Two universities in China are utilizing big data to screen and subsidize students from low-income families. Furthermore, this dynamic list of subsidized students remains closed to the public to help protect their privacy.

In order to screen the most ideal candidates, the information network technology center of Xidian University needs to establish scientific quantitative indicators, where consumption data of the whole year of 2018 for university undergraduates would be pulled out, and the relevant data would be added according to three consumption periods in the morning, afternoon and evening. In this way, 187,300 pieces of data could be obtained.

By comparing the consumption average levels in a particular school, the consumption data of students who eat more than 60 meals in the canteen every month is one such financial threshold, which is designed to exclude students who often order takeout or take part in internships.

According to the statistics of consumption level of Xidian University in 2018, the standard of food per person is 8 yuan, and the school sets the standard of small consumption for students in difficulty at 5 yuan or less.

Finally, the financial aid will be verified manually to improve the accuracy: the school will check the 166 students who are not in the identification database of poor students through field visits with counselors, to avoid the deviation of financial aid caused by low consumption of those who wish to lose weight, for example. The name of students making the list will not be open to the public to protect their privacy.

In addition to Xidian University, Zhengzhou University has also made full use of big data to help students in need. This school has been a pioneer in providing precision aid for impoverished students in some aspects. For instance, as the funding cycle of the campus card is one month, the dynamic monthly statistics of consumption data in the previous year will be taken into consideration.

Furthermore, Zhengzhou University's big data tracking, which is updated every month, has also been applied to assist the identification of students in need. Last year, the school cross-checked this data with the list of students from families with economic difficulties, which canceled the identification of some students with high consumption behaviors and increased the number of students in need in the database.