'Social Credit Scoring' Being Pushed By The IMF

World financial leaders want to adopt China’s system to determine credit using a person’s internet history

Michael Haynes

In a blog post on its website, the International Monetary Fund (IMF) proposed a system of social credit scoring similar to the kind already in use in Communist China that would determine people’s credit eligibility based on internet history, leading to concerns that such a system could be turned against anyone who opposes the will of financial and globalist leaders.   

The concepts that the IMF proposes are already being quietly promoted and practiced, notably in China, but also in the U.K., where trials are underway involving widespread covert internet surveillance and data recording. 

The blog post in question, entitled “What is really new in Fintech,” appeared on the IMF website in December 2020 and was drawn up by four men: Arnoud Boot, a professor of finance at the University of Amsterdam; Peter Hoffmann and Luc Laeven, both economists with the European Central Bank; and Lev Ratnovski, an economist with the IMF but currently with the European Central Bank. 

It addressed the questions of how new innovations would change the face of finance, as well as the “challenges” that these developments would bring, particularly with regard to the growing challenge to traditional banking, which is posed by the rise of Big Tech.  

In response to this issue, the paper proposed a system of social credit born out of one’s online activities. It pointed to “information,” which the authors described as having “new tools to collect and analyze data on customers, for example for determining creditworthiness.” 

In a section entitled “New types of information,” the authors casually revealed how online activities could, and seemingly already are, being used to determine a social credit score. “The most transformative information innovation is the increase in use of new types of data coming from the digital footprint of customers’ various online activities — mainly for credit-worthiness analysis.” 

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