Context, Competition, Technology 

and Geopolitics

November 16, 2020

Lead author: Kendra Schaefer

Trivium China

An insider’s look at China’s new market regulation 

regime: the thinking that founded it, the policy that 

underpins it, and the technology that powers it — and 

what it means for the United States. 

China’s Corporate 

Social Credit 

System

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Disclaimer: This research report was prepared at the request of the U.S.-China Economic 

and Security Review Commission to support its deliberations. Posting of the report to the 

Commission’s website is intended to promote greater public understanding of the issues 

addressed by the Commission in its ongoing assessment of U.S.-China economic relations 

and their implications for U.S. security, as mandated by Public Law 106-398 and Public Law 

113-291. However, it does not necessarily imply an endorsement by the Commission or 

any individual Commissioner of the views or conclusions expressed in this commissioned 

research report.
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Table of Contents

Foreword 3

Key findings 6

Introduction 9

Policy Foundations 15

CSCS Data: Corporate Social Credit Files 19

3.1 Public Credit Information (PCI) 19

3.2 Market Credit Information (MCI) 24

3.3 The boundaries of corporate social credit data for foreign companies 25

CSCS Legal Mechanisms: Blacklists, Redlists, Penalties, and Rewards 26

4.1 Blacklists and redlists 26

4.2 Ramifications of list inclusion: Unified Rewards and Punishments 29

4.3 Rectifying violations: objections and credit repair 30

4.4 Market access controls in wider industry 33

Targeted Regulatory Resource Deployment 35

5.1 Corporate social credit “scores” 35

5.2 Risk monitoring platforms 38

Lending and Finance 40

6.1 Lending risk assessment for MSMEs 40

6.2 The corporate bond market and credit ratings 41

Technical Infrastructure 43

7.1 Hardware and software 44

7.2 Next-generation technologies 44

Implementation Status 46

8.1 Seamless data aggregation 46

8.2 Standardized policy and legal foundation 48

8.3 Well-defined penalty and reward ecosystem 49

Compliance and Competition 51

9.1 Equality of application 51

9.2 Increased vulnerability to corruption and bias: the human factor 52

9.3 Increased risks to — and from — key personnel 53

9.4 More risk for companies with larger presence? 54

9.5 Cross-contamination 54

9.6 Data collection and disclosure 55

9.7 Implicit pressure to submit to unfair penalties 55

9.8 Confusion due to decentralized rollout 56

9.9 Sector-specific dangers 56

Geopolitics and Future Risk 57

10.1 Coercing behavior from foreign companies 57

10.2 Enhancing China’s influence over domestic companies abroad 58

10.3 Tightening Party control over local governments 58

10.4 The power of data centralization 59

10.5 Exporting the CSCS: a challenge to Western financial credit models? 60

10.6 Exporting the CSCS: corporate regulation technology 62

10.7 Lack of remedial avenues 63

Recommendations for Congress 65

Appendices 68

Appendix I: Member organizations of the Joint Inter-ministerial Council 68

Appendix II: Key national-level social credit policies and documents 70

Appendix III: Blacklists and redlist MOUs 71

Appendix IV: Key provincial-level social credit regulations by province 75

References & Notes 77
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Foreword

China’s Corporate Social Credit System (CSCS) was conceptualized in the late 1990s 

primarily as a mechanism to crack down on rampant corporate malfeasance and contract fraud 

that proliferated in China’s post-opening market environment. At the time, China’s leadership 

believed this unchecked malfeasance was stunting the growth of the socialist market economy 

by engendering widespread distrust between consumers, businesses, regulators, and lenders. The 

CSCS was initially envisioned as a mechanism to help regulators bring non-compliant companies 

into line, bolstering China’s weak legal system by using “the tools of the market to punish economic 

dishonesty.”1 The CSCS has now been implemented nationwide, and its emergence represents a 

fundamental shift in China’s approach to market regulation.

Officially launched in 2014 with the release of the Planning Outline for the Construction of 

a Social Credit System (2014-2020),

2

 the CSCS has expanded into an ambitious national project of 

staggering scale and scope. It is a complex, sweeping, government-wide initiative that reaches into 

every sector of the economy and touches on such issues as data collection, corporate regulation, 

finance, consumer advocacy, and geopolitics — all of which this report will explore.

Under the CSCS, government records and market-generated corporate compliance data are 

collected into “Corporate Social Credit Files” on every legal entity in China. The scale of this data 

aggregation scheme cannot be overstated. CSCS files contain regulatory and administrative records 

contributed by at least 44 state agencies and their branch offices across every province in China. In 

a U.S. context, this would be roughly equivalent to the IRS, FBI, EPA, USDA, FDA, HHS, HUD, 

Department of Energy, Department of Education, and every courthouse, police station, and state 

agency sharing records across a single platform. 

This nationwide data collection enables the second core component of the CSCS: a nonprosecutorial mechanism to penalize companies with poor compliance records by reducing their 

access to the market and subjecting them to public censure via “blacklists”, while rewarding 

consistently-compliant companies with economic incentives and public praise via “redlists.” 

CSCS files are also used as the basis for a wide variety of public and private-sector initiatives 

which Beijing hopes will collectively form a multi-pronged solution to the perceived lack of 

“trustworthiness” in the market environment.

The term “Corporate Social Credit System” is a somewhat of a misnomer, and the use of 

the word “system” is misleading, as it implies that the CSCS is a single, holistic, techno-regulatory 

apparatus, and that each policy under the social credit banner is a node in an integrated regulatory 

framework. In fact, while the data aggregation is centralized, the policy environment surrounding 

the CSCS is a disjointed mix of national and sector-specific policies, municipal pilot projects, and 

hybrid public-private sector cooperative agreements, loosely centered around the goal of enhancing 

market “trustworthiness.” 

The CSCS has been chronically misunderstood outside of China. The system’s broad 

scope and technical and legal complexity, coupled with a lack of English-language primary source 

documentation on social credit, present significant barriers to understanding the realities of the 
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system’s aims and functions. Without clear insight into the CSCS’s design, technologies, functions, 

policies, goals, and limits, U.S. policymakers and businesses are at a disadvantage in assessing 

how the CSCS may or may not evolve to negatively impact U.S. companies operating in China, 

or be leveraged by Chinese regulators to disadvantage or otherwise impact U.S. businesses. In this 

report, we draw on several thousand Chinese primary sources to describe what the system is and 

what it does. 

We also seek to more clearly define what the system does not do. A general lack of 

understanding regarding the legal limits and technical design of the CSCS has led to widespread 

confusion over the system’s aims — for example, the oft-repeated mischaracterization that CSCS’s 

primary purpose is to issue “social credit scores” to companies. Similarly, the casual use of terms 

like “big data” and “artificial intelligence” by Chinese policymakers in relation to the CSCS,3

coupled with China’s recent forays into the deployment of mass domestic surveillance technologies 

such as facial recognition4 has led to significant speculation on the role that next-generation tech 

is playing in the system’s rollout.5 In the course of our research, we draw on technical manuals, 

data catalogs, and technical procurement documents to define the limits of data and technology as 

they apply to the CSCS. 

Perceptions of the CSCS within China and outside of China are starkly divergent. 

International commentators tend to focus on the long-term potential of the system to be used as a 

weapon of trade war against foreign companies and to strengthen the socioeconomic control of the 

state.6 It has been pointed out that, while the CSCS was ostensibly created to enforce adherence 

to laws and regulations, those laws and regulations exist at the sole discretion of the Party. By 

contrast, domestic reception is largely positive. By and large, observers tend to view the CSCS 

in light of its immediate potential to clean up a business environment perennially dogged by 

malfeasance and fraud. We find that paradoxically, both of these may prove true, particularly in 

China, where enhanced state control is not seen as mutually exclusive with the idea of enhanced 

market trust and efficiency.7

There is also a distinct dissonance between the rhetoric used by top officials to promote 

the CSCS domestically, and the legal realities of the system. China’s leadership touts social credit 

as an inescapable enforcement dragnet under which, as Premier Li Keqiang stated, “there are 

benefits everywhere for the trustworthy, and for the untrustworthy restrictions with every step.”8

Statements such as these call to mind a pervasive instrument of state control unbound by law 

or human rights considerations. In practice, as this report will illustrate, many of the system’s 

features are subject to discrete limits and are far more pedestrian than such sinister statements 

would lead observers to believe. That said, the emergence of the CSCS raises concerns about the 

mass aggregation of data, how the system may be abused, and how it may enable discrimination.

Ultimately, it is Chinese policymakers, and their vision for the CSCS, that will determine the 

direction of the system’s development. As such, this report seeks to highlight the “insider’s view” 

on social credit. We believe that a deeper understanding of the system’s intended consequences 

through the eyes of the CCP will better enable U.S. policymakers to predict its future evolution, 

evaluate the broader implications and potential unintended consequences, and engage with 

Chinese policymakers on this issue. To that end, this report seeks to supplement its analysis with 
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illustrations of how the CSCS is envisioned by Beijing.

It is important to note that while the design, functions, and overall strategic direction of the 

CSCS have been clearly articulated, many aspects of the system remain in flux; and although the 

CSCS is operational, it is evolving rapidly. This makes definitive conclusions about some aspects 

of the system difficult at this time. Additionally, the large number of actors participating in the 

system’s construction has resulted in a highly fragmented policy rollout, with widely divergent 

degrees of implementation across sectors and localities, making its overall implementation status 

difficult to assess. That said, it is clear from the rapid progress made in the formulation of broader 

CSCS policy and the extensive deployment of CSCS data infrastructure over the past six years that 

China intends to proceed rapidly with nationwide implementation which will have widespread and 

significant impact on China’s development. 

The year 2020 is a critical moment in the development of the CSCS. The Planning Outline, 

which articulated the strategic direction of the CSCS, is due to expire in December, and an updated 

plan detailing the next half-decade of social credit strategy is expected by year-end. Considering 

that the impacts of the CSCS on China’s business environment are becoming increasingly 

apparent, now is an opportune time for U.S. business and government stakeholders to deepen their 

understanding of the system’s purpose, functions, and dangers — as well as design an initial U.S. 

policy response and begin to engage directly with Chinese policymakers on the topic.
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Key findings

●	 The CSCS was conceptualized and built — and will be implemented —

primarily to address domestic market concerns and to govern the behavior

of domestic market entities. There is currently no explicit reference in CSCS 

policy that directly disfavors foreign companies operating in China, nor is 

there evidence to suggest that the CSCS is being unfairly applied to foreign 

firms. However, the CSCS opens up certain risks for all companies operating 

in China, and foreign firms may get caught in the crosshairs. Additionally, the 

rapid evolution of both U.S.-China relations and the CSCS itself may see the 

CSCS evolve to disadvantage U.S. firms.

●	 The CSCS is first and foremost a mechanism to strengthen enforcement

of China’s existing laws and regulations. Where those laws are just and 

reasonable, such enforcement may be welcome. However, the CSCS will also 

strengthen enforcement of laws which conflict with U.S. values, resulting in, for 

example, more online censorship or advancement of the One China Principle. 

As such, the system gives China a tool through which to intensify the pressure 

on foreign companies to adhere to Chinese regulatory requirements that may 

conflict with their own corporate values or the values of their customers overseas 

— or potentially even with U.S. government policies or broader U.S. interests. 

●	 The CSCS is already operational, but the degree of implementation is still

highly divergent across localities and sectors. There is no date at which the 

system will be “switched on.” Rather, the CSCS will be incrementally expanded 

as various local governments and state agencies ramp up participation over the 

next decade.

●	 Corporate social credit files have been established on most registered entities

in China, including the China-registered branches and subsidiaries of U.S.

firms. These files are the central axis around which the CSCS revolves, and 

the information they contain drives the many policy and regulatory initiatives 

associated with the CSCS. 

●	 Corporate social credit files are primarily populated with aggregated

government records related to corporate compliance. When the system is 

fully implemented, they will also contain additional information regarding a 

company’s product and service quality as generated by consumers, industry 

associations, and other market entities. There is no indication that CSCS 

files currently support direct input from next-generation data sources such as 

information from remote sensing tools, facial recognition-driven video feeds, 

social media data streams, e-commerce purchase history, or any other such 

information. 

●	 The current technologicalsophistication of the CSCS has been overstated in
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popular discourse both within and outside of China, and the degree to which

the CSCS currently automates data collection and regulatory processes

is low. Although China is piloting technologies designed to remotely detect 

operational violations (such as when a factory exceeds emissions quotas), there 

is no known instance in which automated data collection leads to the automated 

application of sanctions without the intervention of human regulators.

●	 Though the sophistication of CSCS technologies is not currently high, the

scale of China’s national government record centralization effort, of which

social credit is a part, is indeed enormous. This project has considerable 

potential to enhance the bureaucratic efficiency of the Chinese state, increasing 

its predictive capacity and regulatory responsiveness, which could in turn 

enhance Party legitimacy in China and other countries.

●	 Multiple government bodies and state regulators control various blacklists

relevant to their jurisdictional mandate and have administrative authority

to determine which companies are added to such lists. Companies and 

individuals cannot be blacklisted on a completely arbitrary basis, as there are 

pre-determined types of violation that lead to blacklisting, but officials still hold 

discretionary power in terms of which violations are pursued and how severely 

violations are treated. China is currently working to further standardize the 

procedures for the creation of new blacklists, notifications, objections, blacklist 

removal and credit repair. 

●	 One of the mechanisms through which the CSCS aims to improve

“trustworthiness” in the market environment is by creating a national

enforcement dragnet under which companies blacklisted by one regulator

are subject to sanctions from multiple regulators, and companies redlisted

by one regulator are granted incentives by multiple regulators. To extend 

the impact of the CSCS into corners of the market the government cannot 

easily reach, policymakers are also experimenting with initiatives that invite 

non-government entities, such as industry associations and big tech platforms, 

to impose sanctions on blacklisted companies and offer benefits to redlisted 

companies.

●	 The broad range of application in which CSCS files are employed may

increase corporate vulnerability to regulatory corruption and bias through

the inclusion of contaminated data in CSCS files. Through the CSCS, any 

and all records on compliance and regulatory infractions that feed into the 

system will carry additional weight. Chinese regulators may continue to employ 

existing methods of enforcing arbitrary regulatory infractions against foreign 

companies, and the CSCS will by its very nature amplify the consequences of 

those infractions by damaging a company’s CSCS standing. 

●	 Though the CSCS was not designed to serve as a trade war weapon, there
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are avenues through which the system could be politicized. In the event of 

increased trade tensions, regulatory bias could result in regulators applying 

penalties more stringently to U.S. companies. Such penalty records would be 

included in a company’s CSCS file, thus impacting that company’s overall social 

credit profile and potentially resulting in constraints to their market access. 

There is currently no clear bi-lateral platform or framework through which U.S. 

policymakers can raise potential CSCS-related disputes with Beijing. 

●	 Under the CSCS, the social credit files of a company’s legal representative,

key personnel, and actual controllers are linked to the CSCS file of the

company itself. If a U.S. firm is sanctioned under the CSCS, key personnel 

may be personally sanctioned and subject to punishment. Conversely, anecdotal 

reports indicate that the personal social credit standing of key personnel may 

unofficially impact the company. Not only does this leave companies vulnerable 

to unlawful behavior from senior employees, it is also possible that pressure 

could be indirectly applied to a U.S. company via the unfair targeting of its 

personnel.

●	 Companies with a larger presence in China may be more exposed under

the CSCS. Chinese policymakers are currently hashing out the relationship 

between the social credit standing of parent companies and their branch outlets, 

specifically whether or not a parent company would be blacklisted if multiple 

retail locations each receive a single infraction. 

●	 As the platforms which extract insights from social credit data become

more sophisticated, and algorithms are increasingly used to supplement

human regulatory decision-making, “algorithmic accountability” — or

the inherent difficulty in verifying the fairness or accuracy of machinegenerated recommendations — will become a key concern. This issue is 

not unique to China, but the use of such tools by an authoritarian government 

with an immature data privacy regime underscores the need for a push towards 

formulating global data governance principles that protect privacy and civil 

liberties while enabling government data to be used for analysis and decisionmaking.

●	 Within China, CSCS data is increasingly being used to supplement

financial credit data in the assessment of lending and investment risk.

Chinese economists have proposed that a multi-dimensional approach under 

which lenders consider regulatory compliance metrics in addition to financial 

metrics could form the basis of a new Chinese-led financial credit rating model. 

Thus, in the realm of global finance, it is possible that over the long-term, the 

CSCS could present a challenge to U.S.-led sovereign debt and corporate bond 

rating models developed by S&P, Moody’s, and Fitch Ratings. 
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Section 1

Introduction

In the years leading up to and following China’s accession to the WTO in 2001, a great deal 

of international attention was fixed on China’s failure to protect the intellectual property of foreign 

companies. At the same time, China’s central leadership was becoming increasingly concerned 

over the economic losses incurred by domestic businesses as a result of rampant market misconduct 

and weak regulatory enforcement. While international voices expressed concerns over a market 

environment plagued by IP infringements and counterfeiting, internally, key Chinese policymakers 

likewise decried the widespread contract violations, patent infringements, food safety scandals, 

fraud, and other acts of corporate malfeasance that they believed were stunting the growth of the 

socialist market economy. 9

In the late 1990s, then-Premier Zhu Rongji tasked a research team at the Chinese Academy 

of Social Sciences — which included representatives from the People’s Bank of China, the Ministry 

of State Security, the State Intellectual Property Office, and the Ministry of Industry and Information 

Technology — with exploring a solution to the epidemic of unscrupulous market behavior.10 The 

resulting treatise, The National Credit Management System (国家信用管理体系),11 was published 

in 1999. The treatise defines the word “credit” — the Chinese word for which (信用) is perhaps 

better translated as “trustworthiness” — in expansive terms, simultaneously understanding it as a 

measure of one’s basic reputability, honest dealings in business, timely repayment of debts, contract 

fulfillment, and compliance with regulatory obligations.12

Updated in 2002 under the title Principles of the Social Credit System (社会信用体系原

理),13 the treatise frames “credit” (or “trustworthiness”) as a critical component of a functioning, 

efficient business environment, and as a necessary facilitator for economic activity.14 Conversely, 

it describes “untrustworthiness” as a problematic market phenomenon resulting in both tangible 

fiscal losses and intangible damage to the growth of the socialist market economy and society as 

a whole. 

In its earliest incarnation, the Social Credit System (SCS) was entirely concerned with 

“trustworthiness” in the economic sense — malfeasance by enterprises and misconduct by individual 

citizens in their roles as business professionals, entrepreneurs, borrowers, and consumers. But over 

the fifteen years between the publication of the treatise and the official launch of the SCS, the 

scope of the system was broadened dramatically. China’s modern Social Credit System not only 

seeks to enforce regulatory policy in the business environment, but also to coerce desired behaviors 

from citizens in a social context, as well as crack down on unsanctioned corruption, overspending, 

and policy non-compliance among local governments. Because noncorporate applications of the 

modern SCS are outside the scope of this report, we use the term “Corporate Social Credit System” 

(CSCS) to refer only to those parts of the Social Credit System which are relevant to businesses, 

while the term “SCS” is used to reference the system as a whole. 

The emergence of the CSCS was an acknowledgement that China’s judicial system was illequipped to address issues of market misconduct. The treatise stated that:
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[O]nly a small portion [of such infringements] result in criminal prosecution and 

judicial punishment. The majority of contract violations and other untrustworthy 

phenomena cannot be resolved through criminal investigation and judicial trial, and 

even in the event that a judicial trial occurs, there are still considerable difficulties 

in enforcement of the judgement. The contract violations that the [social credit 

system] seeks to address is precisely this type of untrustworthy economic activity, 

those ... which are inconvenient to prosecute under public security laws. 15

The CSCS was intended to shore up these gaps by creating an alternative enforcement 

mechanism: one which would use “the tools of the market to punish economic dishonesty,” rather 

than depending on criminal prosecution to achieve the same effect. Thus, with two key problems in 

their sights — untrustworthy market behavior and a judiciary that struggled to enforce regulatory 

compliance — the architects of the CSCS were faced with the challenge of designing a marketbased mechanism for penalizing non-compliant market actors. 

However, before “untrustworthy” parties could be penalized, they had to be identified. 

Thus, the first task in the implementation of the CSCS was the establishment of a dataset that could 

be used to give regulators a holistic view of corporate and individual regulatory compliance. In 

order to be effective, such data would presumably need to be reliably available to the government, 

relatively uniform for all companies regardless of sector or size, and relevant to determinations of 

compliance. 

Viewed collectively, the Chinese government has access to an immense pool of data that 

could fulfill these requirements. Information such as corporate registration records, tax arrears 

records, social security and utility payment history, administrative penalty records, and operational 

license records — all of which have been determined under CSCS policy to provide relevant 

insights regarding corporate compliance — have long been collected by China’s state agencies. 

However, no single authority has unilateral access to all such records. Thus, CSCS policy mandates 

the elimination of inter-agency and inter-locality data silos, requiring multiple government bodies 

and market regulators to contribute relevant records to a national body of “corporate social credit 

files” (CSCS files). 

CSCS files have already been established on the majority of China’s businesses. These 

files are the axis around which the CSCS revolves, and the CSCS’s various initiatives are based 

on the records they contain. In Section 3, we will examine exactly which government records are 

included in CSCS files and which are not. We will also examine how China intends to supplement 

government records with data generated by consumers, industry associations, credit reporting 

agencies, and others to craft an increasingly detailed picture of corporate compliance.

Once corporate compliance can be assessed via CSCS files, the CSCS seeks to penalize 

“untrustworthy” companies by reducing their access to the market and enforcing economic 

sanctions, while rewarding “trustworthy” companies with increased market access and economic 

incentives. The CSCS does this by empowering regulators to place companies found in violation 

of pre-determined regulations on one of several dozen national “blacklists.” When a company 

is blacklisted by one government regulator, the blacklist record is included in the company’s 
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CSCS file, triggering a series of additional sanctions from multiple participating regulators. Such 

sanctions can include restrictions on issuing stocks and bonds, more frequent environmental or 

safety inspections, restrictions on foreign exchange quotas, bans on participating in government 

procurement bids, denied approvals for science and tech projects, restricted access to loans and 

financing, ineligibility for government funds and subsidies, and many others. Conversely, when 

consistently compliant companies are “redlisted” by one regulator, they become entitled to a wide 

variety of incentives and preferential policies offered by multiple state agencies, including fasttracked administrative approvals and processing of bureaucratic procedures, fast-tracked access 

to credit and financing, preferential consideration in government procurement bidding and policy 

incentives, reduced inspection rates, better import and export quotas, and more. This mechanism, 

called “Unified Rewards and Punishments”, is described in Section 4. 

Though government regulators play the leading role in penalizing blacklisted companies 

and rewarding redlisted companies, Unified Rewards and Punishments is envisioned as a partially 

market-driven mechanism. To this end, the central government is beginning to experiment with 

enlisting private companies and industry associations to participate in the issuance of awards 

and the application of penalties — for example, by encouraging e-commerce platforms to mark 

blacklisted sellers as “untrustworthy” in search results. In this way, CSCS policymakers seek to 

embed the system into corners of the market where the government itself may not easily reach. 

In Section 4.3, we look at some examples of how Unified Rewards and Punishments is being 

increasingly integrated into the private sector. 

It is interesting to note that although China’s Social Credit System and its financial credit 

system are distinct (we discuss social credit’s relationship to finance in Section 6), the design of the 

Social Credit System takes its inspiration from Western financial credit rating systems.16The 2002 

treatise dedicates several chapters to examining U.S. credit law and identifying two key aspects of 

the U.S. approach to financial credit assessment as fundamental to the development of the Chinese 

social credit model, those being:

1. A national system for the collection of records related to debt repayment history, 

which is applied in a variety of financial contexts.17

2. An economic penalty mechanism enabled by these records under which a failure 

to honor one financial obligation (failure to pay credit card bills, for example) 

has concrete ramifications in other areas (such as receiving unfavorable interest 

rates when applying for a mortgage loan).18

The treatise expanded these two basic ideas beyond the financial sphere, and under the 

CSCS, this manifests as:

1. A national system for the collection of records related to regulatory compliance 

(CSCS files), which are then applied in a variety of regulatory and commercial 

contexts. 

2. A system of penalties and market access restrictions for entities that have failed 

to honor such obligations, and incentives for those who consistently comply.
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These two facets of social credit — the collection of data and a system for applying 

punishments and rewards based on that data — are the two pillars on which the CSCS (and indeed 

the broader Social Credit System) is built. However, the data collection element is arguably the 

more central of the two, and to characterize the CSCS as merely a mechanism for meting out 

sanctions and incentives is to miss the bigger picture. Under social credit policy, CSCS files — 

and particularly the blacklist and redlist records they contain — are used as the basis for a wide 

array of initiatives aimed at boosting trustworthiness across the economy. CSCS files are publicly 

available, and they are incorporated into analytics platforms deployed by market regulators to 

determine how much regulatory attention should be paid to given company; they underpin a variety 

of grades issued to companies based on their level of compliance; they are displayed on public- and 

private-sector websites and apps designed to help consumers choose trustworthy service providers, 

reputable employers, and honest business partners; and they are integrated into financial credit 

reports to enable lending institutions to better assess loan and investment risk. Various sections of 

this report will touch on each of these applications of CSCS data. 

