Big data aids Fujian crackdown on gangs

Big data technology has helped authorities in Fujian province solve 150 cases involving mafia-style gangs in the past three years.

They have also solved nearly 1,000 other cases of organized crime since the start of a three-year crackdown in 2018 and seized assets worth 27.7 billion yuan ($4.25 billion).

By using a platform to analyze massive amounts of data, the authorities can gain more precise clues about such crimes, examine key problems in cases and pinpoint industrial management vulnerabilities.

Investigators first label an organized crime case with keywords based on its type, the way the crime was committed, and the behavioral characteristics and makeup of the criminal gang.

They can then conduct multidimensional correlation analysis to discover the main characteristics of organized crimes in a certain area and provide precise guidance for further investigation.

More than 10 departments, including public security, tax, natural resources, and housing and urban-rural development, share their information, enabling investigators to compare inter-department data and dig out more clues of organized crime cases. The results of such analysis are sent back to regulators promptly for early warning and prevention.

A survey conducted by the Fujian Provincial Party Committee's political and legal affairs commission found that people's sense of security exceeded 99 percent last year, with 97.3 percent of people satisfied with law enforcement. The number of criminal cases registered last year fell 16.2 percent year-on-year.

Xiamen, a city in Fujian, began to build a political and legal information-sharing platform at the start of last year. It has gathered more than 50 billion pieces of government affairs data, including police reports, public complaints and proposals, court decisions, and information from market supervision and urban management authorities.

Based on the platform, the Party's anti-organized crime working group in Xiamen built a unified event library for screening out clues related to organized crimes and classified the clues into different types, such as forced trading, illegal mining and loan fraud. Through the analysis, the authorities can effectively discover the main areas and industries affected by organized crime gangs.

The analysis of information from courts and the natural resources and notarial departments led investigators in Xiamen to suspect last year that a local resident, Zhang Rongguo, was involved in loan fraud.

Zhang was involved in 27 cases of private lending litigation and 19 cases of falsified notarization. He also signed five house leases of more than 15 years but changed the property rights of three of them during the lease period. Historical complaints data also showed that Zhang was involved in two complaints about usury and collecting debts through violence.

Police later filed a loan fraud case against Zhang and other suspects. Their investigations are continuing.

The Xiamen platform has provided more than 10,000 possible clues in a range of cases, the working group said.