Chinese police researchers build AI model that spots illicit crypto transactions with 89.4% accuracy

Researchers at China’s top police university have built an AI system that can identify illicit Bitcoin transactions with 89.4% overall accuracy, a development that could reshape how law enforcement agencies worldwide approach crypto-related financial crime. The team at the People’s Public Security University of China published their findings in May in the Journal of Intelligence. The South China Morning Post reported on the breakthrough, highlighting how the framework outperforms existing mainstream baseline models for detecting dirty money flowing through blockchain networks. How the AI actually works This new framework combines three technologies: dynamic graph neural networks that map the evolving relationships between transaction nodes, a memory module that stores historical patterns of illicit activity, and large language models that handle the reasoning and classification layer. The researchers tested their system on the Elliptic Bitcoin dataset, a public benchmark that contains 203,769 transaction nodes and 234,355 edges connecting them. The model achieved 89.1% precision and a 64.5% recall rate specifically for illicit transactions. When the model flags something as suspici...