There is no definitive timeline for the system’s nationwide finalization, nor have any 

CSCS FILES

Used by regulators to support:

Market access controls

Used by general public to support:

Consumer decision-making

Used by regulators, industry associations, and

credit rating agencies to inform: 

Corporate grading systems

Used by regulators to support:

Smarter resource deployment

Used by lenders to support:

Financial risk assessment

Figure 1: Key uses of CSCS files

Source: Graphic by Trivium China
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clear implementation milestones been set. This is likely because, as we discuss in Section 8, the 

ambitious nature of the project and its many moving parts pose significant scheduling challenges. 

Additionally, the large number of actors participating in the system’s construction has resulted in a 

highly fragmented policy rollout, with widely divergent degrees of implementation across sectors 

and localities, making overall development difficult to track. 

Perhaps more fundamentally, it is impossible to assess the progress made towards a goal 

that has not yet been fully defined. Beijing has never articulated a long-term vision or “end state” 

for the SCS in general, or for the CSCS more specifically. What form the CSCS will ultimately 

take, what balance of automated algorithmic regulation and human decision-making Beijing 

ultimately hopes to achieve, how deeply the CSCS will penetrate the market, and whether or not 

Beijing plans to export aspects of the CSCS or its underlying theories, are all open questions. 

Given that Beijing continues to take a trial-and-error approach to stress-testing certain elements of 

the system domestically — an approach former Communist leader Deng Xiaoping once referred 

to as ‘crossing the river by feeling the stones’ — it is likely that the long-term vision has not been 

articulated because it has not yet solidified at the highest levels. A shifting regulatory environment, 

emerging technologies, and changes in the broader geopolitical landscape are all factors that may 

influence the final shape of the CSCS.

 Beijing’s medium-term vision for the system, however, is easier to extrapolate from its 

existing status and developmental direction. We assess that from China’s perspective, a mature 

CSCS would be characterized by:

Seamless data aggregation: All records earmarked as relevant to corporate compliance, 

generated by government bodies down to the district level, would be centralized in CSCS files 

reliably and in real time — roughly equivalent to the seamlessness with which individual mortgage 

payments, auto loan payments, credit card payments, and other financial records are passed to U.S. 

credit reporting bureaus by various lenders. Additionally, well-worn channels would exist for the 

collection of market-generated information related to a company’s product and service quality 

from consumers, business partners, and industry associations. 

CSCS files will have taken root as the official national source of corporate credibility 

information, with broad awareness among the general public, and broad adoption of their use not 

only in the regulatory arena, but in applications such as due diligence, recruitment and employment, 

consumer advocacy, member selection for key industry association, participant selection for trade 

expos, and financial risk assessments. China’s major tech platforms and startups would draw upon 

CSCS data to develop credibility-related algorithms to extract predictive market insights. 

Strong legal and policy ecosystem: A strong, stable, and refined body of laws and policies 

will underpin the various mechanisms that drive social credit, including the issuance of penalties and 

rewards, the procedures for credit repair, and the rights and obligations of citizens and government 

under the CSCS.

Well-defined penalty and reward ecosystem: A broad body of regulators, financial 

institutions, tech platforms, social organizations, industry associations, and private businesses 
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Section 1 - Introduction

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would form an enforcement dragnet under which a blacklisted company or individual becomes so 

hampered by financial sanctions, operational restrictions, and public condemnation that they are 

driven either to rectify the violation or exit the market. Likewise, that same body of actors would 

cooperate to place redlisted companies and individuals on the path to economic success through 

financial incentives, bureaucratic conveniences, and public praise.

The feasibility of attaining these end results, however, is still in question, and significant 

implementation challenges remain. These include the technical challenges inherent in deploying 

nationwide data aggregation infrastructure, ensuring data reliability and security, ensuring equal 

application of CSCS policies across localities, navigating pushback from state agencies and local 

governments, among others. 

This vision — particularly the potential omnipresence of the Unified Rewards and 

Punishments mechanism — has given rise to deep concern that the CSCS will be leveraged to lock 

foreign companies out of the market. This report finds little evidence to suggest that the CSCS is 

currently being employed to either disadvantage foreign firms or to advantage Chinese companies. 

Nor do we find that there is currently any intention to use the system in such a manner. However, the 

CSCS is being developed and implemented in a context of both deteriorating U.S.-China relations, 

and stronger top-down economic control under Xi Jinping, and it must therefore be viewed within 

this context. The design of the CSCS does open up certain avenues through which it could evolve 

to disadvantage foreign firms in the event of worsening international relations. Additionally, the 

CSCS exposes all companies — both Chinese and foreign — to certain potential risks, including 

greater vulnerability to regulator bias and data contamination. Ultimately, whether or not the CSCS 

becomes a trade war weapon will depend largely on the fairness with which it is applied, and the 

degree to which it is developed. We discuss these findings in Section 9. 

So far, the CSCS has had little tangible impact in the realm of geopolitics, but depending 

on how the system evolves, the next several decades may see it begin to impact the international 

arena. In Section 10, we explore how the CSCS could manifest as a tool of corporate coercion, 

how China’s drive towards data centralization and algorithmic regulation under the CSCS may 

enhance Beijing’s global power, how the system gives the central government a tool through which 

to solidify its grip over local governments, and whether or not the CSCS might present a challenge 

Western financial credit rating models. 

Ultimately, the role the CSCS plays on the global stage will depend on the shape it takes 

domestically. Thus, before we speculate on the CSCS of tomorrow, we look first at the policies 

shaping the system today.
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Section 2

Policy Foundations

In June 2014, China’s State Council published the landmark social credit policy, Planning 

Outline for the Construction of a Social Credit System (2014-2020)19 (hereafter Planning Outline), 

marking the official launch of China’s SCS initiative. 

Though social credit received little international attention prior to the Outline’s release, the 

system had remained under more or less continual development since it was initially proposed. Social 

credit was first formally raised for legislative consideration at the 2000 Two Sessions conference, 

the annual meeting of China’s senior lawmakers.20 The proposal soon received the support of the 

State Council, China’s top administrative authority. Over the following years, social credit working 

groups and research committees were formed to move the system forward, and early urban pilots 

of the SCS were launched in Shanghai, and later, Wenzhou, to test its viability. From 2007 to 2008, 

the State Council released two policies formalizing its intention to proceed with the nationwide 

construction of the Social Credit System.21 It also established the Joint Inter-ministerial Council 

on the Construction of the Social Credit System (社会信用体系建设部际联席会议) – a crossagency platform for social credit research, planning, promotion, and development,22 setting the 

stage for the first concerted push towards national implementation (see all member organizations 

in Appendix I).

The release of the Planning Outline in 2014 represented the culmination of 15 years 

of research, planning, groundwork-laying, pilot programs, and false starts. It established the 

motivations, theory, scope, and stakeholders for the SCS, outlined vague targets for the first six 

years of SCS implementation, and called on state agencies, local governments, and the private 

sector to participate in its construction in various capacities. A follow-up policy, Opinions on 

Promoting the Institutionalization of Integrity Construction,

23 was released the following month. 

This second document sketched out the Party’s vision for the practicalities, technical underpinnings, 

and regulatory mechanisms of social credit. 

In many critical respects, the Planning Outline adheres closely to the original vision of 

the SCS as outlined in the 1999 treatise. It identifies one of its key aims as the prevention of 

“production safety accidents, food and drug security incidents... commercial deception, production 

and sales of counterfeit products, tax evasion, fraudulent financial claims, academic impropriety 

and other such phenomena [which] cannot be stopped in spite of repeated bans.”24

However, the Planning Outline also extends social credit well beyond the original conception 

of the SCS as a “corporate social credit system,” recontextualizing it as a banner under which to 

also effect sweeping trust- and efficiency-based reforms in government and society at large, such 

as fostering a culture of law-abiding sincerity and civic responsibility (the “citizen social credit 

system”), increasing judicial credibility, improving the efficiency of regulatory and administrative 

services, and ensuring local governments honor commitments to the people, the Party and the State 

(the “government social credit system”). 
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To be clear, the Planning Outline does not segment the Social Credit System into these 

discrete buckets, and there are areas of overlap between the corporate-, citizen-, and governmenttargeted aspects of the SCS. For example, just as social credit files are being compiled on every 

company in China, so are social credit files compiled on every Chinese citizen. These files can be 

interconnected, as under the CSCS, the personal social credit file of a company’s legal representative 

and actual controllers are tied to the CSCS file of the entity itself. As we discuss in Section 9.4, if 

a company is blacklisted for malfeasance, key personnel may themselves be blacklisted, effecting 

their personal social credit. In another example of conceptual overlap, under the “government 

SCS”, entire local governments are blacklisted and sanctioned for running up unpaid debts to local 

SMEs.25

Perhaps paradoxically for such a wide-reaching, top-down system, the Outline also 

contextualizes social credit as a tool to reduce “administrative governmental interference in the 

economy,” the thinking being that a market environment and judiciary made more efficient through a 

greater degree of auto-pilot, self-regulation would require less government and regulatory oversight, 

freeing up regulators to focus their attention on a smaller handful of bad actors, while allowing 

“trustworthy” companies with proven records of compliance to operate with less disruption.

The Planning Outline did not formalize legal definitions for the terms “social credit,” 

“trustworthiness,” or “untrustworthy behavior,” and the words were subsequently used ambiguously 

in both policy and public discourse. Although it is tempting to draw Orwellian associations with 

the vague use of moralistic terminology such as “trustworthiness” by authoritarian governments, 

there is currently scant evidence to suggest that the term represents a degree of loyalty to socialist 

ideology. This was underscored in a July 2020 national social credit policy draft, which states: 

[A] determination of untrustworthy conduct must be based on a legally 

effective document. The basis for determining untrustworthy conduct includes: 

effective judicial judgment and arbitration documents, administrative penalties, 

administrative rulings, and other administrative decisions, as well as other 

documents that can be used as the basis for determining untrustworthy conduct 

according to laws, regulations, or decisions and orders of the State Council. 26

Additionally, a review of the broader collective body of social credit policies supports 

the assertion that, under the modern CSCS, “social credit” — and by extension “trustworthiness” 

— primarily refer to compliance with obligations.

27 This definition is explicitly spelled out in 

Shanghai’s provincial social credit ordinance,28 which defines social credit “to mean ‘the status of 

compliance’ ... with legally prescribed obligations or performance of contractual obligations in 

social and economic activities.”29 

None of this is to suggest that the CSCS is necessarily benign or apolitical, particularly 

from the perspective of those foreign governments and companies that object on ethical grounds 

to some of the laws and obligations that the CSCS was designed to enforce, such as the One 

China Principle, the Cybersecurity Law, and online censorship regulations. Moreover, it has been 

argued that while democratic governments conceptualize the law as existing “independently of 

politics, the Party understands law as a reflection of [its own will],”30 and new regulations may 
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be established with little warning or oversight, and with few — if any — checks and balances. 

Viewed from this lens, the enforcement of the law is, in an abstract sense, the enforcement of Party 

ideology. An exploration of such concerns is far beyond the boundaries of this report, but in the 

most immediate and practical sense, it is clear that “trustworthiness” under the CSCS is currently 

understood in legal rather than political terms. 

The Planning Outline identifies the National Development and Reform Commission 

(NDRC), China’s administrative planning body, and the People’s Bank of China (PBOC), China’s 

central bank, as the agencies tapped to spearhead the implementation of the SCS.31 Specifically, 

the NDRC’s Department of Fiscal Finance and Credit Construction (财政金融和信用建设司) 

is responsible for SCS project planning and oversight, and its sub-body, the National Public 

Credit Information Center (国家公共信用信息中心), is responsible for administering the social 

credit dataset and data transfer infrastructure.32 In its capacity as a macroeconomic regulator, the 

NDRC’s work and jurisdiction touches on those of most other state agencies, and it is therefore 

well-placed to act as a both a central administrator of the SCS data and a coordinator of rewards 

and punishments under the CSCS. The PBOC’s involvement is primarily focused on the areas in 

which social credit overlaps with the financial sector (discussed in Section 6). Taken together, the 

jurisdictional coverage of these bodies extends across all sectors of the economy. China’s primary 

market regulator, the State Administration for Market Regulation (SAMR), also plays a critical 

role in the CSCS, as in the course of its duties, it generates a significant proportion of records on 

corporate operations that are included in CSCS files.33

Though the NDRC and the PBOC are at the helm of the CSCS, implementation is truly a 

government-wide effort. As of April 2020, the Joint Inter-ministerial Council on the Construction 

of the Social Credit System had grown from its initial 15 member organizations to 46 member 

organizations,34 and as of June 2019, a reported total of 44 government agencies across 32 localities 

contribute records to the social credit dataset.35 

Major Chinese policy initiatives are typically rolled out in a cyclical, trickle-down fashion: 

general strategic direction is set at the highest levels of government, and the practicalities of 

implementation are refined at the provincial, city, and district levels. Lessons learned at the local 

level are then passed back up the chain to the national government, which uses these insights to 

course-correct and further hone the next strategic plan. 

Social credit has been no exception. The release of the Planning Outline touched off a 

similar waterfall effect, as China’s government agencies, industry regulators, and local governments 

worked to apply social credit to their areas of jurisdiction. Social credit-related policies now number 

in the thousands. They include strategic plans for the future of SCS development, national-level 

policies for integrating social credit into specific sectors, local-level ordinances for the collection of 

social credit data, local-level pilots exploring potential applications of social credit, and technical 

standards that govern social credit databases and data sharing. 

National-level foundational policies: Released by the State Council and the NDRC, 

national planning and foundational policy documents define the major strategic direction of social 

credit implementation and define its core functions (see major national social credit policies in 
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Appendix II). They also may reaffirm the Party’s commitment to social credit, outline new features 

of the CSCS or course-corrections in CSCS development, and urge state agencies and local 

governments to improve or accelerate certain aspects of the CSCS in their jurisdictions. Building 

on the Planning Outline, in 2019 the State Council released Guiding Opinions on Accelerating the 

Construction of a Social Credit System and Building a New Credit-based Supervisory Mechanism 

(hereafter cited as 2019Guiding Opinions),

36 which called for the expanded implementation of social 

credit specifically as it regards market regulation. This document indicated that policymakers saw 

deficiencies in the state of CSCS data collection, data privacy protection, public credit awareness, 

and availability of bureaucratic channels for credit repair. In July 2020, the NDRC and the PBOC 

jointly released the draft policy Guiding Opinions on Further Regulating the Scope of Inclusion 

of Public Credit Information, Punishment for Untrustworthiness, and Credit Restoration to Build 

a Long-term Mechanism for Credit Construction (hereinafter cited as 2020 Guiding Opinions on 

Further Regulation), which seeks to tighten the standardization and legal basis for blacklisting, 

data collection, and CSCS penalties.37

National-level sector-specific policies: Taking broad direction from the State Council and 

the NDRC, China’s state agencies are responsible for drafting and implementing CSCS policies and 

initiatives within their areas of jurisdiction.38 Several hundred such policy documents exist at the 

national level, including regulations defining the CSCS penalties for companies found in violation 

of a specific agency’s statutes (see Section 4.2), sector-specific social credit data collection projects 

(see Section 7), and grading systems to measure corporate compliance within certain sectors 

(see Section 5.1). This includes such documents as the Ministry of Human Resources and Social 

Security’s policy covering how the SCS will be leveraged to penalize companies in violation of 

social insurance laws,39 the Ministry of Agriculture’s policy on the establishment of social credit 

files for agricultural producers,40 and the Ministry of Ecology and Environment’s policies covering 

social credit’s relationship to environmental impact assessments for construction projects.41 In 

many cases, policymakers have updated existing regulations to include provisions stating that 

violations of any rules outlined within that document will be recorded in social credit files. 

Local-level policies: Each provincial, city, and district government is tasked with 

formulating social credit regulations, implementing data collection infrastructure, and devising 

social credit initiatives relevant to its locality.42 Social credit policies at the local level number 

in the thousands, and include ordinances governing local social credit development (see Section 

8.2), incentive schemes for local companies that maintain good social credit, as well as existing 

corporate regulations that have been updated to tie them into the CSCS framework. 

Technical standards: The basic technical standards covering the storage, structure, and 

transfer of social credit data are defined at the national level. These standards are still incomplete 

and are currently being finalized through cooperation between the NDRC, PBOC, and China’s 

national standards bodies. We cover these standards in greater detail in Section 3. 

Through these policies and technical standards, social credit is being layered into regulatory 

schemes across every sector and locality in China, but though CSCS policies take many forms, the 

vast majority share a common thread: they deal with the collection, sharing, application, processing, 

analysis, and leveraging of corporate social credit files.
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Section 3

CSCS Data: Corporate Social Credit Files

The 2014 Opinions on Promoting the Institutionalization of Integrity Construction called 

for the establishment of a cross-sector “social credit file [system] with full national coverage” 

under which social credit files would be established for every company, organization, and citizen 

in China.1 It further indicated that CSCS files should contain aggregated corporate compliance 

records from multiple government departments across various localities, and that files should be 

made publicly available so that the social credit status of enterprises is “open, transparent, and 

verifiable.”43 Social credit files are tied to each organization’s Unified Social Credit Identifier (

统一社会信用代码), which replaced business registration numbers as China’s key domesticallyregistered business entity identifier in 2015.44 The CSCS file system has now become a reality, and 

there is a reasonably large body of documentation detailing what information CSCS files contain. 

Shanghai’s regional social credit regulations define “social credit information” as “objective 

data and materials that can be used to identify, analyze, and judge the compliance and performance 

status of information subjects.”45 Broadly, CSCS policy segments social credit information into 

two categories:46

1.	 Public Credit Information (PCI), which is defined as data or information 

generated or collected “by government bodies or legally-authorized 

administrative bodies in the performance of their duties,” and

2.	 Market Credit Information (MCI), or “information generated by businesses, 

organizations, or credit services and credit investigation bodies ....”47

Put more simply, PCI is data about a company generated as a direct result of the company’s 

interactions with regulators and government entities, and MCI is data about a company more 

indirectly generated by the market through the company’s broader interactions with industry, 

lenders, and consumers.

3.1 Public Credit Information (PCI)

Public Credit Information (公共信用信息) forms the core of corporate social credit files 

and is the key set of records on which the CSCS is based. PCI consists of government records 

generated by state agencies and local governments during the course of regulatory operations, and 

includes “fines, warnings, citations, punishments, court orders, and also professional qualifications, 

business licenses, official approvals, [and] commendations” (see complete list of PCI categories in 

Table 1).48

In 2016, the NDRC released a national-level catalog of PCI,49 generally identifying which 

records each member agency of the Joint Inter-ministerial Council should be responsible for 

contributing to the CSCS. Though the catalog was quite extensive — earmarking 400 records for 

1 For the purposes of this report, the term “social credit file” refers to a dossier of records relating to one individual or company, “social credit record” refers to a single entry contained within that file, and “social credit data” or 

“social credit information” is a general term referring to any part of a social credit file or record.
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inclusion — it was not a finalized list. Just as the Planning Outline set the national policy direction 

for social credit but left the specifics of implementation to state agencies and local governments, so 

did the national PCI catalog set a national data-collection guidepost but leave state agencies and local 

governments to further refine exactly which records would be submitted at the provincial,2 city,3

and district4 levels. In the following years, however, it became clear that a nationally-standardized 

PCI index was needed: in July 2020, the NDRC and PBOC jointly released a draft policy calling on 

the Joint Inter-ministerial Council to finalize the contents of a national PCI catalog by “soliciting 

opinions from various regions, departments and relevant market entities, industry associations, 

chambers of commerce, legal service agencies, experts, scholars, and the public.”50 This catalog 

has not yet been released, but is not expected to vary greatly from the 2016 version.

In the 2016 PCI catalog, each item of PCI is marked as positive, negative, or neutral 

information, and is assigned one of three designations which determines the scope of access to 

that data: “open to the public,” “shared between all government agencies,” or “restricted sharing 

(between select government agencies).” Approximately 75 percent of the records collected on 

companies is designated as “open to the public.” The remaining 25 percent includes potentially 

sensitive information such as details of criminal cases and prosecutions, and approval records 

related to national research and development projects, energy and pipeline projects, foreign 

investment by SOEs, and foreign-invested projects within China, among many others.51

Technical documentation released in 2019, which details the types of data supported for 

sharing over CSCS data-transfer networks, groups PCI into 19 specific categories. These 19 

categories form the core anatomy of CSCS files, as summarized in Table 1.52

Table 1: Nineteen categories of Public Credit Information

Unified Social Credit Identifier

Record type Existed 

prior to 

the SCS?

When record is generated Government body 

which contributes 

this type of record

Expandability

Basic company 

registration data

Yes During company registration State Administration 

for Market Regulation 

(SAMR) 

Low

2 Example: Hubei Provincial Development and Reform Commission, Hubei Province Public Credit Information 

Catalogue (2017 version) (湖北省公共信用信息目录(2017版)(属地篇)), November 22, 2017. Translation. http://

www.hbcredit.gov.cn/gywm/xyml/201802/t20180201_27394.shtml.

3 Example: Liaoyuan City Office of the Joint Conference on the Construction of the Social Credit System, Liaoyuan City Public Credit Information Catalogue (2020 version), (辽源市公共信用信息目录(2020年版)), May 22, 

2020. Translation. http://www.liaoyuan.gov.cn/ztzl/xyly1/zcfg/swzcfg/202006/t20200609_444649.html.

4 Example: [Weihai] Economic Zone Office of the Joint Conference on the Construction of the Social Credit System, Weihai Economic and Technological Development Zone Public Credit Information Data Collection List (2019 

version), (威海经济技术开发区公共信用信息数据归集清单(2019年)), September 30, 2019. Translation. http://

www.eweihai.gov.cn/art/2019/9/30/art_63558_2244148.html.
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Record type Existed 

prior to 

the SCS?

When record is generated Government body 

which contributes 

this type of record

Expandability

Registration data 

alterations

Yes On change of company ownership, 

registered address, etc.

SAMR Low

Equity information Yes During company registration SAMR Low

Branches and 

subsidiaries

Yes During branch and subsidiary 

registration

SAMR Low

Senior management Yes During company registration or on 

change of management / ownership

SAMR Low

Annual report Yes On submission of annual report, 

self-submitted by companies 

SAMR Low

Legacy registration 

numbers 

Yes Registration numbers issued before 

implementation of Unified Social 

Credit Identifiers

N/A Low

Tax payment records Yes On payment State Taxation 

Administration (STA)

Low

Tax arrears Yes On legal judgement of default STA Low

Social insurance 

payment history

Yes On payment Ministry of Human 

Resources and Social 

Security, STA

Low

Provident Fund 

payment record

Yes On payment Ministry of Housing 

and Urban-Rural 

Development

Low

Public utility payment 

record

Yes On payment Utility companies Low

Public utility arrears Yes On legal judgement of default Utility companies Low

Permits, licenses and 

project approvals

Yes On issuance Any issuing body High

Inspection records 

and inspection 

results

Yes After random or targeted 

inspections

Typically SAMR, 

but includes other 

inspecting regulators

High

Administrative 

penalty records

Yes On issuance Any regulator 

empowered to issue 

penalties

High
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Record type Existed 

prior to 

the SCS?

When record is generated Government body 

which contributes 

this type of record

Expandability

Blacklist records 

(Details in Section 

4.1)

No When the criteria for blacklist 

inclusion has been met and 

enterprise has been added to a 

blacklist, or criteria for removal has 

been met and enterprise has been 

removed 

Any government 

body empowered 

to administer one or 

more blacklists

High

Redlist records

(Details in Section 

4.1)

No When the criteria for redlist 

inclusion has been met and 

enterprise has been added to a 

redlist, or criteria for removal has 

been met and enterprise has been 

removed 

Any government 

body empowered 

to administer one or 

more redlists

High

Awards and 

recognitions

Yes Upon receiving any one of various 

awards, from R&D innovation 

awards to outstanding charitable 

contribution awards and product 

quality awards 

Any government 

body empowered to 

issue official awards 

High

Source: Various.53

These basic categories of PCI have remained consistent for at least the last five years, and 

there is currently no evidence of plans to add additional categories to this list. Any expansion of 

the PCI dataset, then, would likely come from an expansion of the number of records contained 

within each category. The number of records could be expanded through an increasing number 

of government agencies participating in data sharing under the CSCS, or through an increasing 

number of contributed records from currently participating agencies. However, we assess that only 

six of these categories are likely to see any significant expansion, as two-thirds of them represent 

a discrete set of documents — such as “tax arrears,” “senior management,” and “branches and 

subsidiaries” — that are, by nature, limited in scope. Categories with a high likelihood of expansion 

include those that have a broad or ill-defined scope, such as “project approvals” and “penalty 

records,” and “awards and recognitions.”

Regardless, it is clear from an examination of the documents discussed above that traditional 

government records make up the main body of CSCS files; the PCI dataset and databases were not 

designed to directly collect, contain, or share data from next-generation sources such as information 

from remote sensing tools, facial recognition-driven video feeds, social media data streams, 

e-commerce purchase history, or any other such information, and do not appear to currently support 

the input or storage of such data. 

