors indicting thousands for virtual currency-related money laundering in 2025.
Chinese police researchers have created an artificial intelligence framework capable of identifying illicit cryptocurrency transactions with an accuracy rate nearing 90%. The AI system is designed to tackle money laundering and other criminal activities that exploit the pseudonymous and global nature of digital currencies.
The study, published in the peer-reviewed Chinese Journal of Intelligence, was conducted by researchers from the People's Public Security University of China, an institution affiliated with the Ministry of Public Security. According to Dr. Sun Jingchao, a researcher specializing in criminal investigation and cybersecurity, the framework offers a "precise, generalisable and interpretable solution" for detecting illicit cryptocurrency transactions.
provides a precise, generalisable and interpretable solution for detecting illicit cryptocurrency transactions
Sun also stated that the system "provides an innovative technological pathway for regulatory authorities to combat illicit cryptocurrency transactions and economic crimes." The research comes at a time when authorities are intensifying their focus on financial crime linked to cryptocurrencies. In March, China's Supreme People's Procuratorate reported that prosecutors indicted 3,259 individuals in 2025 for money laundering involving virtual currencies and underground banking operations.
provides an innovative technological pathway for regulatory authorities to combat illicit cryptocurrency transactions and economic crimes
Originally published by South China Morning Post. Summarized and contextualized by our editorial team with added local perspective. Read our editorial standards.