Chinese authorities’ plan to use “data matching” to locate people who have not joined the social insurance system and urge them to enroll has triggered strong reactions on social media in recent days. Li Zhong, a vice minister of human resources and social security, said at an October 10 press conference that officials would expand coverage through policy adjustments and data matching, aiming to keep basic pension participation above 95 percent during the 15th Five-Year Plan period.
The approach uses big data to identify people who have never enrolled or have stopped paying contributions. A widely circulated image purporting to be a WeChat Security Center notice warned that some group members had not paid social insurance and told group administrators to supervise them, or risk the group’s features being restricted or the group banned.
Several people said high premiums and unstable work make payments unaffordable. Sun Yan, a resident of Jiaozhou in Shandong, said he stopped paying years ago. Local minimum monthly wages are around 2,000 yuan (about US$280), he said, yet social insurance costs more than 1,000 yuan (about US$140). One online user said in a video that he was still working on a construction site awaiting wages and would pay once his employer paid him. Another commenter joked that big data could find the uninsured but seemed less effective against missing persons and telecom fraud.
Chat screenshots also suggested some schools were pressing parents to enroll, with one claiming this could affect children’s exam prospects. The claim was relayed secondhand, and neither image showed a posting date.
The debate comes as retirement rules tighten. Since January 2025, the male retirement age is rising gradually from 60 to 63, and the female ages from 50 and 55 to 55 and 58. From 2030, the minimum contribution period for monthly pensions will rise from 15 to 20 years.
Source: Radio Free Asia, October 15, 2026
https://www.rfa.org/mandarin/shehui/2026/10/15/china-social-security-big-data-economic-downturn-overburdened/