The records marked for inclusion in the PCI dataset are shared between government agencies 

and aggregated via the National Credit Information Sharing Platform (全国信用信息共享平

台), a back-end channel for intra-governmental PCI exchange. In late 2015, the NDRC launched 

its first iteration of the National Credit Information Sharing Platform (NCISP),54 built on top of 

China’s existing government services extranet (政务外网), which handles national information 
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sharing of all government records, not only those related to the CSCS.55 In November 2017, various 

draft documents of the NCISP data management framework were released by the NDRC,56 and in 

March 2019, the task of refining that framework was assigned to the social credit standards drafting 

committee SAC/TC470 (全国社会信用标准化技术委员会),57 which is comprised of the NDRC’s 

National Public Credit Information Center, the China Standardization Research Institute, and a 

number of other research institutions and private technology companies.58 Though the framework 

has not yet been finalized and several key standards are still subject to approval,5 the structure of 

social credit’s PCI data transfer mechanisms is clear. 

According to the framework, participating government bodies generate and collect records 

which are transferred to each company’s national CSCS file via the NCISP, where non-protected 

records are then accessible by other government bodies and the general public nationwide. In 

most cases, it is the local branches of government bodies — such as product quality inspectors at 

the municipal branch of SAMR, or the provincial-level tax collection authorities — that conduct 

the bulk of PCI collection on companies registered or operating within their jurisdictions. This is 

because it is the local branches of each agency that undertake most day-to-day tasks of governance 

and administration.59 Records can then be passed up the chain to the national-level ministry or 

agency as needed. This system is roughly equivalent to the IRS, FBI, EPA, USDA, FDA, HHS, 

HUD, Department of Energy, Department of Education, and every courthouse, police station, and 

major utility company in the U.S. sharing regulatory records across a single platform.

Publication and transparency: The majority of PCI records are earmarked for public 

sharing. This is one of several indications that Beijing’s intention in compiling a national repository 

of corporate PCI is not to reserve the data for government use. Rather, the NDRC acts as a data 

administrator — collating, standardizing, and publishing CSCS records — while encouraging the 

use of such data in the broadest possible range of applications in both the public and private sectors 

(see Section 4.4).60

To extend the reach of CSCS data to the general public, two centralized web platforms 

offering open social credit record searches have been established: Credit China (信用中国), 

operated by the NDRC, and the National Enterprise Credit Information Publicity System (全国

企业信用信息公示系统), operated by SAMR. The CSCS records displayed on Credit China are 

collected from multiple regulatory agencies, and provide an overview of a company’s credit status, 

key penalties received, and operational licenses. In addition, Credit China also serves as the official 

government website for social credit news, policy releases, and officially sanctioned op-eds by 

officials and academics at institutions involved in social credit research. The National Enterprise 

Credit Information Publicity System is a CSCS record search portal only, and contains a number 

of additional records collected by SAMR, including inspection reports. Of the two, Credit China is 

by far more complete and accurate: though multiple CSCS policies indicate that certain PCI from 

any agency will be listed on both Credit China and the National Enterprise Credit Information 

Publicity system, as of June 2020, the National Enterprise Credit Information Publicity System 

5 Example: National Development and Reform Commission of the People’s Republic of China, General Framework for Standard System of Public Credit Information (国家发展改革委办公厅关于印发实施《公共信用信息标

准体系框架》等六项工程标准的通知), November 15, 2017. Translation. http://webcache.googleusercontent.com/

search?q=cache:https://www.ndrc.gov.cn/xxgk/zcfb/tz/201803/t20180302_962672.html.
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only contains records collected by SAMR, and does not contain data from other agencies. This 

may simply indicate that SAMR is running behind on integrating cross-agency data into its portal, 

or it may indicate an internal conflict over CSCS data sharing. While these platforms are both 

currently online and searchable by the public, they are also still under development. CSCS data 

sharing infrastructure is not yet fully implemented nationwide, and thus the platforms cannot yet 

offer complete and accurate record sets (see Section 8 for implementation status). 

3.2 Market Credit Information (MCI)

Market Credit Information (MCI) refers to information on companies generated by 

consumers, industry associations, enterprise credit rating agencies, and other market players, and 

may include consumer complaints regarding product or service quality, operational soundness, and 

other data points.61

Unlike PCI, a specific and well-defined dataset, the concept of MCI is vague and poorly 

defined. Some sources of MCI have been identified in policy, but others have only been alluded 

to in official documents or public statements by regulators. On the more specific end of the 

spectrum, the Planning Outline and the 2019 Guiding Opinions make reference to the collection 

of product and service quality information gathered via national consumer complaint hotlines such 

as “12315,”6 but the policies do not specify how this information will be employed in relation to 

the CSCS. More ambiguously, the NDRC has indicated that MCI such as “data publicized by ... 

industry associations” and “major incidents of [corporate] dishonesty as exposed online” has been 

taken into account (alongside PCI) in the issuance of certain CSCS grades (see Section 5.1 on 

CSCS grades and ratings), but the process through which this occurs is opaque.62

A 2017 NDRC social credit directive urged CSCS policymakers to “encourage industry 

associations, chambers of commerce, big data companies, financial institutions, news media, [and] 

social organizations ... to provide information on the trustworthy and untrustworthy behaviors of 

relevant subjects so as to research whether or not [this information] may have relevance [to social 

credit].”63 In 2018, the National Public Credit Information Center issued a request for proposals 

to undertake research into “the extraction of effective information and key indicators reflecting 

the credit status of credit subjects from large datasets, and the excavation and analysis of all types 

of credit information (including Public Credit Information, [Market] Credit Information, internet 

big data, etc.),” indicating that the NDRC is still exploring which types of MCI can be reliably 

collected and how such data can be used effectively.64

Beyond exploring the possibilities for MCI collection and evaluation, the central government 

is also encouraging companies to self-submit MCI that may bolster social credit assessments. 

The 2019 Guiding Opinions “encourage market entities to voluntarily register credit information 

6 China has established a series of national dial-in hotlines which members of the general public may call to file 

complaints regarding specific businesses, of which 12315 is one. Callers provide the company’s Unified Social Credit Identifier when making their complaint. See: State Administration of Market Regulation of the People’s Republic 

of China, Opinions of the General Administration of Market Supervision on the Integration and Construction of the 

12315 Administrative Law Enforcement System to Better Serve Market Supervision and Law Enforcement (市场监

管总局关于整合建设12315行政执法体系更好服务市场监管执法的意见), February 25, 2019. http://webcache.

googleusercontent.com/search?q=cache:http://www.gov.cn/gongbao/content/2019/content_5407676.htm.
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such as qualification certificates, market operations, contract performance... and make a credit 

commitment as to the authenticity of the information and authorize [various government social 

credit] websites to integrate and share the information.”65 Currently, companies may optionally 

upload this information via SAMR’s National Enterprise Credit Information Publicity System, but 

there is no particular incentive to do so.

It bears underlining that there is no known CSCS initiative or penalty scheme which 

exclusively draws on MCI. Viewed collectively, policies that deal with the applications of MCI 

characterize it as supplementary to the core PCI dataset, rather than as a standalone asset, and center 

on its potential to help regulators target the deployment of resources by more closely pinpointing 

which companies should receive a greater degree of regulatory attention.7

3.3 The boundaries of corporate social credit data for foreign companies

None of the above intends to suggest that the Chinese government does not collect any 

other data on foreign companies or is uninterested in collecting corporate data beyond what we 

have outlined above. Taking a wide-lens view, Beijing’s efforts to scrape, compile and analyze 

cross-border trade data — particularly in relation to the “Belt and Road Initiative” — are well 

documented.66 Nor does the above suggest that the scope of PCI may not be expanded in the future. 

The government extranet on which the NCISP is built contains a vast array of records, accessed 

and contributed to by 149 government departments,67 that policymakers may one day decide to 

include in the PCI dataset. Additionally, there are significant outstanding questions regarding the 

current and future scope of MCI. 

However, there are also increasingly clear regulatory and technical boundaries around what 

constitutes CSCS data, what type of data China intends to associate with the CSCS in the nearand medium-term. Social credit’s legal and regulatory mechanisms — including CSCS sanctions, 

rewards and grades — are principally driven by PCI, and there are no social credit regulations 

or initiatives wholly based on or driven by other datasets. Though the Chinese government may 

collect any amount of data on foreign companies, such data is not currently relevant to the CSCS 

and does not have any impact on corporate social credit profiles. The conflation of non-CSCSrelated data collection with CSCS data muddles the issue of corporate social credit and impedes 

clear-eyed analysis of the system.

Finally, it is significant to note that from a technical perspective, corporate social credit 

files must be tied to a Unified Social Credit Identifier, which is only assigned to entities registered 

in China, and therefore core CSCS databases do not appear to support the creation of social credit 

files on foreign companies with no registered Chinese entity. Moreover, as PCI is only generated 

in the course of China-based regulatory operations, companies and individuals located outside of 

China will not trigger the mechanisms that generate these records. This applies equally to the types 

of MCI that are currently defined.

7 Example: Key SCS policymaker Lian Weiliang outlines core role of PCI in one CSCS-related grading system: 

State Council Information Office of the People’s Republic of China, “The Comprehensive Evaluation System for 

Public Credit is Being Established and Perfected (公共信用综合评价制度正在建立和完善之中),” July 18, 2019. 

Translation. http://webcache.googleusercontent.com/search?q=cache:http://www.gov.cn/xinwen/2019-07/18/content_5411351.htm.
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Section 4

CSCS Legal Mechanisms: Blacklists, Redlists, Penalties, and Rewards

As outlined in Section 3, CSCS files are the centralizing point for 19 categories of government 

records shared by government agencies across China. However, two of those categories —blacklist 

and redlists — have by far the greatest impact on a company’s social credit standing. Under the 

CSCS, blacklists and redlists are the primary determinants of whether a company is sanctioned 

or incentivized, and thus deserve particular attention. In this section, we will examine how the 

CSCS uses centralized blacklist and redlist records to reward consistently compliant companies 

with increased access to the market and penalize non-compliant companies with restricted market 

access.

4.1 Blacklists and redlists

A blacklist is a type of public record which identifies companies and individuals found 

in violation of a pre-determined set of regulations — for example, one blacklist may identify 

companies which have violated work safety regulations, while another identifies parties found in 

violation of patent laws. A redlist is the opposite: a roster of companies and individuals demonstrating 

consistent compliance with a specific set of regulations, such as consistent tax payment or low rates 

of import-export violations. 

Blacklists and redlists have been an integral component of the CSCS since the system 

was first proposed, and though the concept of blacklists and redlists existed in China long before 

the release of the Planning Outline,

8

 it is under the CSCS that these lists have been become a 

standard feature of China’s new market regulation regime. The 2014 Opinions on Promoting 

Institutionalization of Integrity Construction called on each government body and regulator 

participating in the CSCS to develop blacklists and redlists relevant to their sector, with a priority 

on sectors in which malfeasance poses a significant threat to public safety or has caused “public 

concern.”68 The State Council’s 2016 Guiding Opinions on Establishing and Improving the Joint 

Incentive System for Trustworthiness and Joint Disciplinary System for Untrustworthiness further 

pressed for blacklist and redlist standardization. 

In response to these policies, government bodies — guided by the NDRC — formulated 

regulations establishing blacklists and redlists for their areas of jurisdiction. The majority of existing 

blacklists and redlists were created between 2016 and 2018. Since then, the announcement of new 

national-level lists has slowed dramatically. As of November 2019, forty established blacklists and 

eight redlists were in effect at the national level.69 Of these, about half have a broad scope, such as 

those targeting violations in the areas of environmental protection, import-export, social security, 

8 Though it is unclear when blacklists were first used in China, they have been employed for regulatory purposes 

since at least the early 2000s, and likely long before. The 2002 treatise references blacklisting as a familiar tool that 

should be standardized under the CSCS. Examples of blacklists and redlists in effect prior to Planning Outline release: State Food and Drug Administration of the People’s Republic of China, Regulations on the Administration of 

the “Black List” of Drug Safety (Trial) ( 药品安全“黑名单”管理规定(试行)) , August 13, 2012. Translation. http://

www.hngy.gov.cn/zwgk/zdly/spaq/7647/content_1444667.html. ; China Information Broadcast Network, “8 Zhejiang Enterprises Selected for ‘Customs Red List’ - Integrity is the Key” (8家浙企入选“海关红名单” 诚信是关键), 

March 1, 2009. Translation. http://zj.cnr.cn/xwdd/200708/t20070824_504550479.html. 
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tax arrears, and e-commerce fraud. The remaining blacklists are only applicable to enterprises and 

professionals operating in specific sectors, such as financial services, transportation, insurance, 

salt production,9 domestic services, travel, real estate, food, agriculture, and medicine. Some 

government agencies control more than one blacklist, particularly agencies whose regulatory 

mandate is broad, such as SAMR (which controls blacklists identifying violators in the areas of 

food safety, product quality, and general business operations), the Ministry of Human Resources 

and Social Security (which controls a blacklist identifying companies that fail to pay migrant 

workers’ wages, and another for companies that violate social security statutes), and the Ministry 

of Transport (which controls a blacklist for companies that overload transport vehicles and another 

for logistics providers). 

The creation of new blacklists (and redlists) is coordinated through the NDRC and the Joint 

Inter-ministerial Council, which cooperates with state agencies to identify appropriate lists for each 

sector. The documents that establish new national lists — called Memorandums of Understanding 

(MOUs) — all follow a similar format: they first enumerate the purpose of the list and its targets, 

and then they note the penalties or rewards to which parties included on the list will be subject (see 

all MOUs in Appendix III).

Although the NDRC is involved in the creation and ratification of blacklists and redlists, 

the administration of these lists is not centralized under any one government body. After a list has 

been created, the state agency that controls each list has primary authority to determine which 

companies are added to it.10 For example, the State Taxation Administration (STA) has the authority 

to blacklist companies for tax fraud, tax arrears in excess of RMB 100,000, invoice forgery, and 

other tax-related violations. Conversely, the STA has the authority to redlist companies that have 

paid taxes in full for two consecutive years, and have not been blacklisted by any other state agency. 

State agencies may not arbitrarily determine which companies and individuals are 

blacklisted. Some MOUs directly enumerate the violations that will lead to blacklisting, other 

MOUs simply state which types of violations will lead to list inclusion and specify inclusion 

criteria in separate documents.70 For example, a company may be included on the General 

Administration of Customs blacklist of “dishonest enterprises” for any one of ten violations which 

include smuggling, committing more infringements within a given year than 0.1 percent of the 

total number of customs declarations and manifests submitted by the company in the previous year, 

being in arrears of payable fines, providing false information to Customs, and “serious” obstruction 

of Customs officers in the performance of their duties.71 In mid-2020, the Guiding Opinions on 

Further Regulation draft updated “industry blacklisting standards and procedures to require both 

9 In 2016, the government moved to end the state monopoly on salt, allowing producers to determine their own 

prices and distribution channels. The creation of a salt industry blacklist is intended to enforce regulations on the 

newly liberalized industry and ensure product safety (such as the sufficient addition of iodine) in the absence of the 

state monopoly.

10 For examples of blacklist authority relegation, see Articles 4 and 5 in: State Administration of Work Safety of 

the People’s Republic of China (duties relegated to Ministry of Emergency Management after 2018 Chinese government restructure), Implementation Measures for Joint Punishment for Untrustworthy Conduct in the Field of Work 

Safety, (对安全生产领域失信行为开展联合惩戒的实施办法), May 9, 2017. Translation. http://webcache.googleusercontent.com/search?q=cache:https://www.mem.gov.cn/fw/cxfw/xycx/zdwj/201705/t20170509_245783.shtml. 
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a serious violation of law and [either] a threat to health or safety, disruption of the marketplace, 

violations of judicial or administrative orders, or refusals to perform national defense duties.”72

The stipulations for redlist inclusion are similarly enumerated. Companies qualify for 

inclusion on the Ministry of Emergency Management11 work safety redlist if they meet six criteria, 

including no record of violations or significant work safety incidents by the company, its legal 

representatives, or top safety management personnel within the past three years, the company has 

issued a credit commitment letter promising to continue to operate in good faith, and the company 

has not been blacklisted by any other state agency.73

As blacklists are established to address recurring or widespread violations which regulators 

perceive as particularly problematic, they serve as an indication of China’s regulatory priorities 

and shed some light on which regulations China’s judicial system struggles to enforce. The largest 

blacklist in China — the “defaulter blacklist” — is controlled by the Supreme People’s Court, and 

targets companies and individuals who fail to carry out court-ordered judgements, such as paying 

fines or issuing public apologies.74 This list was created in response to the government’s longstanding difficulties collecting on court-ordered payments due to debtors concealing collectable 

assets. Another blacklist targets the oil and natural gas industry, identifying parties which break 

laws related to “prospecting, development, storage and transport, processing and refining, import, 

export, or wholesale” of energy products.75 In the years leading up to and immediately following 

the release of this list, China’s state-run energy sector has been plagued with scandal. “At least 

12 senior-level [National Energy Administration] officials have been investigated or charged with 

corruption in the past decade... [and] officials from China’s oil and coal sector have been among 

the most high-profile corruption cases ever since President Xi Jinping started the anti-corruption 

campaign... .”76

Although blacklists are established by state agencies at the national level, it is the local 

branches of those same agencies that typically carry out the blacklisting of companies registered 

within their regional jurisdiction. For example, the blacklist for violations of product quality 

statutes was established by SAMR’s national office, but it is SAMR’s county, municipal, and 

provincial product quality inspection officials that conduct investigations on local companies and 

add violating companies to the list. The 2020 Guiding Opinions on Further Regulation specify that 

“[b]lacklisting decisions should generally not be made below the county-level and are reviewed at 

the provincial level.” 77

Both blacklists and redlists are classified as PCI and are a matter of public record.78 When a 

regulator places a company on a list, a record of that inclusion is added to the company’s national 

social credit file and promulgated to all other regulators and the general public via the NCISP. 

The NDRC is responsible for administering the NCISP and CSCS data sharing channels, and thus 

plays a coordinating role in blacklist collation. Once non-compliant companies and consistently 

compliant companies can be identified via the blacklist and redlist records in their centralized 

CSCS files, regulators can take steps to either limit or extend that company’s market access.

11 Functions of the former State Administration of Work Safety were merged under the Ministry of Emergency 

Management in the Chinese Government’s 2018 restructure.
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4.2 Ramifications of list inclusion: Unified Rewards and Punishments

Inclusion on a list triggers the primary CSCS disciplinary mechanism, Unified Rewards 

and Punishments, under which companies blacklisted by any regulator are subject to operational 

sanctions imposed not only by the regulator that blacklisted them, but also by any other regulators 

which have agreed to honor the specific blacklist on which the company is included.12 Conversely, 

if a company is redlisted by one state agency, they become entitled to incentives offered by 

multiple agencies. Such inter-agency cooperative agreements are ratified via Memorandums of 

Understanding (MOUs) that stipulate which regulators will impose penalties in the case of blacklist 

inclusion, or issue rewards in the case of redlist inclusion.13

Penalties leveraged against blacklisted companies vary slightly from blacklist to blacklist, 

depending on which agencies have signed on to honor that list, but many of the same sanctions 

appear on the majority of MOUs. The MOU underpinning the Ministry of Agriculture and Rural 

Affairs (MARA) blacklist targeting companies who have violated agricultural regulations provides 

a standard example. Companies on this blacklist face 25 cross-sector sanctions including: restrictions 

on participating in government procurement (imposed by the Ministry of Finance), restrictions on 

issuing stocks and bonds (People’s Bank of China, Securities Regulatory Commission), restricted 

use of government land (Ministry of Natural Resources), restricted access to financial subsidies 

and preferential policies (multiple agencies), suspension of approvals on sci-tech research and 

development projects (Ministry of Science and Technology), and more.79 In contrast, when 

a transport engineering or construction company is placed on the Ministry of Transportation’s 

redlist of trustworthy enterprises, it becomes entitled to 63 cross-sector benefits, including fasttrack handling of administrative approvals (multiple agencies), increased likelihood of winning 

procurement bids (multiple agencies), reduced inspection rates (Ministry of Transport), priority 

participation in preferential policies (NDRC), fast-tracked approval of import-export licenses for 

steel and other goods (Ministry of Commerce), priority access to loans and financing as long as 

financial credit history is sound (People’s Bank of China, China Banking and Insurance Regulatory 

Commission), preferential treatment in real estate transactions (Ministry of Housing and Urban 

Rural Development), priority assistance in patent applications and trademark registrations (China 

Council for the Promotion of International Trade), and others.80

12 Unified Rewards and Punishments was incrementally established in a series of foundational social credit policies, including the Planning Outline and Opinions on Promoting Institutionalization of Integrity Construction, and 

refined in two core documents: State Council, Guiding Opinions on Establishing and Improving the Joint Incentive 

System for Trustworthiness and the Joint Disciplinary System for Dishonesty (关于建立完善守信联合激励和失

信联合惩戒制度加快推进社会诚信建设的指导意见), July 12, 2016. Translation. http://jszx.court.gov.cn/2550/

ExecuteStandard/14535.jhtml; National Development and Reform Commission and People’s Bank of China, 

Guiding Opinions on Strengthening and Regulating the Management of the List of Targets for Joint Incentives for 

Trustworthiness and Joint Punishment for Dishonesty (关于加强和规范守信联合激励和失信联合惩戒对象名单

管理工作的指导意见), October 30, 2017. Translation. https://webcache.googleusercontent.com/search?q=cache:hze2bITWZMEJ:https://www.ndrc.gov.cn/xxgk/zcfb/ghxwj/201711/t20171103_960925.html+&cd=1&hl=en&ct=-

clnk&gl=ph.

13 Complete list of MOUs available at China Law Translate, “Legal Documents Related to the Social Credit System - MOUs on Joint Rewards and Disciplinary Actions”. https://www.chinalawtranslate.com/en/social-credit-documents.
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The 2020 Guiding Opinions on Further Regulation draft includes calls for the creation 

of a standardized index of lawful CSCS sanctions, stating that “[a]ll credit punishments must be 

listed in a national catalog of penalties drafted in conjunction with experts and other concerned 

parties, ... [and that] an explicit legal basis must be provided for all possible punishments.”81 As 

of writing, this catalog has not yet been released. Overall, the scope of CSCS punishments can 

be summarized as “higher scrutiny or restrictions in authorizing necessary permits, credentials, 

or approvals, higher scrutiny or restrictions on participation in government contract bidding or 

authorization of use of government resources, restrictions on receiving / revocation of awards and 

honors, increased routine regulatory oversight, [and] limits on receiving government benefits.” 82

At the consumer level, the Planning Outline and related policies also encourage the active 

promotion of blacklists and redlists on government websites and in traditional and social media. 

Regulators hope this will organically “result in the [public] praise of companies which operate 

honestly and the censure of dishonest behavior,” thus adding an additional layer of pressure on 

companies to comply.83

The CSCS also seeks to ensure that the consequences of blacklisting are inescapable by 

extending the Unified Punishments imposed on blacklisted companies directly to responsible key 

personnel — creating an additional concern not just for foreign companies, but for their key Chinabased and even global executives. Each blacklist MOU defines a scope of responsibility in terms 

of who will be personally subject to penalties in the event of blacklisting. This may include the 

company’s legal representative, board members, actual controllers, and other parties responsible 

for the violation.84 Under Unified Rewards and Punishments, responsible parties, including foreign 

personnel, may be subject to penalties imposed by members of the Joint Inter-ministerial Council, 

such as restrictions on luxury consumption including real estate transactions (imposed by Supreme 

People’s Court), 85 restrictions on the purchase of plane and high-speed rail tickets (imposed by the 

Civil Aviation Administration of China and China Railway), or ineligibility to serve in management 

positions in industries where malfeasance may cause greater damage to public health or economic 

stability, such as the finance and chemical sectors. 

4.3 Rectifying violations: objections and credit repair

In a 2017 national CSCS policy, the NDRC emphasized that enabling credit restoration 

and repair is one of the foundational principles of Unified Rewards and Punishments.86 Chinese 

policymakers envision credit repair as a process through which “market players who have behaved 

with slight dishonesty can reform and operate in good faith,” but also as a structured process with 

“preconditions, procedures and limits.”87 That vision, however, has not yet been realized: while 

Chinese regulators are currently taking steps to standardize the procedures for blacklist inclusion 

and removal, these procedures are still undergoing review and finalization.

The draft 2020 Guiding Opinions on Further Regulation states that “before being 

blacklisted, parties must be given notice of the reason and the legal basis and have a chance to 

object. If blacklisted, they must be given a clear written decision indicating the reasons, [and] 

rules for removal... .”88 Poor notification procedures have been a common complaint regarding 
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the CSCS over the last several years, with blacklisted parties often unaware that they had been 

blacklisted until they felt the effects of imposed penalties.14

 There is currently no national, unified procedure for blacklist removal; as with many 

features of the CSCS, general national guidelines have been provided by the NDRC,89 but in 

practice, removal procedures are currently determined on a list-by-list and agency-by-agency 

basis, and companies must typically apply for removal to the agency that controls the blacklist on 

which they were placed. However, some generalizations about credit restoration procedures can be 

made based on a collective overview of multiple credit repair documents. 

First, as a general guideline, the NDRC segments blacklist behavior into three categories: 

“generally untrustworthy,” “seriously untrustworthy,” and “particularly seriously untrustworthy.”90

Companies found to have engaged in “particularly serious untrustworthy behavior” may have their 

business license revoked and credit may be irreparable. This designation includes:

● Violations of food and drug safety, environmental protection, engineering 

quality, production safety, product quality, and fire safety regulations

● Bribes, tax evasion, debt default, failure to pay wages, illegal fund-raising, 

contract fraud, pyramid schemes, unlicensed operations, infringement of 

intellectual property rights, bid rigging, false advertising, infringement of 

consumer rights, infringement of investor rights, serious Internet behavior 

violations, and disruption of social order

● “Other”

The definitions for the remaining two designations are less specific. “Serious untrustworthy 

behavior” is defined as “acts that damage individual physical health or safety, seriously disrupt 

social order, or constitute a failure to fulfill court orders or an infringement upon national security, 

as well as other malicious acts defined by laws and regulations or the penalty-issuing agency.” 

