So far, we’ve taken the macro view on social credit, and examined the SCS on a national scale, primarily as it relates to businesses and professionals. Now, we’ll zoom in to the city level, and take a look at how the system treats individuals in the social context.
City governments are the key players for individual social credit. A person’s city and province of residence are responsible for collecting and managing most of the information about them. City data collection, blacklisting, and punishment and reward mechanisms happen just like they do at the national level, but on a smaller scale.
Within cities, data collection is decentralized. Each city bureau is responsible for gathering and logging data that relates to its administrative area, then submitting that info to the city’s SCS database.
For example, if you get caught drunk driving, the city police would keep their own record of the traffic violation as usual, and also add that violation to the city credit database. If you’re caught teaching under false credentials at the local school, the municipal bureau of education would submit that information to your city credit record. If you don’t pay your property management fees, the city housing authority will submit that to your credit report.
Good deeds get reported too: if you volunteer for community service, the related department will submit that info. If you donate blood or bone marrow, the local health planning commission will log your donation.
That data then gets passed up the chain through the National Credit Information Sharing Platform to the provincial and national databases.
The source documents we’ve seen show that the data collected on citizens at the local level is fairly standardized from city to city. That’s because most cities in China have the same set of bureaus and agencies. Those agencies already have a standard set of records they collect. These basic data sets get passed up to the national database from every location.
But while the data sets are similar from city to city, what cities have chosen to do with SCS data at the local level varies dramatically from place to place.
Some cities are independently creating citizen scoring systems based on the data. These city-level scoring systems are what often get cited in media reports on the SCS, and are sometimes confused for national scores.
The scoring pilots are completely different from city to city. Some cities have decided on a 0-200 scoring scale, some on a 0-1000 scale, and this discrepancy is evidence that the central government didn’t dictate how citizens should be scored, but left it up to the municipalities to come up with their own programs.
|Examples of city-level citizen social scoring systems|
|Location||Name of scoring system (English)||Name of scoring system (Chinese)||Point scale|
|Suzhou 1||Osmanthus Points||桂花分||0-200. Baseline points are 100, with the potential to add up to 100 more.|
|Suqian 2||Xichu Points||西楚分||Scores start at 1000, and will go up or down depending on behavior. A rating from AAA to D will be assigned based on credit score range.|
|Rongcheng 3||Rongcheng Points||荣诚分||Scores start at 1000, and will go up or down depending on behavior. A rating from AAA to D will be assigned based on credit score range.|
|Weihai 4||Haibei Points||海贝分||Scores start at 1000, and will go up or down depending on behavior. A rating from AAA to D will be assigned based on credit score range.|
|Fuzhou（抚州）5||Yuming Points||玉茗分||Scores from 0-1000:
(1) Above 750 – Excellent credit
(2) Between 750-600: Superior credit
(3) 500-599: Good credit
(4) 400-499: Slightly dishonest
(5) 250-399: Poor credit
(6) Below 250: Extremely bad credit
|Wuhu 6||Lehui Points||乐惠分||Scores from 350-1200
(1) 950-1200: Excellent credit
(2) 850-949: Superior credit
(3) 700-850: Good credit
(4) 350-700: Average credit
|Hangzhou 7||Qianjiang Points||钱江分||(1) Over 750: Excellent credit
(2) 700-750: Superior credit
(3) 600-700: Good credit
(4) 550-600: Average credit
(5) Below 550: Needs improvement
|Xiamen 8||Egret Points||白鹭分||5 levels:
(1) Excellent credit
(2) Superior credit
(3) Good credit
(4) Average credit
(5) Needs improvement
|Zhucheng 9||Ju’de Points||舜德分||Scores start at 1000.|
It’s unclear whether or not every city will eventually have a citizen scoring system, but things look to be moving in that direction. At the end of 2018, for example, Beijing released a policy on improving the city’s market environment, which included a clause on the creation of the city’s “citizen integrity” system: 10
By the end of 2020, the Beijing “individual credit” project covering all permanent residents will be built, and [the use of] credit information will be promoted in the fields of market entry, public services, travel, entrepreneurship and job hunting. …We will improve the credit blacklist system, regularly publicize the records of corporate and personal trustworthiness, and identify patterns of dishonesty and punishment so that “if one is dishonest one area, they will be limited everywhere and will find it difficult to move”, thus ensuring that those who violate the law and fall behind on debts will pay a heavy price.