“General untrustworthy behavior” is defined as that which causes “marginal damage” to society. 

14 Two U.S. multinationals indicated in interviews that headquarters was unaware that a branch office, located in a 

different province, had been blacklisted until the deadline for objection had expired. Such complaints have also been 

frequently reported in English-language media articles regarding the citizen social credit system. 
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Forced out of the market: the case of OSI’s Shanghai Hsui

The blacklisting procedures and credit consequences for the most serious offenders can 

be illustrated by the case of Shanghai Hsui, the Chinese subsidiary of U.S. holding company OSI 

Group. A food supplier with customers including McDonald’s and KFC, Shanghai Hsui became 

mired in scandal in 2014 when a local TV station reported “that staff were using expired meat, 

falsifying production dates and violating other hygiene-related issues.”91

A 2016 court case found the firm guilty in 2016, after which the directly responsible employees within the company were sentenced to prison and fined for the crime of producing and 

selling fake and inferior products, as were members of Shanghai Hsui’s holding company OSI.92

This had credit-related consequences: the local branch of SAMR revoked Shanghai Hsui’s 

food production licenses, the company was designated as a “seriously untrustworthy producer”93

and added to SAMR’s food safety blacklist by Shanghai SAMR officials for a period of two years 

(2016-2018). Additionally, three key responsible parties (the quality supervisor, factory manager 

and planning director) within the organization were personally blacklisted for a period of five years 

(2016-2021). The company reportedly lost RMB 6 billion in the year after the scandal,94 though 

how much of those losses resulted from CSCS penalties rather from the scandal more generally, is 

unknown. The company did not repair their credit — though OSI still operates in China, Shanghai 

Hsui appears to have effectively halted operations.95

Generally speaking, regulators require companies to resolve the cause of the violation 

before applying for rectification.96 Following correction of the underlying issue, rectification 

procedures typically follow a fairly standard process, with some variation depending on the severity 

of violation:97

1. The company applies to the government agency that issued the penalty.

2. The agency issues notification of acceptance or rejection of application.

3. If the application is accepted, the agency will call a meeting with the company’s 

legal representative to discuss the issues, review the company’s corrective 

steps, and require the representative to promise that there will be no repetition 

of wrongdoing.15

4. The agency conducts an inspection or reviews evidence that corrective action 

was taken.

5. The agency hands down a decision within five days of the inspection or review. 

6. The decision is made public and pushed out through various data sharing 

channels. 

15 These interviews most often conducted by internal departments of state agencies dedicated to addressing 

malfeasance and credit-based concerns. For example, the Department of Enterprise Management and Audit-Based 

Control within the General Administration of Customs oversees violations and credit-related issues of importers and 

exporters.
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However, there is a mandatory minimum time that blacklisted companies must remain 

on a list before they can apply for removal, regardless of how quickly the underlying problem is 

rectified. These minimums vary from list to list and agency to agency, but inclusion typically lasts 

for a minimum of three to six months and a maximum of five years depending on the severity of 

the violation.98Additionally, for “general dishonest behavior,” a removal may be facilitated if the 

business owner undertakes a credit repair course given by a government-authorized credit services 

organization.16

In practice, the procedures for credit repair in all but the most serious cases have alternately 

been criticized as too difficult and too easy. Some anecdotal evidence describes a convoluted 

bureaucratic process fraught with unresponsive personnel and long wait times for removal, even 

once the conditions for removal have been met.99 In contrast, another report detailing one Chinese 

business owner’s experience with blacklist removal described a lax and ineffectual process in 

which government-approved third-party credit education courses are used as a loophole through 

which the owners of blacklisted businesses may pay a nominal fee and take a brief examination 

to be removed, and companies may be allowed to continue operating “without fully atoning for 

their crimes.”100 This discrepancy may be due to the fact that state agencies have administrative 

authority over their own lists, implementation and resources dedicated are not uniform from agency 

to agency and location to location, thus the efficiency and clarity of credit repair procedures will 

necessarily vary. 

4.4 Market access controls in wider industry

The Planning Outline clearly frames the Party’s vision of the CSCS as an initiative that 

should be adopted and applied cooperatively not only by regulators, but also integrated into wider 

industry in the private sector. To that end, policymakers have experimented with several initiatives 

that expand the influence of blacklists beyond the regulatory space. In 2016, prominent Chinese 

tech players – Alibaba, Tencent, Jingdong, 58 Tongcheng, Didi, Baidu, Qihoo 360, and Shunfeng 

Logistics – signed on to a government action plan to penalize e-commerce retailers, apps, and 

other online businesses which had been blacklisted by regulators for fraudulent online activity 

such as forging positive reviews, shipping empty parcels to bump sales numbers, or reselling user 

data, activities which are illegal under Chinese consumer protection laws. Under this initiative, 

tech platforms reference CSCS blacklist data and use it to impose penalties such as restricting the 

creation of new user accounts, deleting accounts, restricting participation in marketing activities, 

lowering on-platform ratings, or marking the company as a “risk” in search results.101

Additionally, several pilot initiatives empower industry associations to adopt and enforce 

CSCS-style punishments and rewards within their sectors.102 For example, in April 2018, the 

16 List of authorized credit repair agencies: Credit China, “List of Credit Report Service Providers” (信用报告

服务机构名单), https://www.creditchina.gov.cn/xyxf/xygbfwjgmd/ ; Policy on credit repair through Credit China: 

General Office of the National Development and Reform Commission of the People’s Republic of China, Notice on 

Further Improving the “Credit China” Website and Local Credit Portal Website Mechanisms for Credit Repair of 

Information on Administrative Punishments (国家发展改革委办公厅关于进一步完善“信用中国”网站及地方信

用门户网站行政处罚信息信用修复机制的通知), April 30, 2019. Translation. http://webcache.googleusercontent.

com/search?q=cache:https://www.ndrc.gov.cn/xxgk/zcfb/tz/201905/t20190514_962445.html.
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NDRC invited the China Chemical and Pharmaceutical Industry Association (CCPIA, 中国化学

制药工业协会) to cooperate in one of the first government-plus-industry CSCS trials. Under the 

partnership, the CCPIA was empowered to administer industry blacklists and redlists, establish 

credit records for member companies, and enforce joint punishments on violators in the fields of 

healthcare, pharmaceuticals, and medical devices.103

Technically speaking, industry associations, tech platforms, and other such organizations 

are not legally required to participate in the CSCS in this manner. The draft of the 2020 Guiding 

Opinions on Further Regulation states that no government body “shall force financial institutions, 

credit service agencies, industry associations, chambers of commerce, news media, or other entities 

to punish untrustworthy entities.” However, while these entities may not be “forced” to participate, 

they may be encouraged or coerced to do so through invitations or suggestions by the NDRC or 

the PBOC. 

Depending on the effectiveness of these pilot projects, it is likely that the NDRC will seek 

to broaden the Unified Rewards and Punishments dragnet by working to extend the effectiveness 

of blacklists through enlisting participation from a broader body of industry actors. The overall 

ubiquity of the CSCS will, in part, depend on how wide this dragnet becomes. Punishing and 

rewarding firms, however, is not the only purpose for which blacklist data, and PCI more widely, 

is used. It is also used to help state agencies determine where to concentrate limited regulatory 

resources.
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Section 5

Targeted Regulatory Resource Deployment

The CSCS is part of China’s larger shift toward a data-driven regulatory regime,104 a shift 

motivated in large part by the need to alleviate burdens on regulators whose resources are stretched 

thin.105 Rather than applying the same level of regulatory scrutiny to all enterprises, Beijing hopes 

to move toward a more targeted scheme wherein companies are segmented according to their 

social credit: those with good credit are given less attention, and those with poor credit become the 

target of tighter regulatory focus and control. This was expressed in the 2019 Guiding Opinions, 

which stated:106

For market entities with good credit and which are deemed to be low risk, the 

frequency of inspections can be reasonably lowered to reduce the impact on normal 

production and operation; for market entities with average credit risk, random 

inspections can be conducted at regular rates and frequency; and for those market 

entities that are untrustworthy and high-risk, the inspection frequency can be 

appropriately increased.

This shift is also intended to invite greater participation in the market by lowering the barriers 

to market entry, and “working toward a comprehensive and systematic monitoring of companies’ 

day-to-day behavior, continuously testing their trustworthiness as they actively participate in the 

market.”107 To this end, policymakers are supporting the development and deployment of various 

segmentation and grading schemes, as well as risk prediction models and platforms, based on PCI, 

MCI, and independently-collected data. 

5.1 Corporate social credit “scores”

Regulatory bodies, private companies, and industry institutions are taking advantage 

of publicly available CSCS files (and the PCI they contain) to develop a variety of grades 

and ratings which reflect various assessments of a given company’s operational and financial 

soundness. 

These grades do not interact to form a unified, algorithmically controlled “social credit 

scoring system.” Rather, at the encouragement of the NDRC, these grades have been independently 

developed by public or private sector actors to reflect a discrete aspect of a given company’s 

credibility. For example, regulatory bodies have developed grades to measure level of compliance, 

private credit rating agencies are developing grades to measure financial creditworthiness, and 

industry bodies are developing grades to measure product and service quality. The factor that 

unifies these dozens, if not hundreds, of “social credit grades” is that they are all based, to varying 

degrees, on PCI, and that the NDRC has encouraged and supported their development. These 

grades may be loosely grouped into four types based on their intended purpose and issuing body 

(see overview in Table 2). 

1. Compliance grades: China’s state agencies have been grading enterprises on regulatory 

compliance long before the advent of the CSCS, and though these grades are as varied as the 
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agencies that develop and issue them, with the emergence of the PCI dataset under the CSCS, many 

compliance scoring algorithms have been adjusted to at least partially base grades on PCI data. 

Some grades are standardized at the national level, such as the State Taxation Administration (STA) 

taxpayer rating system108 and the Ministry of Transport grading system for companies engaged in 

the construction of roads and waterways.109 Others are created by regulators at the local level, such 

as the Datong Health and Family Planning Commission’s credit grades for city hospitals.110

Many — though not all — of the compliance grading systems operate on a letter-based 

scale (A-D), underpinned by a points matrix (90-100 points equals Grade A). Under the STA’s 

grading system, companies start with 100 points (Grade A), and points are deducted for any one 

of 95 specific violations. For example, companies who are found in arrears of amounts equal to or 

in excess of RMB 50,000 will have 11 points deducted from their overall grading matrix (which 

would result in a Grade B), and three points or fewer deducted for arrears of lesser amounts.

Under the CSCS, blacklist inclusion or other significant incidents of non-compliance count heavily 

against compliance grades, often resulting in an immediate assignment to the lowest grade level. 

Compliance grades determine how companies will be treated by the grade-issuing agency. 

In the case of the STA, taxpayers with higher grades will receive preferential treatment by the 

agency, those with middling grades receive neither positive nor negative attention, while those at 

lower grade levels will be subject to increased STA scrutiny.

Compliance grading is still evolving; many of the policies underpinning effective 

compliance grading systems are still in a trial phase, and agencies at all levels of government 

continue to announce the impending release of new or adjusted grading schemes.17

2.Quality grades:The central government is also encouraging China’s industry associations 

and Chambers of Commerce to develop PCI-based grading systems for their member companies. 

A 2016 policy urged such organizations to “cooperate with qualified third-party credit service 

agencies to conduct assessments on members’ credit status and improve member credit evaluation 

mechanisms.”111 At the national and local levels, organizations such as the China Industrial Gases 

Industry Association (CIGIA), the China Construction Machinery Association112 and the Wuhan 

Software Industry Association113 issue credit grades based on a combination of the association’s 

own data collected on member companies, self-submitted data by member companies, and PCI. 

The CIGIA grading matrix, which is highly representative of those released by other industry 

associations, considers five categories of information: basic company information, competitiveness, 

management ability, financial strength, and the PCI dataset, of which PCI data is given the heaviest 

weight, amounting to 30 percent of the overall grade.114 The ramifications of a poor quality grade 

are not entirely clear, but it is likely that these grades will be used to promote “industry selfgovernance,” under which industry associations put pressure on companies with low grades to 

17 Example: Announced Ministry of Ecology and Environment corporate compliance grading system for environmental protection: Ministry of Ecology and Environment of the People’s Republic of China, Opinions on Further 

Deepening Ecological and Environmental Regulatory Services to Promote High-Quality Economic Development(关

于进一步深化生态环境监管服务推动经济高质量发展的意见), September 8, 2019. Translation. http://webcache.

googleusercontent.com/search?q=cache:http://www.mee.gov.cn/xxgk2018/xxgk/xxgk03/201909/t20190911_733474.

html.
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improve their performance, as well as disseminate grades to the general public. Additional clarity 

regarding how industry association grades interact with the CSCS is expected in the coming years, 

as regulators are pushing for the formulation of rules that define a standardized system for industry’s 

involvement in social credit.115

3. Financial Credit Grades: Financial credit rating agencies (CRAs) play a key role in 

the CSCS (details in Section 6.2), and China’s credit ratings industry is developing alongside the 

social credit system. The NDRC has encouraged credit rating agencies to take advantage of PCI 

availability, and to use it in conjunction with their own data and proprietary algorithms to develop 

enterprise credit ratings indicative of financial risk. CRAs then supply regulators and industry 

associations with rating results which support their own assessments.116

4. The Comprehensive Public Credit Grade (公共信用综合评价): In 2019, the NDRC 

announced the impending release of the “Comprehensive Public Credit Grade,” which will loosely 

serve as a net assessment of a company’s overall social credit profile. Under the Comprehensive 

grading system, a rating of “excellent,” “good,” “fair,” or “poor” is assigned to every registered 

entity in China.18 The exact metrics that contribute to a company’s final Comprehensive Grade 

have not been made public, but regulators have stated that these grades are primarily based on PCI, 

and that they may also take compliance grades, quality grades, financial grades into account.117

The NDRC announced the completion of the first round of Comprehensive grading in 

September 2019, stating that 33 million companies in China had been assigned a Comprehensive 

grade, but only a tiny fraction of those have been made public, with the “excellent” and “poor” 

graded companies in the natural gas, coal, travel, and transportation sectors published on the Credit 

China website.118 It is currently not possible for companies to look up their own Comprehensive 

grade, and such grades have not been integrated into public CSCS files or databases. 

The NDRC has stated that once fully implemented, Comprehensive grades will serve as a 

general indicator of a company’s social credit standing, and are issued as a guidepost to help local 

regulators decide how much regulatory scrutiny will be applied to a given company.119 Companies 

with “excellent” or “good” Comprehensive Grades will receive less attention from local regulators, 

while those with “fair” and “poor” grades will be interviewed and urged to rectify their behavior. 

In the case of “poor” grades, key personnel may be required to undergo credit training courses.120

One common misperception regarding corporate social credit grades is that a company 

receiving a low grade will be blacklisted as a result of that grade. In reality, this works the other 

way around: companies receive low grades if they have been blacklisted. If a company has been 

blacklisted based on regulatory violations, the blacklist record is included in the company’s CSCS 

file as PCI. Considering that Compliance, Quality, Financial and Comprehensive Grades are 

18 Launch of Comprehensive Public Credit Grading system announced in: General Office of the State Council of 

the People’s Republic of China, Guiding Opinions of the General Office of the State Council on Accelerating the 

Construction of a Social Credit System and Building a New Credit-based Supervisory Mechanism (国务院办公厅

关于加快推进社会信用体系建设构建以信用为基础的新型监管机制的指导意见), July 16, 2019. Translation. 

http://webcache.googleusercontent.com/search?q=cache:http://www.gov.cn/zhengce/content/2019-07/16/content_5410120.htm.
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determined based on the PCI in a company’s CSCS file, a blacklist record would result in lower 

grades across the board.121 Thus, it is fair to say that grades are indicative of a company’s social 

credit standing, but do not determine social credit standing. Social credit standing is determined 

first and foremost by blacklists and redlists. 

Although grades are certainly a crucial feature of the CSCS, the issuance of grades is not 

the system’s paramount purpose, and we assess that the CSCS should not be understood as a 

grading mechanism. Rather, grades should be understood as one of the many weapons in social 

credit’s new market regulation arsenal. 

Table 2: Types of enterprise grades based on PCI19

Comprehensive 

Public Credit 

Grade

Compliance-based 

grades

Quality Grades Financial credit 

grades

Issuer NDRC, in 

cooperation with 

other regulators

Various regulators Industry 

associations

Private enterprise 

credit rating agencies

What they 

measure

Overall status of 

company 

Compliance with laws 

and regulations

Service and 

product quality, 

compliance, 

operational 

soundness

Investment risk

Rating scale Excellent

Good

Fair

Poor

Usually letter-based 

(e.g., A-D)

Various Various

What ratings 

indicate

Level of regulatory 

scrutiny

Level of market 

access

Not clear - 

intended to 

promote market 

awareness 

and consumer 

advocacy

Access to loans and 

investment

Who gets one Every registered 

entity in China 

Most companies will 

receive several from 

different regulators

Members 

of industry 

associations, any 

companies listed 

on app

All companies rated 

by that particular 

agency

5.2 Risk monitoring platforms

There is little available information regarding the degree to which the issuance of PCIbased grades is automated. However, automation of PCI and MCI analysis is being piloted on a 

series of regulatory platforms designed to support the process of determining targets for regulatory 

scrutiny. The largest of these platforms was developed under the Internet Plus Regulation 

19 Categorization matrix created by Trivium China from comprehensive review of regulations underpinning multiple PCI-based grading systems, official statements on purposes of various grade types.
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initiative (互联网+监管), a sub-segment of the national “Internet Plus” initiative, which aims to 

“deeply integrate network innovations with various fields of the economy and society.”122 Internet 

Plus Regulation centers around the construction of a centralized digital platform for market 

regulation that aggregates PCI, MCI, and non-social credit datasets such as those provided by law 

enforcement,123 then segments companies into buckets that determine the frequency at which they 

will be inspected.124 The Internet Plus Regulation platform is supported by technologies built by 

China’s internet tech giants, Huawei, Tencent, Alibaba, and funded by the State Council for a total 

of at least RMB 527.8 million.125

In 2019, the State Council selected the provinces of Hebei, Shanxi, Zhejiang, Anhui, and 

Fujian, along with the cities of Beijing, Yantai, Luohe, Guangzhou, Foshan, and Chongqing, to pilot 

Internet Plus Regulation in their jurisdictions.126 Of these, the Zhejiang pilot — nicknamed “531X”20

— is by far the nation’s most advanced, both technologically and in terms of implementation: the 

platform consolidates PCI and MCI and a grading system for local enterprises,127 and according 

to project progress reports, has collected 2.4 billion PCI records, and connects with 315 “creditrelated business systems across the province”.128

These programs are part of a national push towards “algorithmic regulation,”129 the 

deployment of big datasets — including social credit datasets — to augment human decisionmaking. While not inherently dangerous in itself, the emergence of algorithmic regulation has 

given rise to considerable debate about its fairness, transparency, and legality. Among the most 

critical of these is the issue of “algorithmic accountability,” or the inherent difficulty in verifying 

the fairness or accuracy of machine-generated recommendations “owing to the sophisticated 

computational processes upon which [algorithms] rely and their protection from disclosure ... , yet 

[they are] capable of exercising or informing decision-making power with highly consequential 

effects.”130 Neither algorithmic regulation nor the questions it raises are unique to China, but 

the deployment of automated, non-public-facing corporate segmentation mechanisms under an 

authoritarian government with an immature data privacy regime raises additional questions, not 

only in terms of how companies may assess algorithmic fairness, but how they might object in the 

event of unfair treatment.

20 531X is so named because it grades five targets (individuals, companies, social organizations, institutions, and 

government agencies), and combines three mechanisms (credit standards, credit regulation, and credit penalties) in 

one unified system. 
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Section 6

Lending and Finance

The 1999 social credit treatise, The National Credit Management System, was focused first 

and foremost on describing how the social credit system could be used crack down on corporate 

malfeasance. But the treatise also addressed a secondary issue, namely, China’s underdeveloped 

financial credit system for the assessment of lending risk. Though these two issues — corporate 

malfeasance and credit-based lending — appear unrelated, the treatise explicitly connects them. It 

does so by defining the idea of “credit” in expansive terms, combining the financial definition of 

“credit” or “creditworthiness” (i.e., the willingness and ability to repay one’s debts131) with a more 

basic notion of one’s overall reputability (i.e., honesty, promise-keeping, and integrity).132

Although China’s financial credit and social credit systems are distinct, areas of practical 

overlap do exist. Most notably, social credit data is now used as a supplement to financial credit 

data in the assessment of lending risk.133

Indeed, the CSCS and its regulatory underpinnings cannot be wholly separated from 

traditional financial credit assessments, and their deficiencies in the Chinese market. Specifically, 

lenders and regulators in China have long struggled to assess the creditworthiness of private 

business, particularly Micro, Small, and Medium Enterprises (MSMEs), as we explain below. In 

addition, the poor track record and politicization of bond ratings further underscore the need for a 

more accurate mechanism for lenders and investors to assess a company’s ability to repay its debt 

obligations. In this section we briefly examine these two key deficiencies of assessing traditional 

financial credit in China and look at the development of the CSCS as it relates to those deficiencies. 

6.1 Lending risk assessment for MSMEs

Assessing financial risk for private enterprises, particularly for entrepreneurs and MSMEs, 

has historically posed an intractable problem for Chinese lenders. This challenge has stemmed 

largely from the fact that China has the world’s largest unbanked population (225 million citizens 

do not hold an account at any financial institution),134 low rates of credit card use,135 and a largely 

collateral-driven system for assessing credit risk.136 Moreover, as of 2018, the PBOC’s Financial 

Credit Database included credit histories on only 35 percent of Chinese citizens,137 a stark contrast 

to the 88 percent of American citizens with trackable credit histories.138 Given that personal and 

corporate financial credit records serve as one substitute for trust between lenders and borrowers, 

the dearth of records is one of several factors that has resulted in an over-reliance on collateralbased lending, especially for small, family-owned businesses and other entities without ready 

access to China’s capital markets. 

Policymakers have sought in vain to address this issue for at least the last two decades. 

In 1998, Premier Zhu Rongji — the man responsible for advocating initial research into the 

social credit system — sent instructions to the Industrial and Commercial Bank of China (ICBC) 

requiring it to establish a credit department focusing on SME loans.139 A year later, he instructed 

government officials in Zhejiang province — China’s most SME-heavy provincial economy — to 

work with banks to make breakthroughs in supporting SMEs, and explicitly asked banks to lend 
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to SMEs without requiring collateral.140 Zhu’s efforts failed to solve the problem: 75.3 percent of 

China’s bank loans still go to large enterprises which have access to the assets needed to back large 

debts and the political capital to secure funding,141 and policymakers have continued to struggle to 

formulate an adequate solution.

More recently, throughout the 2018-2020 time period, the central government has 

repeatedly urged banks to increase lending to small and micro-enterprises,142 and relatedly, officials 

have attempted to leverage CSCS data to ameliorate the lack of risk assessment metrics through a 

joint NDRC and China Banking and Insurance Regulatory Commission (CBIRC) initiative called 

Xinyidai (信易贷).143 Xinyidai encourages the development of PCI-based financial risk assessment 

models specifically aimed at enabling SME loans. These models have been developed both by the 

central government as a service to banks and lenders and by banks and other lenders themselves, 

with the hope that access to such risk assessments will make lending to SMEs both more viable 

and financially attractive.

6.2 The corporate bond market and credit ratings

In addition to the weaknesses in China’s credit assessment mechanisms that have held back 

bank lending and other forms of indirect financing to private companies and SMEs, unreliable 

corporate bond ratings have also held back development of the bond market and a commensurate 

increase in direct financing for private companies.144 Specifically, tight state control over the 

corporate bond market has resulted in a disempowered, corrupt ratings industry whose ratings have 

historically been seen as largely ornamental:

Chinese credit rating agencies (CRAs) are a direct product of Chinese regulators’ 

mandate that all public bonds have to be rated. With a regulatory captive customer 

base, the Chinese rating industry, as a whole, has less incentive and pressure to 

provide a high-quality product: informative credit ratings. Furthermore, there is a 

generally negative perception of the quality of Chinese bond ratings. The fact that 

the vast majority of Chinese bonds are rated AA or better has raised doubts about 

the accuracy of Chinese ratings and concerns of over-optimism of Chinese CRAs 

and/or rating shopping.145

The birth of the CSCS directly coincides with China’s early attempts to reform the financial 

credit system and improve the quality and reliability of domestically issued corporate credit ratings 

in the early 2000s.146 Indeed, The National Credit Management System devotes several chapters 

to the topic. The treatise raises the point that the issuance of accurate ratings depends on access to 

dynamic data that assesses the “Five Cs of Credit Analysis,” or the Character, Capacity, Capital, 

Collateral, and Conditions of the bond issuer.147 We assess that both PCI and MCI offer alternative 

metrics that could fulfill a broader or deeper assessment of “character” metrics, which credit rating 

agencies may have had difficulty obtaining in the past. More generally, a range of policymakers and 

policy advisors increasingly see the ability to rate companies’ creditworthiness as a key element 

of financial soft power, and a driver of a country’s ability to influence and partake in global capital 

markets, as discussed in Section 10.4. 

This drive to improve China’s domestic ability to rate credit has taken place outside of CSCS 
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development and led to a proliferation of entities involved in domestic credit rating. In 2005, only 

five state-owned CRAs were authorized by the government to issue ratings for corporate bonds 

and other debt instruments,148 but in mid-2019, 130 private sector financial credit rating agencies149

were licensed to issue enterprise credit reports and grades. As the CSCS has been rolled out, these 

entities have been encouraged to align their rating mechanisms with the system by basing credit 

grades on PCI in addition to their own MCI.150 The relationship between the central government 

and these credit rating agencies is cooperative, and data does not only flow one way; the MCI 

obtained by these agencies — including the grades they issue — are passed back to the government 

for use in determining regulatory enforcement targets,151 and play a part in informing the results of 

enterprise credit ratings issued by local governments and industry associations.152
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Section 7

Technical Infrastructure

Beijing’s ultimate vision for the CSCS of seamless nationwide PCI sharing cannot be 

realized without the deployment of databases, servers and software that enable the collection, 

processing, and sharing of PCI. Thus, an understanding of CSCS technical infrastructure is critical 

to assessing the overall feasibility of the CSCS and the technical challenges its implementation 

presents. Here, we undertake a brief review of CSCS system architecture.

The deployment of PCI databases is highly decentralized, and each state agency and local 

government is responsible for the development, installation, and maintenance of their own hardware 

and software. Social credit platform contracts are farmed out to third-party tech companies via 

government procurement processes, and procurement records indicate that at least 100 government 

bodies have undertaken such projects.21 Deployment costs vary from platform to platform, with 

district- and city-level builds typically costing approximately RMB 3 million,22 while the State 

Administration for Market Regulation has spent upward of RMB 400 million on national rollout of 

its Enterprise Credit Information Publicity System alone.23

Although some of these databases are not accessible to the general public, as of April 

2020, 11 state agencies operate sector-specific, public-facing social credit and blacklist databases 

to publicize their own agency’s social credit data, such as the Ministry of Housing and Urban-Rural 

Development153 the Ministry of Finance,154 the Ministry of Culture and Tourism,155 and the Supreme 

People’s Court.156 An additional four agencies — the Ministry of Ecology and Environment, the 

Ministry of Science and Technology, the Ministry of Civil Affairs, and the Ministry of Human 

Resources and Social Security — have announced plans to build such databases.24

21 Data on CSCS projects collected from the Ministry of Finance portal for government bidding and procurement, 

which holds several thousand documents related to social credit technical infrastructure projects. Search terms that 

return relevant results include “social credit system (社会信用体系),” “public credit information (公共信用信息)”, 

“National Credit Information Sharing Platform (全国信用信息共享平台)”, “credit information platform” (信用信

息平台), among others. http://webcache.googleusercontent.com/search?q=cache:http://www.ccgp.gov.cn.

22 Average cost of district- and city-level social credit contracts collected from Ministry of Finance portal for government bidding and procurement. http://webcache.googleusercontent.com/search?q=cache:http://www.ccgp.gov.cn. 

23 Average cost of district- and city-level social credit contracts collected from Ministry of Finance portal for government bidding and procurement. http://webcache.googleusercontent.com/search?q=cache:http://www.ccgp.gov.cn. 

24 Announcements from state agencies on the construction or imminent implementation of sector credit databases: 

Ministry of Science and Technology of the People’s Republic of China, “National Working Conference on Science 

and Technology Supervision and Integrity Construction Held in Beijing” (全国科技监督与诚信建设工作会议在北

京召开), December 2, 2019. Translation. http://www.most.gov.cn/kjbgz/201912/t20191202_150272.htm. ; Ministry 

of Human Resources and Social Security of the People’s Republic of China, Guiding Opinions of the Ministry of 

Human Resources and Social Security on the Establishment of a Unified National Social Insurance Public Service 

Platform (人力资源社会保障部关于建立全国统一的社会保险公共服务平台的指导意见), September 24, 2019. 

Translation. http://webcache.googleusercontent.com/search?q=cache:b3uNvsWZS8wJ:www.mohrss.gov.cn/gkml/

zcfg/gfxwj/201909/t20190927_335478.html+&cd=1&hl=en&ct=clnk&gl=ph ; Ministry of Civil Affairs of the People’s Republic of China, “National Credit Information Sharing Platform (Phase II) Project - Announcement of Tender 

for Software and Hardware Equipment and System Integration” (全国信用信息共享平台(二期)项目(民政部
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Major Chinese tech players have won bids for certain aspects of national-level SCS 

data platforms – Baidu for buildout and upgrade of the Credit China website,157 Tencent for the 

development of the Credit China mobile app and service support system,158 Neusoft for software 

related to the National Credit Information Sharing Platform159 – but overall, contracts have not been 

concentrated in the hands of a few select firms. Deals have been awarded to more than 50 domestic 

companies at the national level, and hundreds of vendors have been involved in provincial, urban, 

and district systems. 

7.1 Hardware and software

Just as there is no one company responsible for social credit platform buildout, there is also 

no single hardware or software package for CSCS systems, thus the infrastructure that drives these 

databases is as varied as the companies that build them. Common U.S. enterprise data technologies 

are used in some cases, including Oracle databases,160 Windows Server operating systems, and 

physical servers running on Intel processors,161 while domestic technology is preferred in others at 

the discretion of the commissioning department. 

What unifies these disparate systems is that they are built to adhere to the national technical 

standards framework for PCI exchange (as introduced in Section 3), and are enabled to share 

data across the NCISP via a standardized digital uplink based on RSA-encrypted public/private 

keys, which allows for secure transmission of credit records with no dependency on the type of 

underlying hardware or software used for data storage.162 The simplicity and modularity of this 

transfer mechanism allows the transfer of credit information from any enabled server, and appears 

to have been designed to unify a variety of domestic platforms. 

7.2 Next-generation technologies

Reports that appear to link the CSCS to next-generation technologies such as facial 

recognition-based surveillance feeds, remote sensing output, or auto-flagged social media content 

have resulted in concern among foreign companies and governments that the CSCS penalties and 

CSCS-related scores are driven by data collected through these sources. Although the NCISP is 

ushering in a new age of government data aggregation and sharing, a review of the PCI technical 

standards, PCI catalogs, and blacklist MOUs clarifies that CSCS records hold PCI only, and there 

is no input channel through which next-generation data sources can feed information directly 

into CSCS files (see Section 3). PCI records are still manually generated, collected, and input by 

inspectors and civil servants.163

However, there are several examples of next-generation technologies being piloted in 

CSCS-adjacent capacities, such as the use of remote sensing technologies to collect operational 

data used to identify a potential violation. For example, the Environmental Protection Bureau of 

the Yichun Economic Development Zone has required companies to install on-site instruments 

to track and measure pollution emissions.164 Similarly, regulators in the Changshu Economic & 

Technological Development Zone employ real-time monitoring of emissions, sewage, pH levels, 

and power consumption, and conduct inspections whenever abnormal values are detected.165 The 

建设部分)软硬件设备及系统集成招标公告), March 13, 2018. Translation. http://www.mca.gov.cn/article/gk/

zfcg/201803/20180315008058.shtml.
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application of these tools is only indirectly related to the CSCS, in that an irregularity identified 

using these technologies may lead to an inspection, which may in turn lead to a penalty, which 

would then appear in CSCS records as PCI. There is currently no known instance in which 

automated operational data collection leads to automated penalty issuance and CSCS record 

generation without human intervention. In other words, although technology and automation may 

be employed to detect violations or trigger inspection, regulatory action resulting in the issuance of 

a penalty or blacklisting is only conducted by humans within an agency.

CSCS data is also likely to play a role in China’s experimental smart city regulation 

platforms, such as the Alibaba-built Hangzhou “City Brain.” Sources indicate the City Brain may 

employ CSCS data to automate the determination of eligibility for government subsidies. Once 

such systems are complete, it is likely that companies with clean social credit records will receive 

immediate approval and funds will be released within minutes or hours of application.166

Additionally, 2019 Guiding Opinions call for the use of both big data and artificial 

intelligence specifically in relation to regulatory “early warning systems” like the Internet Plus 

initiative. As “the defining characteristic of big data is the capacity to search, aggregate, and crossreference large datasets for analysis to identify previously undetectable patterns,”167 it is likely 

that intended applications of these technologies center around the employment of AI algorithms 

against large datasets of PCI and MCI in order to unearth previously undiscovered patterns in 

the available metrics which might more narrowly identify which companies will be subject to 

greater regulatory attention, or point to impending market instability or consumer safety issues. 

However, there is currently no evidence to suggest that any highly advanced market or operational 

risk prediction models are in active use, and existing research on the issue has concluded that 

current implementation is “crude.”168

These systems are likely to become increasingly sophisticated as algorithms are upgraded, 

PCI data sharing becomes uniform across provinces, and MCI sources are further defined. As these 

technologies become ever more ubiquitous, issues such as algorithmic transparency — the relative 

ease or difficulty with which humans can understand the basis for decisions made by computers, as 

well as whether or not those algorithms “formalize and mask biases embedded in the data on which 

they are trained”169 — are likely to come to the fore over the next 10-20 years, particularly given 

divergent U.S. and Chinese values regarding data transparency.
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Section 8

Implementation Status

The CSCS is operational, that much is clear. CSCS files exist, they are being populated with 

PCI collected by government bodies across the country, national agencies and local governments 

are layering social credit into their regulatory processes by developing blacklists, redlists, grading 

systems, and pilot projects relevant to their sectors, as well as updating existing regulations to tie 

them into the CSCS. 

Still, assessing the exact degree to which the CSCS has been implemented has poses an 

intractable challenge. CSCS files exist, but for how many companies in China? They are being 

populated, but how accurately and reliably? CSCS policies exist, but with what degree of national 

coverage? This difficulty is partially due to the system’s enormous size and scope, its many 

moving parts, and the broad spectrum of public and private sector players involved. Nationwide 

implementation of the CSCS requires a complex amalgamation of policymaking, technical 

infrastructure deployment, government- and society-wide process adjustments, and inter-agency 

and inter-locality cooperation. 

More importantly, Beijing has never spelled out its end game for the CSCS, and it is 

impossible to assess progress made toward a goal that has not been defined. Concrete milestones 

or phases of implementation have not been officially identified in policy — either of the CSCS or 

the broader social credit system, but the Planning Outline does enumerate several vague targets 

that Beijing intends to meet by the end of 2020: 

By 2020, having essentially established systems of fundamental laws, regulations 

and standards for social credit; having essentially built a credit investigation 

system that covers the entire society credit on the foundation of sharing information 

resources, having essentially completed credit supervision and management 

systems, having a relatively complete credit services market system, and giving full 

play to mechanisms encouraging trustworthiness and punishing untrustworthiness. 

Making clear headway in the establishment of government affairs, commercial, and 

social creditworthiness and in judicial credibility, with a substantial rise in market 

and social satisfaction levels. Spreading stronger awareness of creditworthiness in 

the entire society, noticeably improving the economic and social development credit 

environment, and a significant improvement in the economic and social order.170

Though this obscure phrasing does not offer clues to Beijing’s long-term goals for the CSCS, 

it does indicate that the immediate objective is to make clear progress in laying the technical, legal, 

and inter-agency cooperative groundwork upon which the CSCS can take root. Thus, as outlined 

in Section 1, we assess that a “fully implemented” CSCS would be characterized by three features: 

seamless data aggregation, a standardized legal and policy foundation, and a well-defined penalty 

and reward ecosystem. 

8.1 Seamless data aggregation
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The foundational technologies that support the storage and transfer of PCI between 

government agencies and the central CSCS repository are largely in place, but the flow of data 

between state agencies and central CSCS files is currently patchy, and the rollout of data sharing 

infrastructure is erratic, due to inconsistent levels of CSCS implementation from agency to agency. 

From a technical perspective, the reliable transfer of data between various government 

bodies and central CSCS files required the establishment of a standardized social credit record 

identification system which would allow PCI — regardless of where and how it was generated 

— to be associated with the CSCS files of the corresponding company. As outlined in Section 3, 

the Unified Social Credit Identifier (USCI) system was established in 2015 to meet this need, and 

USCIs have now been assigned to most registered entities nationwide. As of end-2019, China 

recorded a total of 38.5 million domestically-registered enterprises (企业), nearly 100 percent of 

which had been issued a USCI, and an additional 82 million registered individual proprietorships 

(个体工商户), with a reported 71.5 percent covered by USCIs.171 Once a legal entity has been 

assigned a USCI, social credit data may be associated with that entity, and thus that entity’s social 

credit file can be considered established. As the majority of companies have received a USCI, this 

suggests that CSCS files have been established on the majority of registered entities in China.

The fidelity of the data stored within those files, however, is currently weak. Our analysis of 

the social credit records stored in ten standalone state agency credit databases, compared against the 

records displayed in the central CSCS files, showed significant gaps in accuracy and completeness. 

For example, though 89 percent of blacklist records issued by the General Administration of 

Customs (GAC) and State Taxation Administration (STA) appear in Credit China’s central CSCS 

records database, blacklist records from the Ministry of Housing and Urban Rural Development 

(MoHURD) are not currently included, and only approximately 25 percent of records from the 

Ministry of Transport and 20 percent of records from the Ministry of Industry and Information 

Technology are included. We found that data completeness between other agencies ranged 

from 10 to 90 percent, indicating that large gaps still exist in inter-agency data transfer. Chinese 

policymakers are aware of these deficiencies, as the notice accompanying the release of the 2019 

PCI Catalog noted: 

...there are still problems such as the absence of important credit records, a lack of 

timeliness [in data transfer], [issues with the] integrity of information, and there is 

a large gap between the overall information collected and the demand for diverse 

and high-quality information from government regulators.172 

At the local level, implementation of CSCS data storage infrastructure is equally nonuniform. Shanghai is a leading locality in terms of infrastructure buildout. As of end-2018, the 

Shanghai urban credit database had centralized earmarked data from 88 local government bodies 

and included a reported 11.3 million records on enterprises.173 Other large metropolitan areas, such 

as Shenzhen and Nanjing, have similarly advanced programs, still others have built databases but 

not yet implemented them fully, and many small city governments have not yet deployed even 

foundational data collection infrastructure.174

As the scope of MCI has not yet been defined, assessing the status of its aggregation is not 
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yet possible, but it is safe to say that MCI aggregation lags significantly behind PCI. 

8.2 Standardized policy and legal foundation

At the national level, the basic principles that govern the CSCS — data aggregation, 

blacklists and redlists, Unified Rewards and Punishments — have been broadly established in 

policy, but several critical facets of the system are still undergoing standardization. These include 

solidifying the legal basis for Unified Punishments, standardizing the procedures for blacklisting, 

and standardizing the procedures for credit repair. 

These standardizations are necessary because China’s typical policymaking process, 

under which the central government sets policy direction and strategy while leaving the practical 

details of implementation up to local governments, has proved problematic when applied to the 

CSCS, an initiative which due to its cooperative inter-agency nature requires a high degree of 

top-down coordination. The discretionary power relegated to local governments has resulted in 

non-uniform applications of CSCS blacklists and penalties at the local level. In some cases, local 

regulators have abruptly leveraged the CSCS or developed new blacklists to clamp down on issues 

of immediate concern. This phenomenon was particularly evident during the early days of the 

COVID-19 outbreak in China, as city governments scrambled to enforce compliance with new virus 

containment and work resumption regulations. On February 17, 2020, the city of Xiamen released 

regulations stating that companies found engaging in price hikes, hoarding, making unreasonable 

profits from the epidemic, or manufacturing and selling products such as fake and shoddy masks, 

would be penalized under the CSCS.175 In other instances, local officials attempted to leverage 

the citizen social credit system to blacklist individuals for legal acts perceived as disruptive, such 

as “malicious and frequent job-hopping,” resulting in well-publicized scandals and significant 

public attention, and occasionally requiring central government intervention. 25 Such fluidity and 

confusion has given rise to domestic criticism, with members of the legal community expressing 

concerns that the system would benefit from greater central policy standardization.176 It appears 

Beijing is scaling back the discretionary power relegated to localities regarding these aspects of 

the CSCS, and there are now indications that the central government intends to impose a greater 

degree of top-down coordination moving forward.177

Additionally, in November 2019, the NDRC hosted a social credit legislation symposium 

where key policymakers called for research to support the drafting of a national social credit 

law.178 The timeline for the release of this law is unclear. The Standing Committee of the National 

People’s Congress 2018-2023 legislative agenda includes social credit as one of 108 areas requiring 

legislative attention, but it is not listed among the top national legislative priorities.179 Though little 

is known about this legislation, it is expected that the law will more clearly define the obligations 

of citizens, companies, and governments under the CSCS, and may lay clearer groundwork for the 

25 In April 2019, the deputy director of the Department of Human Resources and Social Security in Zhejiang 

Province announced plans to use the SCS to penalize “malicious, frequent job-hoppers.” The announcement lead to 

public outcry, as Chinese labor law grants workers the right of contract cancellation. No blacklist was established 

and the issue was dropped, but the incident underscored the widespread mis-readings and attempted misapplications 

of SCS law at the local level and highlights one of Beijing’s motivations for increasing top-down control of the 

system. 爆笑基地: 专家建议频繁跳槽纳入征信黑名单,网友:怒了! http://dy.163.com/v2/article/detail/EC94JP7I05496II9.html
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establishment of blacklists.

At the local level, though the majority of China’s provincial-level authorities have taken at 

least minor steps toward implementing regional SCS policies in their jurisdictions, timelines for 

rollout are widely divergent, and the scope of such policies varies. As of June 2020, 14 provinces 

have finalized or drafted regulations governing the management and collection of PCI; nine have 

released or drafted broader social credit regulations codifying data collection, Unified Rewards and 

Punishments, credit repair, and credit information security for the province; six have announced 

that drafts are in the planning stage; and seven provinces have made no announcement (see full 

table in Appendix IV). 

Areas that embraced SCS participation early on are unsurprisingly further along than those 

that began later. Shanghai, a frontrunner in local SCS implementation due to participation in early 

urban SCS pilot programs,26 was collecting enterprise credit information in the Shanghai Free 

Trade Zone as early as 2014,180 and released its local regulations in 2017.181 In contrast, Jiangsu 

province only released a working draft of its provincial regulations at the end of April 2020.182

Implementation status in other provinces varies widely, with some having made no announcement 

regarding the status of provincial regulations, others having announced the impending release of 

drafts, and still others having already issued a series of related ordinances. It is expected that all 

provinces will have released provincial social credit regulations by 2023. 

8.3 Well-defined penalty and reward ecosystem

A mature social credit system would require a stable and predictable blacklist and redlist 

ecosystem, with streamlined, well-established processes for the application of CSCS penalties and 

awards, with clearly defined roles for various market actors in the application of Unified Rewards 

and Punishments.

The number of national blacklists has remained largely stable over the last two years, with 

the rate of new blacklist and MOU releases slowing to a trickle since 2018. However, several new 

blacklists are currently under development.27 It is likely that the blacklisting and redlisting system 

will slowly broaden throughout various sectors over the next decade as new lists are trialed and 

incorporated into the national framework.

26 Shanghai was among the first regions to undertake regional implementation pilots, with initiatives launched as 

early as 2002-2003. “Press Conference of the Municipal Government: Shanghai’s Social Credit System is Taking 

Shape” (市政府新闻发布会:上海社会信用制度已具雏形), Sina News, August 2003. Translation. http://news.sina.

com.cn/c/2003-07-30/1433472956s.shtml.

27 Examples: State Council of the People’s Republic of China, Opinions of the State Council on Establishing a 

Rehabilitation and Assistance System for Disabled Children (国务院关于建立残疾儿童康复救助制度的意见), 

June 21, 2018. Translation. http://webcache.googleusercontent.com/search?q=cache:xs_s_WdlPfAJ:www.gov.cn/

zhengce/content/2018-07/10/content_5305296.htm+&cd=1&hl=en&ct=clnk&gl=ph; General Office of the Ministry 

of Education of the People’s Republic of China, Main Points of the 2019 Inter-ministerial Joint Meeting on Private 

Education (民办教育工作部际联席会议2019年工作要点), April 9, 2019. Translation. http://webcache.googleusercontent.com/search?q=cache:TrQV5AX_DCoJ:www.gov.cn/xinwen/2019-04/09/content_5380749.htm+&cd=1&hl=en&ct=clnk&gl=ph.
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As described in Section 4.3, China is currently examining the boundaries of how far the 

CSCS can percolate into the private sector, and under what circumstances industry actors may 

participate in the issuance of penalties and rewards. Thus, the CSCS’s integration into wider 

industry is in an exploratory stage and remains relatively immature. 

If we consider that a “fully implemented” CSCS would be characterized these three elements 

reaching relative maturity and stability, it is safe to say that the CSCS is still in a foundational stage. 

However, there is no date at which the system will be suddenly “switched on.” Rather, the CSCS 

is already operational, and will be incrementally expanded as various public and private sector 

actors increasingly install infrastructure, ramp up policy participation, and solidify cooperative 

agreements over the next decade.
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Section 9

Compliance and Competition

Unified Rewards and Punishments has emerged as one of the most alarming aspects of 

the CSCS for foreign firms operating in China, particularly the possibility that a single incident 

of blacklisting could result in an avalanche of cascading consequences that hamper — or even 

halt — business activity. This risk is real for all companies in China, not only foreign firms, but 

the risk becomes greater if blacklists are unfairly or unevenly applied to non-Chinese companies. 

Given China’s recent history of mis- or over-application of various regulations and laws to foreign 

firms,183 the question of whether or not the CSCS will be unfairly leveraged to place pressure on U.S. 

companies deserves thorough exploration. This section will examine the pitfalls and compliance 

burdens that the CSCS presents to all companies with operations in China, as well whether or not 

the CSCS has been — or might be — applied unequally to foreign firms.

9.1 Equality of application

As this report has outlined, the CSCS was conceived to address domestic market and 

regulatory weaknesses arising from an inherent lack of trust among market actors, which has led 

to rampant fraud and malfeasance and held back economic efficiency in China in recent decades. 

Given that foreign-invested companies account for less than 3 percent of all companies in China,184

the CSCS primarily targets Chinese companies and seeks to address long-term issues surrounding 

their poor regulatory compliance among domestic firms. 

As of July 2020, we find that there is nothing within current CSCS-related policy that 

explicitly disfavors foreign or U.S. companies or favors Chinese companies. Further we find 

that the realities of its current implementation do not appear to directly disfavor foreign firms or 

advantage Chinese firms. 

A review of the CSCS files of 51 U.S. multinationals operating in China found that 44 had 

been redlisted for tax compliance and were entitled to Unified Rewards.28 This included Google185

and FedEx,186 both of which have been involved in high-profile political disputes with China in 

recent years.187 Neither are Chinese state-owned enterprises (SOEs) immune from blacklisting. A 

filtered public records search29 showed that 1,391 national and local SOEs had been placed on the 

Supreme People’s Court blacklist of legal defaulters for failure to honor court-ordered judgements, 

making them subject to Unified Punishments. Blacklisted SOEs with the highest registered capital 

included Tianjin Binhai New Area State-Owned Commercial Investment Group,188 Sichuan Coal 

Industry Group,189 Shenyang Hunnan Water Group,190 and Yinchuan Cultural Tourism Investment 

Group.191

28 Social credit records review conducted by Trivium China on 51 U.S. multinational companies via the Credit 

China public CSCS records search tool, which indicates whether or not a company is eligible for Unified Rewards 

or Unified Punishments, and enumerates the redlists, blacklists, and penalties companies have received. http://webcache.googleusercontent.com/search?q=cache:http://www.creditchina.gov.cn.

29 Public records found using advanced search options on corporate due diligence portal Qichacha, an official 

CSCS social credit data partner. Company records may be simultaneously filtered by enterprise type, including StateOwned Enterprises (国企), and court default records (失信信息). 
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Furthermore, policymakers have taken steps to ensure the CSCS is applied equally to foreign 

and domestic companies. In November 2019, the Ministry of Commerce announced its intention 

to create a “foreign investor integrity file system” and a special blacklist for foreign investors.192

However, this idea was subsequently abandoned, and final regulations contain no separate foreign 

investor blacklist — all companies are currently subject to the same set of blacklists, regardless of 

whether investors are foreign or domestic.193

In the foreign business community in China, while the level of concern around CSCS 

compliance is certainly elevated, we have heard no complaint that the CSCS systematically puts 

foreign companies at a disadvantage, and we have not yet encountered any specific case in which 

foreign companies have received disproportionate scrutiny under the CSCS. The general view 

among the U.S. businesses we interviewed is that the CSCS will increase the compliance burden 

on all companies operating in China, including foreign companies. Optimistically, some U.S. 

executives expect compliance burdens to initially be higher for Chinese companies, potentially 

benefitting foreign companies in the short term as regulators focus attention on the least-compliant 

firms first. These views have been supported by conversations with executives at approximately 60 

foreign businesses operating in China over the past year, and were corroborated by the AmCham 

China 2020 Business Climate Survey Report, in which 42 percent of member companies viewed 

the emergence of the CSCS as a positive development, 31 percent responded that there was not yet 

enough available information to accurately assess risks, 19 percent viewed the CSCS as inherently 

neither negative nor positive, and just eight percent viewed it as a negative development due to 

either potential for abuse or for other reasons.194

As it appears the CSCS is currently being applied with relative equality to foreign and 

Chinese firms, the question becomes whether or not this will remain the case. The CSCS is being 

developed and implemented against a backdrop of concerted ideological tightening and rising 

information control within China, as well as a deteriorating U.S.-China relationship, and it must 

therefore be viewed within this context. Additionally, a pattern of regulatory abuse and an unlevel 

playing field for U.S. and other foreign companies operating in China is also well documented.195

Thus, though the stated intention of the CSCS is to increase compliance and thereby improve the 

consistency of regulatory enforcement for all commercial entities operating in China regardless of 

ownership, the poor performance of Chinese regulators in this capacity means that U.S. firms must 

remain alert on this front. 