This is representative of the type of policy language we’re seeing emerging from city governments across China, so we do expect that most cities will eventually develop some kind of scoring system.
It’s also unclear whether or not the central government will wait to see which scoring system is most successful, and then swoop in and order all cities to adopt it. Time will tell. But for the moment, these scoring systems are just pilot initiatives laid over the top of the SCS data, and local scores don’t have any impact on your national credit file. It’s actually the other way around: your national credit file will impact your city credit score, if you live in a city with a scoring system.
Still, because the underlying data sets are the same, examining how these scoring systems work gives us a fascinating look into what kind of behavioral data local governments are gathering on citizens, companies, and governments.
The below example of a city scoring system comes from a draft policy released in August 2018 by the government of Fuzhou (抚州), home of Yuming Points (scale ranges from 0-1000). It outlines which behaviors will result in a point deduction, which behaviors will result in an increase, and which departments are responsible for logging and submitting that data. Though this policy hasn’t yet been ratified, it gives us one of our deepest insights into the inner workings of the SCS at the city level.
Again, remember that the behavioral records that are being gathered on citizens will be passed into the central database, but the scores the city assigns are specific to that place only. Apologies for the crazy length of these tables, but we think they’re worth posting in their entirety.
This table is fairly representative of what we’ve seen from other scoring pilots, but in some places, local governments have expanded the “no-no” list to address localized problems.
Shanghai, for example, recently launched a garbage-sorting scheme, and is penalizing non-compliant companies and individuals through the SCS.11 In Jinan, a citizen’s score can be impacted by not leashing their dog in a public place.12 In Anqing, jaywalking has the potential to affect your credit.13
Looking at these and similar tables, a few problems jump out right away:
The point system isn’t very egalitarian
There are a lot of ways for anyone to lose points, but not as many ways for anyone to gain them. That’s because most of the ways to increase points are things over which people have very little control, or else they are awards which many people aren’t in a position to receive, particularly those in low-income brackets.
Being rewarded for providing important clues in a criminal case requires that you happen to have knowledge of that crime – a matter of circumstance and luck. Technological entrepreneurship awards, innovation awards, and literary awards generally favor the highly-educated.
According to these point scales, the only ways that anyone, at any stratum of society, can raise their points at will and by choice are by:
- Doing volunteer work
- Donating blood or bone marrow
- Giving charitable donations
- Performing “good deeds”
Violations are easier to record than acts of charity
Human bureaucracies weren’t set up to record acts of kindness. While there are already well-established collection mechanisms in place for most offenses, there aren’t established collection mechanisms for “positive” behaviors. The police know you ran a red light because there are traffic cameras designed to catch those violations. But how does the government find out you gave someone back their wallet?
A December 2018 Vice News documentary on the scoring pilot in Rongcheng features a profile of a local “information collector”, a sweet retired woman whose job is to walk the city searching out good and bad deeds, which she records in a notebook and reports to the local credit bureau office. That kind of thing might work in some small towns where everyone knows each other, but it’s definitely not nationally-scalable, nor is it objective.
The concept of “good deeds” is ill-defined
What constitutes a “good deed”, and who decides? The nebulousness of this wording leaves it too open to interpretation.
- Official page for Suzhou Osmanthus Points
- Official page for Suqian’s Xichu Points
- Explainer on the Rongcheng Points scale
- News item on Weihai’s Haibai Points
- Policy draft: Fuzhou Yuming Points
- Official page on Wuhu’s Lehui Points
- News item on Hangzhou’s Qianjiang Points
- News item on Xiamen’s Egret Points
- News item on Zhucheng’s Ju’de Points
- 中共北京市委 北京市人民政府关于印发《北京市进一步优化营商环境行动计划(2018年—2020年)》的通知
- Chinese dog owners are being assigned a social credit score to keep them in check — and it seems to be working