9.2 Increased vulnerability to corruption and bias: the human factor

As we have seen throughout this report, CSCS files are the unifying component of the 

CSCS, and the records they contain will feed into a wide variety of applications. They will feed 

into consumer advocacy and corporate due-diligence apps, they will appear on credit reports, they 

will be imported into big data platforms that determine the degree of regulatory scrutiny companies 

receive, and they will be a key metric in PCI-based grading systems. Given the central importance 

and intended ubiquity of CSCS files, each record those files contain — specifically penalty records 

and blacklist or redlist records — will carry greater weight. Thus, the fairness and accuracy with 

which those records are generated and input is of paramount importance. 

As we have also seen in Sections 4 and 7 of this report, the penalty and blacklist records 
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included in CSCS files are not generated on an automated basis — they result from inspections 

and judgements carried out by human beings, and inspectors still possess considerable discretion 

in terms of what is and is not pursued.30 This vagueness around the specific thresholds that may 

induce regulatory action are an intrinsic feature to much of Chinese regulatory policy, and owes 

in large part to China’s under-developed legal system and preference for retaining regulatory 

discretion.196 The fact remains, if inspections are unfairly conducted, or regulators are determined 

to find fault, the biased resulting data may damage a company’s corporate credit standing. Thus, if 

the CSCS was to be leveraged against U.S. companies in the future, this is the most likely channel 

through which it could happen. 

In the event of increased bilateral trade tensions between the U.S. and China, or simply due 

to generalized corruption or bias among local government officials, it is conceivable that regulators 

may be less forgiving during inspections of U.S. firms and issue more frequent or harsher penalties 

to them. This could be done irrespective of the CSCS, but due to the broader impact that penalty 

records will have under the CSCS, unfair penalty issuance and blacklisting therefore becomes a 

bigger threat. 

That said, as part of broader efforts to crack down on domestic corruption, the Chinese 

government is attempting to limit the human factor through the implementation of a “Double 

Random, One Transparency” inspection system (双随机、一公开) in all regulatory agencies 

nationwide.197 Under this system, the company to be inspected and the inspector are randomly 

paired, and the results of the inspection are disclosed to the public. Theoretically, this could limit 

regulatory bias, but its efficacy is highly reliant on the deployment of neutral platforms and tools 

that facilitate random selection of inspection targets, and to date, our discussions with Chinese 

regulators themselves indicate that such systems have not been widely implemented.31 Thus, in 

practice, regulatory bodies have more power to choose their inspection targets than policy indicates. 

9.3 Increased risks to — and from — key personnel

Due to the connection between the CSCS files of the organization and the CSCS files of its 

senior staff, key personnel may be held personally liable for the actions of the company, whether or 

not they were involved in the malfeasance. Ostensibly, the intention is to prevent parties engaged in 

unethical business practices from simply closing up shop, starting another venture, and re-offending. 

However, this “attempt of pierce the corporate veil”198 potentially opens up foreign management 

and investors — some of whom may be based outside of China and have no knowledge of or 

involvement in illegal activity — to significant personal risk. As noted by one social credit scholar, 

“[t]his might delight those who think corporate leadership often escapes responsibility too easily, 

but won’t necessarily help enforce judgments if those affected lack authority to [take rectifying 

action] on behalf of the corporation.”199

30 Example: the Measures of the General Administration of Customs of the People’s Republic of China on Enterprise Credit Management, which outlines the violations that will result in inclusion on the GAC blacklist, includes as 

a violation “other circumstances as prescribed by the GAC.” The majority of blacklists include similar open-ended 

statements. 

31 Based on interviews conducted by Trivium China with Chinese government source.
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Additionally, due to the extension of the broader social credit system to individuals, 

companies themselves are increasingly vulnerable to the personal blacklist status of key personnel. 

Though there are no known regulations explicitly stating that companies will be sanctioned if key 

personnel are blacklisted for personal reasons, interviews with multinationals operating in China 

revealed that one U.S. enterprise was restricted from participating in a large trade expo due to the 

blacklisting of senior staff for legal violations unrelated to the company.32 Not only does this leave 

companies vulnerable to unlawful behavior by their employees, it is also possible that pressure 

could be indirectly applied to a U.S. company via the unfair blacklisting of its personnel.

9.4 More risk for companies with larger presence?

The CSCS’s top-down, holistic approach to both penalties and data collection has the 

potential to disfavor companies with a more significant presence in China, particularly those with a 

large number of branches or stores. More registered entities mean a larger number of social credit 

files within a single parent company’s overall CSCS profile, and therefore an increased number of 

vectors through which problems can arise. 

However, how much a disadvantage this will present is still unclear. The precise relationship 

between the social credit files of registered entities and their parent company is undergoing review, 

and exactly how the blacklisting of entities under a parent company’s umbrella might impact other 

subsidiaries or the parent company itself appears to vary depending on the regulator and blacklist. 

In July 2019, for example, SAMR released a draft CSCS policy targeting the food and beverage 

sector,33 stating that chains would be blacklisted if five or more outlets received administrative 

penalties from local branches of the administration within a single year.200 Under this draft policy, if 

five branches of a national fast food restaurant chain each received a single penalty for food safety 

violations in a given year, the parent company would be placed on a blacklist, potentially affecting 

operations nationwide. Due to pushback from the foreign business community, the finalization of 

this policy has been put on hold, and the final shape these rules will take remains undecided. It is 

also unclear whether other blacklist-controlling agencies will create their own rules in this regard, 

or if — given the general trend towards top-down CSCS standardization — the central government 

will step in and clarify. 

9.5 Cross-contamination

There is one known channel through which the social credit of a company’s business partners 

or suppliers may impact the company itself. While the CSCS files of a company and its suppliers 

are not officially linked the CSCS, when a company bids for a government procurement project 

in partnership with another company, or is required to list its suppliers on bidding documents, 

or otherwise jointly submits other applications to government bodies in cooperation with third 

parties, the social credit profiles of all listed companies and vendors may be reviewed, impacting 

32 Based on conversations held between Trivium China analysts and executives at one U.S. technology firm. 

33 Food safety has been a consistent source of both public and regulatory concern over the last two decades, and 

high-profile food safety issues such as the 2008 melamine-contaminated baby formula scandal, the 2010 and 2014 

“gutter oil” scandals, and the 2019 African Swine Fever outbreak have severely damaged consumer trust in regulators and domestic food products. 
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the success or failure of such bids and applications.201 Other than this, there is currently no known 

channel through which the social credit standing of a company would be impacted by the social 

credit of its business partners, suppliers, contractors, or customers. 

9.6 Data collection and disclosure

CSCS policy expressly states that corporate trade secrets will be protected from publication 

in CSCS files. Indeed, no single item of PCI contained in public-facing CSCS databases is highly 

sensitive, and we have not encountered any examples of foreign companies lodging protest against 

the nature of information made available via CSCS files. On the contrary, several U.S. firms 

interviewed were hopeful that the public availability of CSCS files could enhance the effectiveness 

of due diligence and background checks on potential Chinese business partners and suppliers. 

However, this transparency is a two-way street, and while no individual piece of PCI is overly 

revealing, the ready availability of CSCS files do allow competitors — as well as the media — to 

conveniently formulate a comprehensive overview of any company’s compliance status.

Additionally, though data privacy has been identified as a priority by CSCS policymakers,202

China tends to conceptualize “data privacy” as the protection of networks from unauthorized private 

agents — such as hackers, competitors, app developers, and third party agents — rather than the 

protection of the data subject’s rights in relation to the state.203 Thus it should come as no surprise 

that, though there are mechanisms through which companies may object to the erroneous inclusion 

of certain records in their CSCS files, there are currently no provisions under which companies or 

individuals can object to the sharing of CSCS data between agencies.204

The CSCS itself does not change data reporting requirements for companies based in 

China, but violations related to non-compliance with data disclosure are now recorded under the 

CSCS. Examples include failure to follow new regulations released in December 2019 by the 

State Administration for Market Regulation and the Ministry of Commerce requiring all foreigninvested enterprises (FIEs) to submit annual investment reports on their foreign investors and 

actual controllers,205 which for investors includes the amount and percentage of equity stake, as 

well as whether a Fortune 500 company is involved in investment; for actual controllers, this 

includes whether the controller is an individual, company or government organization, as well as 

direct powers the controller holds through 50 percent or greater financial investment, or indirect 

powers the controller holds through authority to appoint board members, authority to significantly 

influence board decisions, or through authority over key contracts, trusts or technologies.34 Foreign 

companies and investors will face penalties if they neglect their reporting obligations or falsify 

information. Penalties will be made public through the Ministry of Commerce’s FIE Investment 

Information Reporting System, and “credit administration will be undertaken as per social credit 

regulations.”206

9.7 Implicit pressure to submit to unfair penalties

34 See foreign investor reporting form attached to: Ministry of Commerce, “Announcement on Matters Related 

to Foreign Investment Information Reporting” (关于外商投资信息报告有关事项的公告), December 31, 2019. 

Translation. http://webcache.googleusercontent.com/search?q=cache:I_cQnEWfNJMJ:www.mofcom.gov.cn/article/b/c/201912/20191202927046.shtml+&cd=1&hl=en&ct=clnk&gl=ph.
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As fulfillment of obligations and payment of fines must be completed before companies 

can apply for delisting of negative records, some companies may find it easier to forgo prolonged 

challenges to the government’s legal and administrative decisions and pay penalties, even if they 

are unfair, to minimize the reputational damage and operational restrictions caused by blacklist 

inclusion. This could be true even though companies are granted time to object to blacklist inclusion. 

In practice, objecting to or appealing administrative decisions can come with political risk and is 

already a cumbersome and fraught process for foreign companies, who must weigh the benefits of 

attempting to dispute against the costs of a potential backlash. 

9.8 Confusion due to decentralized rollout

Spot polls conducted in chamber and association meetings have indicated that the piecemeal 

nature of CSCS rollout has left foreign firms unsure of when and how to best prepare for compliance, 

and where to focus preparatory efforts.35 Additionally, uneven policy rollout at the local level has 

resulted in inefficient bureaucratic procedures, which is increasingly problematic given the higher 

stakes of penalty incurrence under the CSCS. Under the CSCS, timely penalty rectification is of 

the essence, and CSCS issues arising from slow reporting both on the regulatory end and internally 

was a recurring theme among interviewed businesses, particularly in cases where the compliance 

team is located in a province other than the penalized branch office or subsidiary. Two foreign 

multinationals reported in interviews that the company had not been made aware of penalties 

until after the deadline for appeal had expired. Companies must allocate resources to actively 

monitoring penalty issuance and restructuring reporting channels so that penalties received by any 

branch office or legal entity are swiftly addressed.

9.9 Sector-specific dangers

The CSCS was not designed to target certain industries, but the Chinese government does 

have sectors it wants the system to prioritize.207 Consequently, any companies in those sectors 

will be more closely scrutinized, including U.S. firms. These sectors include food and beverage, 

pharmaceuticals, child and senior care, tourism, finance, healthcare services, construction, and 

high-polluting industries. The rationale is to focus on sectors that are perceived to have significant 

negative externalities and can do the most damage to public health and wellbeing if product or 

service quality fails to meet regulatory standards. Severely non-compliant companies in these 

sectors may see the harshest penalties applied, including permanent bans on market access.208

35 Based on confidential interviews and polls conducted in Beijing by Trivium China with executives at U.S. and 

foreign multinationals.
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Section 10

Geopolitics and Future Risk

To date, the primary concern surrounding the CSCS on the international stage has been the 

system’s potential to be weaponized against foreign companies, particularly in light of the continuing 

deterioration of the U.S.-China relationship. However, at this time, neither the official rhetoric 

surrounding the CSCS, the design of the system, nor the feedback from foreign multinationals 

operating in China provide sufficient evidence to indicate that the CSCS is currently being applied 

unfairly against foreign firms. Though not outside the realm of future possibility, given the current 

lack of evidence to support this as a use case for the CSCS, we assess that the more immediate 

geopolitical risks are of a different nature. These center around its potential to contribute to the 

erosion of the U.S.’ leading position internationally in relation to data management, access, and 

standards, as well as the leading position of U.S. firms in financial enterprise and sovereign credit 

ratings. We detail these and other risks in the sections below. 

10.1 Coercing behavior from foreign companies

The CSCS increases China’s ability to enforce policies which conflict with U.S. social and 

corporate values, such as online censorship regulations and the One China Principle. Impending 

regulations, such as the draft of the Cyberspace Administration of China’s Administrative 

Measures for the Management of Seriously Dishonest Internet Information Services36 stipulates 

that internet companies will be blacklisted if their operational license has been canceled due to 

illegal activities or failure to abide by cyberspace regulations, or if they are found to be spreading 

information that “severely disrupts the order of cyberspace communications, damages the public 

interest and the legitimate rights of the people, and causes negative social impacts.”209

One often-cited incident of such a clash has already caused concern. In 2018, the Civil 

Aviation Administration of China issued a letter threatening to blacklist 44 international airlines 

if they continued to list Taiwan separately from China on their international websites.210 This 

example underscores that blacklisting could be threatened against companies that violate Chinese 

regulations, even when such violations occur outside of China’s jurisdiction. Such demands place 

companies in a difficult position, intensifying the pressure to adhere to Chinese regulatory requirements 

that may conflict with their own values, and also with the values of their customers overseas — or 

potentially even with U.S. policies or broader U.S. interests.

However, it must be pointed out that the core disagreement in such instances is with the 

underlying laws and regulations that the CSCS is designed to enforce, not with the CSCS itself.211

These conflicts existed long before the arrival of the CSCS, and will continue to exist regardless 

of whether and how it is applied. The question is whether or not the CSCS makes the enforcement 

of objectionable laws more efficient by streamlining and instrumentalizing China’s opposition to 

foreign entities it perceives as not sufficiently abiding by its regulations. Additionally, its existence 

and the severity of potential ramifications of blacklist inclusion domestically may subtly encourage 

international companies with operations in China to hew to Beijing’s preferred behavior and 

36 As of July 2020, the Administrative Measures for the Management of Seriously Dishonest Internet Information 

Services has not been officially promulgated.
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narratives, increasingly self-censoring in order to avoid seeing their China-registered entities come 

under CSCS-backed pressure. 

10.2 Enhancing China’s influence over domestic companies abroad

The CSCS gives China a direct channel through which to tighten its grip on the behavior 

and actions of Chinese entities operating overseas. 

This feature of the CSCS is perhaps most apparent through a blacklist controlled by the 

Ministry of Foreign Affairs which targets Chinese companies involved in international economic 

infrastructure, finance, manufacturing, or other Belt and Road projects. The blacklist is aimed at 

companies which “violate relevant domestic laws and regulations or those of cooperating countries, 

or violate international conventions or the United Nations Resolutions, disrupting the stability of 

[China’s] foreign economic cooperation, causing serious adverse effects on the implementation of 

the Belt and Road, and endangering the reputation and interests of [China].” 212 This blacklist can 

be contextualized against a backdrop of international backlash against corrupt and poorly managed 

Belt and Road projects, under which “inadequate enforcement and poor business practices are 

turning the BRI into a global trail of trouble.” 213

CSCS-related language has also appeared in the newly revised draft of China’s controversial 

Export Control Law, which now includes a provision indicating that violations of export control 

regulations will be included in the violator’s CSCS file.214 The inclusion of this provision is not 

peculiar in itself. Hundreds of Chinese market regulations are currently being updated with similar 

provisions, which are little more than administrative formalities that roll various rules under the 

CSCS enforcement umbrella. However, the inclusion of this provision may allow Beijing to hold 

its domestic companies on a tighter leash in overseas markets, particularly during international 

sales and acquisitions. 

10.3 Tightening Party control over local governments

The central government has long struggled to effectively keep local government priorities 

aligned with Party goals. One prime example is the Party’s efforts over the years to reduce 

overcapacity — notably in steel and cement production. Such efforts met with fierce resistance 

from local leadership:

While the national government sought to rationalize industries and to create 

an efficient national economy, local governments gave priority to employment, 

GDP growth and maximizing their revenues, a large portion of which come from 

business taxes. This has led many local governments to encourage investment in 

new capacity, in contravention of national policies. Where Beijing has tried to force 

the closure of firms, be it for violating environmental regulations, having outdated 

production equipment, or other reasons, local authorities have often helped the 

firms to continue producing in defiance of instructions from the capital. Central 

government bureaucrats are not unaware of the problem, but they often lack the 

resources to force compliance. 215
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The CSCS may provide the Party with just such a resource, through two potential channels. 

First, due to the national, cross-sector nature of Unified Rewards and Punishments, central leaders 

may not depend as heavily on local regulators to implement policy and enforce regulations, but can 

instead apply pressure through blacklisting by any agency and allow the CSCS penalty framework 

to kick in, effectively restricting market access to companies it wishes to disadvantage. Secondly, 

analysis of CSCS data via the National Urban Credit Situation Monitoring System (全国城市信用

状况监测系统)216 can be employed to give central leadership a top-down view of which regions 

are least compliant with central key performance indicators. This should help Beijing to root out 

insubordinate or ineffective local authorities unwilling or unable to bring their jurisdictions into 

line with central mandates. 

10.4 The power of data centralization

China’s push towards the rapid, large-scale consolidation of government data, of which the 

CSCS is a part, has the potential to enhance the bureaucratic efficiency, predictive capacity, and 

regulatory responsiveness of the Chinese state,217 which could in turn enhance Party legitimacy and 

control in China and in other countries. 

Historian Yuval Harari argues “free market capitalism and state-controlled communism 

aren’t competing ideologies, ethical creeds, or political institutions. At bottom, they are competing 

data-processing systems. Capitalism uses distributed processing, whereas communism relies on 

centralized processing.”218 While this characterization may be reductive, it does neatly encapsulate 

the divergent approaches to algorithmic regulation taken by China and the United States. 

Employing AI and big data to inform regulatory decision making is not unique to China or 

the CSCS. In the report Government by Algorithm: Artificial Intelligence in Federal Administrative 

Agencies released in February 2020 by a team at Stanford University, researchers found that 45 

percent of U.S. federal agencies have experimented with AI in capacities quite similar to CSCS 

data-based initiatives such as Internet Plus:219

AI tools are already improving agency operations across the full range of 

governance tasks, including enforcing regulatory mandates centered on market 

efficiency, workplace safety, health care, and environmental protection; adjudicating 

government benefits and privileges, from disability benefits to intellectual property 

rights; monitoring and analyzing risks to public health and safety; extracting 

useable information from the government’s massive data streams, from consumer 

complaints to weather patterns; and Communicating with the public about its rights 

and obligations as welfare beneficiaries, taxpayers, asylum seekers, and business 

owners.

Where U.S. algorithmic regulation projects differ from their Chinese counterparts is in 

the scope of data available to them. Without a nationally centralized regulatory dataset, U.S. 

federal agencies are generally limited to leveraging their own internally collected data or that in 

the public domain. By contrast, the centralization of PCI and MCI under the CSCS — and the 

broader government extranet — places a vast body of cross-sector data resources in the hands of 
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China’s state agencies. Moreover, the establishment and expansion of infrastructure and networks 

through which national social credit data can be shared and centralized, such as the NCISP, lays the 

technical groundwork for the rapid expansion of other national data aggregation projects.

Though we do not suggest that the U.S. should centralize government records in the 

same manner that China has done, it has been well-established that government performance and 

administrative competence are critical to the legitimacy of any state,220 and in the age of big data, 

competence and performance are highly dependent on both the amount of data available, and the 

efficiency, efficacy, and innovation with which the state manages and deploys its data resources. 

Thus, we do argue that failure to develop a sophisticated and efficient data-driven governance 

model based on democratic values and underpinned by a strong data privacy regime may result in 

a vacuum which, by default, validates “the idea that authoritarian political systems are not only 

legitimate but can outperform Western democracies.”221

Such outperformance may come in the form of greater accuracy of insights and predictions 

generated through the use of these tools, higher efficiency of policymaking based on such insights, 

and increased capacity to effectively influence corporate behavior on a national scale. Additionally, 

assuming increased bureaucratic efficiency leads to increased predictability in decision-making, 

as well as consistent and predictable application of the law, there could be economic benefits for 

Beijing as well: the CSCS may increase private sector trust in the stability of China’s markets, 

which would likely result in an influx of foreign portfolio and direct investment. 

However, these potential long-term benefits are predicated on the assumption that Beijing’s 

ultimate vision for data connectivity is realized. Significant roadblocks exist, not least of which are 

the technical challenges that accompany the deployment of a decentralized infrastructure project of 

such ambitious scale and scope. The decentralized nature of PCI collection poses another problem 

for data quality and integrity, as the sources of such data are so numerous and varied. Inter-agency 

resistance to data sharing and conflicting interests and motivations among local governments may 

also hinder the project’s momentum.222

10.5 Exporting the CSCS: a challenge to Western financial credit models?

Although there is currently no specific state directive calling for the export of the CSCS, the 

geopolitical benefits of taking the broader social credit system into the international space have been 

suggested by various Chinese thought leaders, in pieces such as Credit of Great Powers: Global 

Vision of China’s Social Credit System,223 a 2017 publication by NDRC International Cooperation 

Center member Wu Weihai. Publications like this indicate that at least some theoretical discussion 

regarding the internationalization of social credit has taken place among technocrats and experts. 

In particular, Wu underscores that not only should China use the CSCS to improve corporate 

trustworthiness and integrity domestically to “win the high praise ... and the trust of industrial 

partners and to achieve strategic cooperation and commodity exchange,” but also that “under the 

all-round opening up of international competition, [control over] credit standards ... is also an 

important area of competition between countries, and is a manifestation of national soft power.”224

In advocating the internationalization of social credit, Wu specifically refers to the CSCS 
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in the context of financial risk assessment, rather than as a tool for corporate regulation. However, 

though Wu champions the theoretical export of the system, his work is highly idealistic, and lacks a 

concrete vision for how the CSCS could feasibly be translated to financial markets outside China’s 

borders. Neither does he clearly indicate whether this vision extends to individual credit ratings, 

corporate credit ratings, or sovereign credit ratings. 

More broadly, Chinese policy thinkers are well aware of the economic benefits inherent 

in becoming a global credit rating authority. A 2018 report from the China Economic and Social 

Council states: 

[C]redit rating is an important force in maintaining national financial sovereignty 

and economic security and represents a country’s position in the international 

financial service system.... Mastering the right to issue a credit rating means 

mastering global information dominance and capital allocation rights. The level of 

a rating directly affects the cost and interest rate of the country or enterprise under 

review for overseas financing. 225

It is equally clear that there are strong voices within the Chinese government who feel 

that the internationally-accepted U.S.-dominated enterprise and sovereign credit rating models, 

particularly those used by the “Big Three” (S&P Global Ratings, Moody’s Investors Service, and 

Fitch Ratings), are biased toward Western countries226 and are ill suited to the Chinese context.

Critics of the Big Three include former finance minister Lou Jiwei and former PBOC governor 

Zhou Xiaochuan, who “stressed the need for Chinese financial institutions to reduce reliance on 

credit ratings from U.S.-based” CRAs.227 As Samantha Hoffman, analyst at the Australian Strategic 

Policy Institute, notes: 

Moody’s Investors Service, Standard & Poor’s and Fitch Ratings [are] seen as 

potential threats to China. One article claimed that the agencies can ‘destroy a 

nation by downgrading their credit score, utilising the shock power of “economic 

nukes”’. Another article tied the problem to the One Belt, One Road scheme ..., 

because participant countries accept the current international ratings system. 

For the CCP, the solution is to increase the ‘discourse power [that China’s] 

credit agencies possess on the international credit evaluation stage.’ China’s SCS 

provides an alternative to the existing international credit ratings system. It does 

some similar things to the existing system but is designed to give the Chinese state 

a more powerful voice in global governance. 228

The dominant position of the U.S. dollar and U.S. control over global financial systems 

have long preoccupied Beijing. China’s concerns over financial sovereignty have led to at least 

one attempt to establish a financial credit ratings body to challenge the U.S. incumbents. In 2012, a 

consortium led by state-backed credit rating agencies from China and Russia, as well as one private 

U.S. firm, collaborated to form the Hong Kong-based Universal Credit Ratings Group,229 formed 

under the premise that the Big Three have been systematically biased against emerging economies 

while favoring U.S. and EU-based clients.230
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This approach falls in line with one major thrust of Beijing’s overall geopolitical strategy, 

which has involved identifying areas where Chinese policymakers believe that U.S.-led international 

organizations or standards systems either marginalize developing economies or struggle to meet 

the needs of emerging economic models. Beijing then moves to establish parallel China-led 

organizations and standards systems that address these gaps while simultaneously favoring China.231

Seen from this angle, the establishment of a Chinese-led international credit rating agency, based 

on social credit theory, could present a unique challenge to incumbent Western models. 

The Universal Credit Ratings Group project appears to now be defunct, with no significant 

movement since 2016. The group never released its international ratings, and the project failed 

partly due to under-investment — leading to an inability to create a robust ratings matrix that was 

granular and reliable enough to challenge the Big Three.37 Still, China’s internal efforts to develop 

its domestic credit ratings industry, and improve the quality of its ratings by leveraging CSCS data, 

is ongoing, and another push towards establishing a China-led international credit rating authority 

would come as no surprise.

It is too early to assess whether the CSCS could reliably be expanded to create the foundation 

for a potential alternative to Western financial credit ratings in any capacity — and if so, how 

PCI or MCI would be collected internationally and what role such data would play in ratings. 

However, the domestic discourse surrounding social credit draws clear links between the two, and 

observers are left to imagine scenarios under which, for example, Chinese investors could demand 

that potential projects — particularly along the Belt and Road — receive a credit rating issued by 

Chinese CRAs as a precondition to investment. If such ratings are based on PCI and graded under 

social credit models, the groundwork would be laid for global standardization of the CSCS data 

framework. Such an alternative rating system may be attractive to developing economies with 

complaints similar to China’s when it comes to perceived bias in the Western-led international 

financial architecture. For the time being, however, the practicalities of these efforts still remain in 

the realm of speculation. 

One final concern on this front is the potential for Western credit rating agencies and 

consumer finance firms to seek to unlock market opportunities in China by leveraging their expertise 

and technology to help Chinese companies or regulators develop credit algorithms based on PCI. 

Not only could such cooperation enable development of the CSCS globally, but it may also open 

an additional avenue for the transfer of knowledge or intellectual property from American firms to 

Chinese entities. 

10.6 Exporting the CSCS: corporate regulation technology

Outside of the financial space, problems that the CSCS seeks to address – low levels of 

market trust, siloed government data, poor regulatory enforceability – are not particular to China, 

and it is not difficult to imagine that a solution to any one of these problems might be attractive to 

both developed and developing economies alike. Although the specific records the CSCS currently 

collects are largely unique to Chinese governance, the categories of PCI earmarked for collection 

37 Trivium interviewed two anonymous sources with personal familiarity with the Universal Credit Ratings Group 

project.
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in China’s CSCS technical standards framework – administrative penalties, inspection records, and 

so on – are common to most nations, and it is not inconceivable that China may seek to promote 

the use of domestically-developed regulatory models abroad.

We assess that foreign countries currently have little incentive to import PCI-specific storage 

databases and database software from China, as they are both too specific to the Chinese context 

to be packaged for export without significant alterations, and too technically straightforward to 

necessitate outsourcing by foreign governments. There is no indication in government procurement 

records or the CSCS technical framework that CSCS hardware is particularly innovative.

Of potentially greater interest are the algorithms currently under development for use 

in regulatory risk prediction modeling based on PCI. The large number of Chinese companies 

involved in the development and deployment of local CSCS-adjacent regulatory platforms means 

that China is now rich with specialists who have technical experience developing and deploying 

local- and national-level software packages along the same lines as Internet Plus Regulation, 

which include features that assess, and draw insights from, corporate compliance data. Though 

currently immature, as these systems become more sophisticated, the insights they provide may 

prove of interest to countries with similar corporate compliance concerns. Such algorithms could 

be deployed on any number of urban regulatory systems, smart city frameworks, and state agency 

data platforms, not only those developed by China. Widespread adoption of these algorithms has 

the potential to reduce U.S. competitiveness in the machine learning space and could underpin a 

shift towards a Chinese-led model of urban regulatory frameworks. 

10.7 Lack of remedial avenues

For now, there is no evidence that the CSCS is being used to disadvantage foreign firms, 

but in the event that the system is leveraged against U.S. companies, or CSCS-related policies 

evolve to disadvantage foreign firms, there is no obvious channel through which the U.S. could 

address such issues with Beijing. Treaties such as the Agreement on Technical Barriers to Trade 

administered by the WTO were not written with concepts like the CSCS in mind. The Agreement 

primarily addresses potential barriers to traditional cross-border trade in goods. Its purpose is to 

proscribe the ways that member-countries might use standards, definitions, accreditations, and 

general product-registration requirements to make it more costly for foreign suppliers (vis-à-vis 

domestic producers) to get their exports to market, and the SCS falls outside of this scope. 

Additionally, the Agreement, like many others administered by the WTO, allows for 

“reasonable” differentiation in national policies toward economic management, assuming that 

those differentiated policies are applied equally to domestic and foreign firms, and assuming that 

those policies serve a “legitimate purpose.” The trade policy experts that we interviewed concluded 

that the CSCS would likely be deemed to serve a legitimate purpose. Furthermore, even if China 

was using the CSCS to disadvantage U.S. firms, it would likely be difficult to prove, which would 

undercut any drive to lodging a case against China in regard to the CSCS at the World Trade 

Organization. 

Beyond the Agreement, there does not appear to be any existing body of international trade 
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law that specifically addresses member state obligations regarding a concept akin to the CSCS. 

However, next-generation regional treaties like the Comprehensive and Progressive Agreement for 

Trans-Pacific Partnership (CPTPP) and the United States–Mexico–Canada Agreement (USMCA, 

or NAFTA 2.0) include an array of up-to-date language on national treatment, cross-border 

investment, cross-border trade in services, financial services, competition policy, and the like. 

These new behind-the-border regulations are a step-level improvement over the WTO’s wording, 

and touch on topics related to potential CSCS risk (not least, provisions related to digital trade, data 

privacy, and data localization requirements). These new treaties also include updated procedures 

for dispute settlement and authorize new remedies for compliance failures. 

In recent years, many U.S. observers and policymakers have noted the failure of the existing 

international economic regulatory architecture to adapt to and effectively manage China’s approach 

to cross-border trade and investment.38 In addition, over the years China’s non-compliance became 

more creative and more entrenched.232 Despite these problems, efforts to reform the WTO have 

faltered in recent years, in large part because the US has not mounted a sustained effort in this 

regard. In the absence of a next-generation WTO, there will be no international rules that address 

complex new developments with the potential to undermine fair trade, such as the CSCS.

38 See for example U.S. Trade Representative, “2018 USTR Report on China’s WTO Compliance,” February 

2019. https://ustr.gov/sites/default/files/2018-USTR-Report-to-Congress-on-China%27s-WTO-Compliance.pdf ; 

Mark Wu, “The ‘China, Inc.’ Challenge to Global Trade Governance,” Harvard International Law Review 57 No. 2 , 

Spring 2016. 261–324, 269. https://harvardilj.org/wp-content/uploads/sites/15/HLI210_crop.pdf.
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Section 11

Recommendations for Congress

1.	 Direct the International Trade Administration (ITA) in the Department

of Commerce to establish a dedicated channel for monitoring unfair

treatment of U.S. firms under the CSCS. As the system unfolds, it is crucial 

that the U.S. has its ear to the ground for signs that the CSCS is evolving in a 

potentially disadvantageous direction or is being used to unfairly disadvantage 

U.S. companies. Congress should direct the Department of Commerce to create 

an online tool similar to the existing “Report a Foreign Trade Barrier” webpage, 

where U.S. companies may alert the ITA to instances of biased or unequal 

treatment under the CSCS. Disclosures made through this channel should be 

used to inform analysis of CSCS impacts on U.S. firms to be included in the 

U.S. Trade Representative’s annual report on technical barriers to trade. 

2.	 Commission a study to improve Washington’s understanding of the full

scope and nature of China’s government data centralization drive. The 

emergence of the CSCS throws a spotlight on an issue much bigger than the 

CSCS itself: the political and economic power that Beijing stands to gain 

from centralizing government data. The geopolitical implications of Chinese 

government agencies realizing swift, nationwide record sharing through China’s 

broader data aggregation push — of which the CSCS is but a small part — are 

potentially far-reaching. As a starting point for formulating a response, Congress 

should commission a study from the U.S. China Economic and Security Review 

Commission that explores the depth and breadth of China’s government datasharing platform, including which agencies are participating, how data is 

administered, relevant laws governing the sharing of government data, and use 

cases illuminating how data is used.

3.	 Build and pass a federal-level legal framework for data privacy that

enables the productive sharing of data in the context of democratic values. 

If Beijing’s model of government data aggregation does indeed prove to boost 

China’s predictive capacity and bureaucratic efficiency, the temptation to follow 

in Beijing’s footsteps may be too strong for governments of developing nations 

to ignore. International adoption of Chinese-led government data collection 

models cannot be challenged without a stronger, more innovative, and at 

least comparably efficient model for supporting algorithmic regulation. The 

U.S. has an opportunity to set the global example for leveraging the power of 

administrative records and other regulatory data within the context of a data 

privacy regime based on democratic values, and the protection of personal 

privacy and national security. The U.S. cannot accomplish this without first 

establishing an overarching mandate governing what public and private sector 

organizations can and cannot do with U.S. citizen data — one that includes a 

framework under which personally identifying information in administrative 
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and government records can remain confidential while enabling key data to 

be extracted to support algorithmic decision-making. At present, federal U.S. 

data protection regulations have only been rolled out in piecemeal fashion 

covering select sectors, with key data protection issues left up to the states. A 

strong federal data protection regime will serve as a basis to establish public 

confidence in government data security, and as a foundation upon which the 

U.S. can harness the power of its big data resources.

4.	 Create a regulatory and technicalsandbox where U.S. government agencies

may collaboratively experiment with innovative regulatory informatization

infrastructure projects. Government data silos are a tremendous barrier to 

effective utilization of regulatory data. While many U.S. agencies have already 

committed to greater data availability and transparency through the Open Data 

movement, this data remains scattered, siloed, and poorly leveraged. Momentum 

for effectively leveraging U.S. agency data has picked up through legislation 

such as the Foundations for Evidence-based Policymaking Act (the Evidence 

Act) and complementary action plans such as the Federal Data Strategy, which 

seek to establish best practices for government data collection and sharing, 

increase interoperability of agency data, and help agencies leverage their data 

as a strategic resource. However, these actions stop short of providing an 

innovative, usable technical pathway and technical standards through which 

government agencies can explore new ways to connect, create data pools, and 

extract the valuable insights from shared data while protecting privacy. To fill 

this gap, Congress should form an inter-agency working group comprised of 

Federal Data Strategy stakeholders, Evidence Act stakeholders, the National 

Institute of Standards and Technology, and the General Services Administration 

(GSA). The working group should collaborate to establish both a regulatory and 

technical sandbox for federal data sharing innovation that leverages the GSA’s 

experience incubating and designing usable government platforms, NIST’s 

standard-setting prowess, and the Federal Data Strategy’s cross-agency vision 

and legislative framework for data utilization. 

5.	 Urge the U.S. Department of State to actively participate in defining global

governance frameworks ofsmart regulatory technologies. The establishment 

of global principles that govern government data collection via emerging 

technologies is a developing frontier, and it is critical that such principles are 

underpinned by democratic values, strong data privacy protections, and U.S. 

market principles. Congress should encourage the U.S. Department of State 

to increase participation in international consortiums such as the International 

Telecommunications Union (ITU), specifically in the ITU’s role as a member 

of the G20 Global Smart Cities Alliance on Technology Governance, led by 

the World Economic Forum, which was launched in October 2019 to define 

global best practices for the ethical use and governance of smart regulatory 

technologies and corporate data governance models. 
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6.	 Direct the Securities and Exchange Commission (SEC) to prepare a report

examining how China’s envisioned approach to corporate credit rating may

pose a challenge to or create an alternative to U.S.-led credit ratings models,

particularly as it may undermine market confidence in the ratings industry

over time. Based on its findings, the report should make recommendations as to 

the extent which U.S. credit rating agencies and financial institutions should be 

required to disclose business or research partnerships with Chinese entities on 

project or business endeavors related to credit and credit rating.
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Appendices

Appendix I: Member organizations of the Joint Inter-ministerial Council on the 

Construction of the Social Credit System

No. Member

1 National Development and Reform Commission

2 Central Civilization Office

3 Central Political and Legal Commission

4 Central Network Information Office

5 Ministry of Ecology and Environment

6 Ministry of Transport

7 Ministry of Science and Technology

8 Central Propaganda Department

9 People’s Bank of China

10 Central Editorial Office

11 General Administration of Customs

12 State Taxation Administration

13 Civil Service Bureau

14 Ministry of Emergency Management

15 Ministry of Agriculture and Rural Affairs

16 Ministry of State Security

17 Supreme People’s Court

18 Supreme Prosecutor’s Office

19 Ministry of Education

20 Ministry of Public Security

21 Civil Aviation Administration of China

22 Ministry of Culture and Tourism

23 Ministry of Civil Affairs

24 Ministry of Justice

25 Ministry of Finance

26 Ministry of Commerce

27 State Administration of Foreign Exchange

28 Bureau of Statistics

29 Ministry of Industry and Information Technology

30 Ministry of Housing and Urban-Rural Development

31 China Securities Regulatory Commission

32 China Banking and Insurance Regulatory Commission

33 China Council for the Promotion of International Trade
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34 Xinhua News Agency

35 National Medical Products Administration

36 State Administration for Market Regulation

37 National Intellectual Property Administration

38 All-China Federation of Industry and Commerce

39 Communist Youth League

40 China Railway 

41 National Health Commission

42 Ministry of Human Resources and Social Security

43 National Railway Administration

44 National Archives Administration

45 China Disabled Persons Federation

46 National Energy Administration
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Appendix II: Key national-level social credit policies and documents

Policy (Chinese) Policy (English) What is it? Year

国务院办公厅关于建立国务

院社会信用体系建设部际联

席会议制度的通知

Circular of the General Office of the 

State Council on the Establishment 

of the Joint Inter-ministerial Council 

for the Construction of the Social 

Credit System 

Establishes the Joint Inter-ministerial 

Council on the Construction of the Social 

Credit System

2007

国务院办公厅关于社会信用

体系建设的若干意见

Opinions of the General Office 

of the State Council on the 

Construction of a Social Credit 

System

Announces State Council’s intention to 

proceed with the establishment of the 

SCS

2007/08

社会信用体系建设规划纲要

(2014—2020年)

Planning Outline for the 

Construction of a Social Credit 

System (2014-2020)

The policy marking the official kickoff of 

the SCS project

2014

关于推进诚信建设制度化的

意见

Opinions on Promoting the 

Institutionalization of Integrity 

Construction

Formalizes the blacklisting, redlisting, 

reward, and punishments mechanisms as 

part of the SCS

2014

发改委《社会信用体系建设

规划纲要(2014—2020年)》任

务分工

Division of Labor for the 

Construction of a Social Credit 

System

NDRC’s directive outlining which 

government bodies will be responsible 

for implementing which aspects of the 

2014 Planning Outline

2014

国务院关于批转发展改革委

等部门法人和其他组织统一

社会信用代码制度建设总体

方案的通知

State Council Notice on Approving 

the NDRC and Other Departments 

to Establish the Unified Social Credit 

Identifier System for Legal Persons 

and Other Organizations

Establishes the Unified Social Credit 

Identifier scheme, setting the technical 

stage for the establishment of a 

nationwide CSCS file system

2015

国务院关于建立完善守信联

合激励和失信联合惩戒制度

加快推进社会诚信建设的指

导意见

Guiding Opinions of the State 

Council on Establishing and 

Improving the System of Joint 

Incentives for Trustworthiness 

and Joint Punishment for 

Untrustworthiness and Accelerating 

the Construction of Social Credit

Formally establishes the Unified Rewards 

and Punishments framework

2016

关于加强和规范守信联合激

励和失信联合惩戒对象名单

管理工作的指导意见

Guiding Opinions on Strengthening 

and Regulating the Management of 

Joint Incentives for Trustworthiness 

and Joint Punishment of 

Untrustworthy Targets

Improves standardization of blacklists 

and redlists

2017

国务院办公厅关于加快推进

社会信用体系建设构建以信

用为基础的新型监管机制的

指导意见

Guiding Opinions on the State 

Council on Accelerating the 

Construction of the Social Credit 

System and Building a New Creditbased Supervisory Mechanism

Urges policymakers to double down on 

SCS implementation, adds new angles 

and nuance to the SCS, ties social credit 

into “Internet + Regulation” model of 

algorithmic regulation

2019

关于进一步规范公共信用信

息纳入范围、失信惩戒和信用

修复构建诚信建设长效机制

的指导意见(征求意见稿)

Guiding Opinions on Further 

Regulating the Scope of Inclusion 

of Public Credit Information, 

Punishment for Untrustworthiness, 

and Credit Restoration to Build a 

Long-term Mechanism for Credit 

Construction (Draft for Solicitation of 

Comments)

Attempts to further standardize the 

procedures for blacklisting, credit 

repair, the definitions of blacklist-worthy 

offenses, and other elements

2020
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Appendix III: Blacklists and redlist MOUs

List of national blacklists and redlists, as well as their inter-agency cooperative agreements, as of 

July 2020. Be aware that some of the below lists, such as the blacklist targeting dishonest behavior 

in marriage registrations, and the redlist for outstanding youth volunteers, apply only to individuals 

and not companies, and are part of the larger social credit system.

Blacklist MOU (Chinese) Blacklist targets Primary Controlling Agency

关于对失信企业协同监管和联合惩

戒合作备忘录 Parties black/watchlisted by 

SAMR

State Administration for Market 

Regulation

关于对失信被执行人实施联合惩戒

的合作备忘录

Court defaulters Supreme People’s Court

关于在招标投标活动中对失信被执

行人实施联合惩戒的通知

Court defaulters restrictions 

in government procurement 

bidding

Supreme People’s Court

关于对失信被执行人实施限制不动

产交易惩戒措施的通知

Court defaulters restrictions in 

real estate transactions

Supreme People’s Court

关于对违法失信上市公司相关责任

主体实施联合惩戒措施合作备忘录 Dishonesty in the securities 

sector

China Securities Regulatory Commission

关于对重大税收违法案件当事人实

施联合惩戒措施的合作备忘录(2016

版)

Parties involved in significant tax 

violations

State taxation administration

海关失信企业实施联合惩戒的合作

备忘录

Customs “Dishonest 

enterprises”

General Administration of Customs

关于对食品药品生产经营严重失信

者开展联合惩戒的合作备忘录 Dishonesty in food and drug 

safety

State Administration for Market 

Regulation

关于对统计领域严重失信企业及其

有关人员开展联合惩戒的合作备忘

录(修订版)

Dishonesty in the field of 

statistics

National Bureau of Statistics

关于对涉金融严重失信人实施联合

惩戒的合作备忘录 Dishonesty in the financial sector China Banking and Insurance 

Regulatory Commission

关于对环境保护领域失信生产经营

单位及其有关人员开展联合惩戒的

合作备忘录

Dishonesty in environmental 

protection

Ministry of Ecology and Environment

关于对安全生产领域失信生产经营

单位及有关人员开展联合惩戒的合

作备忘录

Dishonesty in the field of work 

safety

Bureau of Emergency Management

关于对政府采购领域严重违法失信

主体开展联合惩戒的合作备忘录 Dishonesty in government 

procurement

Ministry of Finance

关于对电子商务及分享经济领域炒

信行为相关失信主体实施联合惩戒

的行动计划

Dishonesty in e-commerce and 

sharing economy

NDRC, PBOC, CAC
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关于对严重违法失信超限超载运输

车辆相关责任主体实施联合惩戒的

合作备忘录

Overloaded transport vehicles Ministry of Transport

关于对严重质量违法失信行为当事

人实施联合惩戒的合作备忘录 Serious (product) quality 

violations

State Administration for Market 

Regulation

关于对出入境检验检疫企业实施守

信联合激励和失信联合惩戒的合作

备忘录

Dishonesty in entry exit 

inspection and quarantine

State Administration for Market 

Regulation

关于对严重拖欠农民工工资用人单

位及其有关人员开展联合惩戒的合

作备忘录

Arrears of migrant workers’ 

wages

Ministry of Human Resources and Social 

Security

关于对文化市场领域严重违法失信

市场主体及有关人员开展联合惩戒

的合作备忘录

Dishonesty in the cultural market Ministry of Culture and Tourism

关于对运输物流行业严重违法失信

市场主体及其有关人员实施联合惩

戒的合作备忘录

Dishonesty in transportation and 

logistics

Ministry of Transport

关于对农资领域严重失信生产经营

单位及其有关人员开展联合惩戒的

合作备忘录

Dishonesty in agricultural 

materials

Ministry of Agriculture and Rural Affairs

关于对财政性资金管理使用领域相

关失信责任主体实施联合惩戒的合

作备忘录

Dishonesty in financial fund 

management and use

Ministry of Finance

关于对电力行业严重违法失信市场

主体及其有关人员实施联合惩戒的

合作备忘录

Dishonesty in the power industry National Energy Administration

关于对盐行业生产经营严重失信者

开展联合惩戒的合作备忘录 Dishonesty in Salt Industry State Council Salt Industry Management 

Agency

关于在电子认证服务行业实施守信

联合激励和失信联合惩戒的合作备

忘录

Dishonest electronic certification 

service institutions

Ministry of Industry and Information 

Technology

关于对社会保险领域严重失信企业

及其有关人员实施联合惩戒的合作

备忘录

Dishonesty in social insurance Ministry of Human Resources and Social 

Security

关于对石油天然气行业严重违法失

信主体实施联合惩戒的合作备忘录 Oil and gas industry Various

关于对慈善捐赠领域相关主体实施

守信联合激励和失信联合惩戒的合

作备忘录

Dishonest charitable 

organizations / dishonest donors 

/ dishonest beneficiaries

Ministry of Civil Affairs

关于对房地产领域相关失信责任主

体实施联合惩戒的合作备忘录 Dishonesty in real estate industry Ministry of Housing and Urban Rural 

Development

关于对保险领域违法失信相关责任

主体实施联合惩戒的合作备忘录 Dishonesty in Insurance industry China Banking and Insurance 

Regulatory Commission
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关于对对外经济合作领域严重失信

主体开展联合惩戒的合作备忘录 Dishonesty in foreign economic 

cooperation

Ministry of Commerce, Ministry of 

Foreign Affairs

关于对国内贸易流通领域严重违法

失信主体开展联合惩戒的合作备

忘录

Dishonesty in domestic trade Ministry of Commerce, State 

Administration for Market Regulation

关于对婚姻登记严重失信当事人开

展联合惩戒的合作备忘录 Dishonesty in marriage 

registration

Ministry of Civil Affairs

关于对家政服务领域相关失信责任

主体实施联合惩戒的合作备忘录 Dishonesty in the field of 

domestic services

Ministry of Commerce

关于对公共资源交易领域严重失信

主体开展联合惩戒的备忘录 Dishonesty in public resource 

trading (bidding / tendering)

Various

关于对严重危害正常医疗秩序的失

信行为责任人实施联合惩戒合作备

忘录

Parties endangering the normal 

medical order

National Health Commission

关于对科研领域相关失信责任主体

实施联合惩戒的合作备忘录 Dishonesty in science and 

technology research

Ministry of Science and Technology

关于对知识产权(专利)领域严重失

信主体开展联合惩戒的合作备忘录 Dishonesty in IP and patents National Intellectual Property 

Administration

关于对会计领域违法失信相关责任

主体实施联合惩戒的合作备忘录 Dishonesty in the accounting 

field

Ministry of Finance

关于对旅游领域严重失信相关责任

主体实施联合惩戒的合作备忘录 Dishonesty in tourism sector Ministry of Culture and Tourism

关于在一定期限内适当限制特定严

重失信人乘坐民用航空器推动社会

信用体系建设的意见

National no-fly list Civil Aviation Administration

关于在一定期限内适当限制特定严

重失信人乘坐火车推动社会信用体

系建设的意见

National no-ride list (trains and 

boats)

China Railway

Redlists / Targets of Unified 

Rewards

English translation Primary controlling agency

关于在电子认证服务行业实施守信

联合激励和失信联合惩戒的合作备

忘录 

Authorized / honest electronic 

certification service institutions

Ministry of Industry and Information 

Technology

关于对出入境检验检疫企业实施守

信联合激励和失信联合惩戒的合作

备忘录

Honesty in entry exit inspection 

and quarantine

State Administration for Market Regulation

关于对纳税信用A级纳税人实施联

合激励措施的合作备忘录 A-grade taxpayers State Taxation Administration

关于实施优秀青年志愿者守信联合

激励加快推进青年信用体系建设的

行动计划

Exceptional youth volunteers Communist Youth League
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关于对安全生产领域守信生产经营

单位及其有关人员开展联合激励的

合作备忘录

Honesty in production safety Bureau of Emergency Management

关于对交通运输工程建设领域守信

典型企业实施联合激励的合作备

忘录

Honesty in transport industry Ministry of Transport

关于对海关高级认证企业实施联合

激励的合作备忘录 High-level customs certification General Administration of Customs

关于对慈善捐赠领域相关主体实施

守信联合激励和失信联合惩戒的合

作备忘录

Honesty / charity Ministry of Civil Affairs

Announced / New / 

Developing

Notes Primary stakeholders

涉医涉药领域虚假违法广告失信主

体名单

Announced in one of the first 

cooperative blacklists between 

industry associations and 

government

China Chemical and Pharmaceutical 

Industry Association, along with 7 other 

industry associations

交通部将制定共享单车领域失信惩

戒备忘录 Plans to create a bike sharing 

industry blacklist

NDRC in cooperation with private city 

bicycle sharing companies

关于建立残疾儿童康复救助制度的

意见 Plans to develop a blacklist for 

the mistreatment of disabled 

children.

Disabled Person’s Federation
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Appendix IV: Key provincial-level social credit regulations by province

Province Policy name (Chinese) Policy status Policy addresses Date

Anhui 安徽省公共信用信息

征集共享使用暂行办

法

Effective General PCI (interim) 2015

Beijing 社会信用条例立法 Unreleased Provincial social credit Release planned by 

end of 2020

Beijing 北京市公共信用信息

管理办法

Effective General PCI Effective May 2018

Chongqing 重庆市社会信用条例 Unreleased Provincial social credit Released planned by 

end of 2020

Chongqing 重庆市企业信用信息

管理办法

Effective Enterprise PCI Effective March 2017

Fujian 福建省公共信用信息

管理暂行办法

Effective General PCI (interim) Effective August 2015

Gansu 甘肃省公共信用信息

条例(送审稿)

Draft General PCI Open for comments 

May 2018

Guangdong 广东省社会信用条例

(草案)

Draft Provincial social credit Draft released 

November 2019

Guangxi None

Guizhou 贵州省社会信用条例

(草案)

Draft Provincial social credit Draft released June 

2019

Hainan None

Hebei 河北省社会信用信息

条例

Effective General PCI Effective January 2018

Heilongjiang 黑龙江省企业信用信

息征集发布使用办法

(2018年修正本)

Effective Enterprise PCI Effective May 2018

Henan 河南省社会信用条例 Effective Provincial social credit Effective May 2020

Hubei 湖北省社会信用信息

管理条例

Effective General PCI Effective July 2017

Hunan None

Inner 

Mongolia

内蒙古自治区公共信

用信息管理办法

Effective General PCI Effective June 2018

Jiangsu 江苏省社会信用条例(

草案,征求意见稿)

Draft Provincial social credit Draft released April 

2020

Jiangxi None

Jilin 吉林省社会信用条例

草案(征求意见稿)

Draft Provincial social credit Draft released 

December 2019
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Liaoning 辽宁省公共信用信息

管理条例

Effective General PCI Effective Feb 2020

Liaoning 辽宁省公共信用信息

管理办法

Effective General PCI Effective January 2016

Ningxia 宁夏社会信用条例 Unreleased Provincial social credit Release planned - no 

date given

Ningxia 宁夏回族自治区公共

信用信息管理暂行办

法》实施细则(试行)

Effective General PCI (interim 

trial)

Effective July 2019

Qinghai 青海省公共信用信息

条例(送审稿)

Draft General PCI Draft released June 

2020

Shaanxi 陕西省社会信用条例

(草案)

Unreleased Provincial social credit Release planned for 

2021

Shaanxi 陕西省企业信用监督

管理办法

Effective Enterprise PCI Effective June 2017

Shandong 山东省社会信用条例 Draft Provincial social credit Draft released April 

2020

Shanghai 上海市社会信用条例 Effective Provincial social credit Effective October 2017

Shanxi None

Sichuan None

Tianjin 天津市社会信用条例(

送审稿)

Draft Provincial social credit Draft released June 

2020

Tibet None

Xinjiang 自治区社会信用信息

管理暂行办法

Unreleased General PCI Release planned - no 

date given

Yunnan 云南省公共信用信息

管理办法

Unreleased General PCI Release planned for 

2020

Zhejiang 浙江省社会信用条例

(草案)

Draft Provincial social credit Draft out May 2017 

Zhejiang 浙江省公共信用信息

管理条例

Effective General PCI Effective Jan 2018
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References & Notes

1 Lin Junyue, Principles of the Social Credit System (社会信用体系原理), China Fangzheng Press, December 

2002. Translation. 

2 State Council of the People’s Republic of China, Planning Outline for the Establishment of a Social Credit System (2014-2020) (社会信用体系建设规划纲要 (2014—2020年) 的通知), June 27, 2014. Translation. http://webcache.googleusercontent.com/search?q=cache:http://www.gov.cn/zhengce/content/2014-06/27/content_8913.htm.

3 General Office of the State Council of the People’s Republic of China, Guiding Opinions of the General Office 

of the State Council on Accelerating the Construction of a Social Credit System and Building a New Credit-based 

Supervisory Mechanism (国务院办公厅关于加快推进社会信用体系建设构建以信用为基础的新型监管机制的

指导意见), July 16, 2019. Translation. http://webcache.googleusercontent.com/search?q=cache:http://www.gov.cn/

zhengce/content/2019-07/16/content_5410120.htm.

4 Lauren Dudley, “China’s Ubiquitous Facial Recognition Tech Sparks Privacy Backlash,” Diplomat, March 7, 

2020. https://thediplomat.com/2020/03/chinas-ubiquitous-facial-recognition-tech-sparks-privacy-backlash/.

5 Samantha Hoffman, “Social Credit,” Australian Strategic Policy Institute, June 2018. https://www.aspi.org.au/

report/social-credit.

6 Larry Catá Backer, “China’s Social Credit System: Data-Driven Governance For a ‘New Era’,” Current History

Volume 118:809 (January 2019): 209-214.

7 Third Plenary Session of the Eighteenth Central Committee of the Communist Party of China, “Decision of 

the Central Committee of the Communist Party of China on Several Major Issues in Comprehensively Deepening 

Reform”, November 12, 2013. http://webcache.googleusercontent.com/search?q=cache:MvxDJ0OopCkJ:www.gov.

cn/jrzg/2013-11/15/content_2528179.htm+&cd=1&hl=en&ct=clnk&gl=ph.

8 General Office of the State Council of the People’s Republic of China, “Li Keqiang chaired an Executive 

Meeting of the State Council (January 15, 2014)” ( 李克强主持召开国务院常务会议(2014年1月15日)), January 15, 2014. Translation. http://webcache.googleusercontent.com/search?q=cache:http://www.gov.cn/guowuyuan/2014-01/15/content_2591053.htm.

9 Lin Junyue, Principles of the Social Credit System (社会信用体系原理), China Fangzheng Press, December 

2002. Translation. 

10 Lin Junyue, “Why Do We Say the Construction of the Social Credit System Began in 1999?” (林钧跃:为什

么说社会信用体系建设起始于1999年?), Xinhua Credit, September 9, 2019. Translation. http://webcache.googleusercontent.com/search?q=cache:https://m.credit100.com/xhxy/c/2019-09-09/535610.shtml.

11 Yu Jinming, Lin Junyue & Sun Jie, The National Credit Management System (国家信用管理体系), Social 

Sciences Academic Press, March 2000. Translation.

12 Lin Junyue, “Credit Concepts” (信用概念) in Principles of the Social Credit System, China Fangzheng Press, 

January December 2002, 2-24. Translation. 

13 Lin Junyue, Principles of the Social Credit System (社会信用体系原理), China Fangzheng Press, December 

2002. Translation. 

14 Lin Junyue, Principles of the Social Credit System (社会信用体系原理), China Fangzheng Press, December 

2002.;Wu Weihai and Zhang Shaoli, Credit of Great Powers: the Global Vision of China’s Social Credit System (大

国信用 全球视野的中国社会信用体系), China Planning Press, January 2017. Translation. 

15 Lin Junyue, Principles of the Social Credit System (社会信用体系原理), China Fangzheng Press, December 

2002, 50. Translation. 
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16 Lin Junyue, “Legal Environment for the Establishment of a Credit System” (建立信用体系的法律环境) in 

Principles of the Social Credit System, China Fangzheng Press, December 2002, 140-165. Translation.

17 Lin Junyue, “The Credit Market and its Data Environment” (征信市场及其数据环境) in Principles of the 

Social Credit System, China Fangzheng Press, December 2002, 61-122. Translation.

18 Lin Junyue, “The Social Credit System and its Framework” (社会信用体系及其框架) in Principles of the 

Social Credit System, China Fangzheng Press, December 2002, 39-53. Translation.

19 State Council of the People’s Republic of China, Planning Outline for the Establishment of a Social Credit System (2014-2020) (社会信用体系建设规划纲要 (2014—2020年) 的通知), June 27, 2014. Translation. http://webcache.googleusercontent.com/search?q=cache:http://www.gov.cn/zhengce/content/2014-06/27/content_8913.htm.

20 Lin Junyue, “Why Do We Say the Construction of the Social Credit System Began in 1999?” (林钧跃:为什

么说社会信用体系建设起始于1999年?), Xinhua Credit, September 9, 2019. Translation. http://webcache.googleusercontent.com/search?q=cache:https://m.credit100.com/xhxy/c/2019-09-09/535610.shtml.

21 General Office of the State Council of the People’s Republic of China, Several Opinions on the Construction of 

a Social Credit System (国务院办公厅关于社会信用体系建设的若干意见), March 28, 2008. Translation. http://

webcache.googleusercontent.com/search?q=cache:http://www.gov.cn/zhengce/content/2008-03/28/content_1923.

htm.

22 General Office of the State Council of the People’s Republic of China, Notice on the Establishment of the Joint 

Inter-ministerial Council System of the State Council’s Social Credit System (国务院办公厅关于建立国务院社会

信用体系建设部际联席会议制度的通知), March 28, 2008. Translation. http://webcache.googleusercontent.com/

search?q=cache:http://www.gov.cn/zhengce/content/2008-03/28/content_1907.htm.

23 Central Guidance Commission for Building Spiritual Civilization of the People’s Republic of China, Opinions 

on Promoting the Institutionalization of Integrity Construction (关于推进诚信建设制度化的意见), July 23, 2014. 

Translation. http://webcache.googleusercontent.com/search?q=cache:http://www.gov.cn/xinwen/2014-08/01/content_2728487.htm.

24 Roger Creemers and China Law Translate trans., “State Council Notice Concerning Issuance of the Planning 

Outline for the Establishment of a Social Credit System (2014-2020),” State Council of the People’s Republic of 

China, April 27, 2015. https://www.chinalawtranslate.com/en/socialcreditsystem/.

25 Wang Lianzhang, “County Government on Legal Naughty List for Unpaid Debts,” Sixth Tone, April 1, 2017. 

http://www.sixthtone.com/news/2131/county-government-on-legal-naughty-list-for-unpaid-debts.

26 National Development and Reform Commission and People’s Bank of China, Guiding Opinions on Further 

Regulating the Scope of Inclusion of Public Credit Information, Punishment for Untrustworthiness, and Credit 

Restoration to Build a Long-term Mechanism for Credit Construction (Draft for Solicitation of Comments) (关于进

一步规范公共信用信息纳入范围、失信惩戒和信用修复构建诚信建设长效机制的指导意见(征求意见稿)), 

July 22, 2020. Translation. https://hd.ndrc.gov.cn/yjzx/yjzx_add.jsp?SiteId=339.

27 Jeremy Daum, “Untrustworthy: Social Credit Isn’t What You Think It Is”. Jeremy Daum, “Giving Credit 3: 

Inputs and Outputs,” China Law Translate, Jun 27, 2019. https://verfassungsblog.de/untrustworthy-social-creditisnt-what-you-think-it-is/.

28 Jamie P. Horsley, “China’s Corporate Social Credit ‘System,’” Briefing, U.S.-China Business Council, Washington, DC, January 31, 2020. https://law.yale.edu/sites/default/files/area/center/china/document/horsley_china_corporate_social_credit_1-31-20.pdf. 

29 Shanghai Development and Reform Commission, Shanghai City Social Credit Regulations (上海市社会信用

条例), December 31, 2016. http://webcache.googleusercontent.com/search?q=cache:NsY5tAyQsLUJ:www.shanghai.gov.cn/nw2/nw2314/nw2315/nw4411/u21aw1187561.html+&cd=1&hl=en&ct=clnk&gl=ph.
79

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30 Ding Xiaodong, “Law According to the Chinese Communist Party: Constitutionalism and Socialist Rule 

of Law” Modern China, January 8, 2017, Volume 43, Issue 3, 322-352. https://journals.sagepub.com/doi/

abs/10.1177/0097700416686731. 

31 National Development and Reform Commission of the People’s Republic of China, Plan Outline of the Division of Labor for the Construction of a Social Credit System (2014-2020) (国家发展改革委 人民银行关于印发

《社会信用体系建设规划纲要(2014—2020年)任务分工》和《社会信用体系建设三年重点工作任务(2014—

2016)》的通知, December 16, 2014. Translation. https://www.ndrc.gov.cn/xxgk/zcfb/tz/201501/t20150105_963726.

html.

32 National Development and Reform Commission of the People’s Republic of China, “Deputy Director Lian 

Weiliang Presided over the ‘Social Credit System Construction Work’ Special Meeting” (连维良副主任主持召开“

社会信用体系建设工作”专题会议), September 21, 2017. Translation. http://webcache.googleusercontent.com/

search?q=cache:https://www.ndrc.gov.cn/fzggw/jgsj/cjd/sjdt/201709/t20170921_1111415.html.

33 State Council of the People’s Republic of China, Interim Regulations on Enterprise Information Disclosure 

(State Council Order No. 654) (企业信息公示暂行条例(国务院令第654号)), August 23, 2014. Translation. http://

webcache.googleusercontent.com/search?q=cache:http://www.gov.cn/zhengce/2014-08/23/content_2739774.htm.

34 General Office of the State Council of the People’s Republic of China, Notice of the General Office of the 

State Council on the Establishment of the Joint Inter-ministerial Joint Council for the Development of the Social 

Credit System (国务院办公厅关于建立国务院社会信用体系建设部际联席会议制度的通知), April 18, 2007. 

Translation. http://webcache.googleusercontent.com/search?q=cache:http://www.gov.cn/gongbao/content/2007/

content_632090.htm.; Credit Jiaozuo, “4 New Members! The number of member units of the Inter-ministerial Joint 

Conference on the Construction of the Social Credit System Increases to 46” (新增4家!社会信用体系建设部际联

席会议成员单位调整为46家), April 18, 2007. Translation. http://www.creditjz.gov.cn/24/7012.html.

35 State Information Center of the People’s Republic of China, “General Overview of the National E-government 

Extranet in the First Half of 2019” (2019年上半年国家电子政务外网总体概况), December 12, 2019. Translation. 

http://webcache.googleusercontent.com/search?q=cache:http://www.sic.gov.cn/News/462/10367.htm.

36 General Office of the State Council of the People’s Republic of China, Guiding Opinions of the General Office 

of the State Council on Accelerating the Construction of a Social Credit System and Building a New Credit-based 

Supervisory Mechanism (国务院办公厅关于加快推进社会信用体系建设构建以信用为基础的新型监管机制的

指导意见), July 16, 2019. Translation. http://webcache.googleusercontent.com/search?q=cache:http://www.gov.cn/

zhengce/content/2019-07/16/content_5410120.htm.

37 National Development and Reform Commission and People’s Bank of China, Guiding Opinions on Further 

Regulating the Scope of Inclusion of Public Credit Information, Punishment for Untrustworthiness, and Credit 

Restoration to Build a Long-term Mechanism for Credit Construction (Draft for Solicitation of Comments) (关于进

一步规范公共信用信息纳入范围、失信惩戒和信用修复构建诚信建设长效机制的指导意见(征求意见稿)), 

July 22, 2020. Translation. https://hd.ndrc.gov.cn/yjzx/yjzx_add.jsp?SiteId=339.

38 National Development and Reform Commission of the People’s Republic of China, Plan Outline of the Division of Labor for the Construction of a Social Credit System (2014-2020) (国家发展改革委 人民银行关于印发

《社会信用体系建设规划纲要(2014—2020年)任务分工》和《社会信用体系建设三年重点工作任务(2014—

2016)》的通知, December 16, 2014. Translation. https://www.ndrc.gov.cn/xxgk/zcfb/tz/201501/t20150105_963726.

html.

39 Ministry of Human Resources and Social Security of the People’s Republic of China, Regulations on Social 

Insurance Management Services (Draft for Solicitation of Comments) (社会保险经办管理服务条例(征求意见

稿), November 13, 2018. Translation. http://www.mohrss.gov.cn/SYrlzyhshbzb/zcfg/SYzhengqiuyijian/zq_fgs/201811/

t20181113_304675.html.

40 Ministry of Agriculture and Rural Affairs of the People’s Republic of China, Notice on the Establishment of 

Credit Files of Agricultural Materials and Agricultural Products Producers and Operational Entities (农业部办公
80

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厅关于建立农资和农产品生产经营主体信用档案的通知), August 1, 2017. Translation. http://www.moa.gov.cn/

nybgb/2017/dbq/201801/t20180103_6133993.htm.

41 Ministry of Ecology and Environment of the People’s Republic of China, Supporting Documents for the “Supervision and Management Measures for Compiling Environmental Impact Assessments for Construction Projects”

(关于发布《建设项目环境影响报告书(表)编制监督管理办法》配套文件的公告), October 24, 2019. Translation. http://www.mee.gov.cn/xxgk2018/xxgk/xxgk01/201910/t20191028_739489.html.

42 National Development and Reform Commission of the People’s Republic of China, Plan Outline of the Division of Labor for the Construction of a Social Credit System (2014-2020) (国家发展改革委 人民银行关于印发

《社会信用体系建设规划纲要(2014—2020年)任务分工》和《社会信用体系建设三年重点工作任务(2014—

2016)》的通知, December 16, 2014. Translation. https://www.ndrc.gov.cn/xxgk/zcfb/tz/201501/t20150105_963726.

html.

43 Central Guidance Commission for Building Spiritual Civilization of the People’s Republic of China, Opinions 

on Promoting the Institutionalization of Integrity Construction (关于推进诚信建设制度化的意见), July 23, 2014. 

Translation. http://webcache.googleusercontent.com/search?q=cache:http://www.gov.cn/xinwen/2014-08/01/content_2728487.htm.

44 State Council of the People’s Republic of China, Overall Plan for the Establishment of a Unified Social Credit 

Code System for Legal Persons and Other Organizations (法人和其他组织统一社会信用代码制度建设总体

方案), June 11, 2015. Translation. http://webcache.googleusercontent.com/search?q=cache:http://www.gov.cn/

zhengce/content/2015-06/17/content_9858.htm.

45 Jamie P. Horsley, “China’s Corporate Social Credit ‘System’,” Briefing, U.S.-China Business Council, Washington, DC, January 31, 2020. https://law.yale.edu/sites/default/files/area/center/china/document/horsley_china_corporate_social_credit_1-31-20.pdf. Translation of: Shanghai Development and Reform Commission, Shanghai City 

Social Credit Regulations (上海市社会信用条例), December 31, 2016. http://webcache.googleusercontent.com/

search?q=cache:NsY5tAyQsLUJ:www.shanghai.gov.cn/nw2/nw2314/nw2315/nw4411/u21aw1187561.html+&cd=1&hl=en&ct=clnk&gl=ph.

46 Joint Meeting Office of Jilin Province Social Credit System Construction, Notice on Soliciting Public Comments on the “Draft Social Credit Regulations of Jilin Province (Draft for Comments)” (关于《吉林省社会信用条

例草案(征求意见稿)》公开征求意见的通知), December 30, 2019. Translation. http://webcache.googleusercontent.com/search?q=cache:http://credit.jl.gov.cn/contents/955/37818.html.

47 Jeremy Daum, “Giving Credit 3: Inputs and Outputs,” China Law Translate, January 15, 2018. https://www.

chinalawtranslate.com/en/giving-credit-3-inputs-and-outputs.

48 Jeremy Daum, “Giving Credit 3: Inputs and Outputs,” China Law Translate, January 15, 2018. https://www.

chinalawtranslate.com/en/giving-credit-3-inputs-and-outputs.;State Council of the People’s Republic of China, 

Interim Regulations on Enterprise Information Disclosure (State Council Order No. 654) (企业信息公示暂行条例(

国务院令第654号)), August 23, 2014. Translation. http://webcache.googleusercontent.com/search?q=cache:http://

www.gov.cn/zhengce/2014-08/23/content_2739774.htm.

49 General Office of the National Development and Reform Commission of the People’s Republic of China, 

Credit Information Catalogue of the National Credit Information Sharing Platform (Member Unit of Inter-Ministry Joint Meeting 2016 Edition) (国家发展改革委办公厅关于印发《全国信用信息共享平台信用信息目录 (

部际联席会议成员单位 2016 年))》的通知), 2016. Translation. http://www.hbcredit.gov.cn/xyjs/tzgg/201608/

P020160812332922961444.pdf.

50 National Development and Reform Commission and People’s Bank of China, Guiding Opinions on Further 

Regulating the Scope of Inclusion of Public Credit Information, Punishment for Untrustworthiness, and Credit 

Restoration to Build a Long-term Mechanism for Credit Construction (Draft for Solicitation of Comments) (关于进

一步规范公共信用信息纳入范围、失信惩戒和信用修复构建诚信建设长效机制的指导意见(征求意见稿)), 

July 22, 2020. Translation. https://hd.ndrc.gov.cn/yjzx/yjzx_add.jsp?SiteId=339.
81

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51 General Office of the National Development and Reform Commission of the People’s Republic of China, 

Credit Information Catalogue of the National Credit Information Sharing Platform (Member Unit of Inter-Ministry Joint Meeting 2016 Edition) (国家发展改革委办公厅关于印发《全国信用信息共享平台信用信息目录 (

部际联席会议成员单位 2016 年))》的通知), 2016. Translation. http://www.hbcredit.gov.cn/xyjs/tzgg/201608/

P020160812332922961444.pdf.

52 National Public Credit Information Center, National Credit Information Sharing Platform Credit Information 

Collection Catalogue (2019 Edition) (全国信用信息共享平台信用信息归集目录(2019年版)), June 2019. Translation. http://www.hbcredit.gov.cn/gywm/xyml/201909/P020190903352933734904.pdf.

53 Record type: National Public Credit Information Center, National Credit Information Sharing Platform Credit 

Information Collection Catalogue (2019 Edition) (全国信用信息共享平台信用信息归集目录(2019年版)), June 

2019. Translation. http://www.hbcredit.gov.cn/gywm/xyml/201909/P020190903352933734904.pdf; Other columns:

compiled by Trivium China from NDRC technical framework documentation, reviews of existing corporate social 

credit record databases, and prior knowledge of Chinese business registration procedures.

54 National Development and Reform Commission of the People’s Republic of China, “Deputy Director Lian 

Weiliang Presided over the National Symposium on the Construction of a Unified Credit Information Sharing and 

Exchange Platform” (连维良副主任主持召开全国统一的信用信息共享交换平台建设工作座谈会), November 

30, 2015. Translation. http://webcache.googleusercontent.com/search?q=cache:http://www.gov.cn/guowuyuan/

vom/2015-11/30/content_5018242.htm.

55 State Information Center of the People’s Republic of China, “General Overview of the National E-government 

Extranet in the First Half of 2019” (2019年上半年国家电子政务外网总体概况), December 12, 2019. Translation. 

http://webcache.googleusercontent.com/search?q=cache:http://www.sic.gov.cn/News/462/10367.htm.

56 National Development and Reform Commission of the People’s Republic of China, General Framework for 

Standard System of Public Credit Information (国家发展改革委办公厅关于印发实施《公共信用信息标准体

系框架》等六项工程标准的通知), November 15, 2017. Translation. http://webcache.googleusercontent.com/

search?q=cache:https://www.ndrc.gov.cn/xxgk/zcfb/tz/201803/t20180302_962672.html; National Development and 

Reform Commission of the People’s Republic of China, Means and Interface Specifications for Public Credit Information Exchange (公共信用信息交换方式及接口规范), November 15, 2017. Translation; National Development 

and Reform Commission, Guidelines for the Compilation of the Public Credit Information Resources Catalogue (

公共信用信息资源目录编制指南), November 15, 2017. Translation; National Development and Reform Commission, Rules for Public Credit Information Classification and Coding (公共信用信息分类与编码规范), November 

15, 2017. Translation. ; National Development and Reform Commission, Rules for Publication of Public Credit 

Information (公共信用信息公示规范), November 15, 2017. Translation; National Development and Reform Commission, Specification for Basic Data Item of Public Credit Information (公共信用信息基础数据项规范), November 15, 2017. Translation.

57 National Development and Reform Commission of the People’s Republic of China, Guide for Compiling the 

Catalog of Public Information Resources (公共信用信息资源目录编制指南), November 15, 2017. Translation. 

https://www.creditchina.gov.cn/biaozhunguifan/zonghexingbiaozhunguifan/201803/t20180302_109779.html.

58 China National Institute of Standardization, “General Framework for the Standard System of Public Credit 

Information (公共信用信息标准总体架构),” National Public Service Platform for Standards Information, accessed 

June 11, 2020. Translation. http://webcache.googleusercontent.com/search?q=cache:http://std.samr.gov.cn/gb/

search/gbDetailed?id=95A3CA380B40D09FE05397BE0A0A47FC.

59 National Development and Reform Commission of the People’s Republic of China, Guide for Compiling the 

Catalog of Public Information Resources (公共信用信息资源目录编制指南), November 15, 2017. Translation. 

https://www.creditchina.gov.cn/biaozhunguifan/zonghexingbiaozhunguifan/201803/t20180302_109779.html.

60 State Administration for Industry and Commerce of the People’s Republic of China, “Creating a National 

Network - One of the Records of the Construction of the National Enterprise Credit Information Publicity System” (

织好织密 ‘全国一张网’—国家企业信用信息公示系统建设纪实之一), March 21, 2017. Translation. http://web-
82

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cache.googleusercontent.com/search?q=cache:http://www.gov.cn/xinwen/2017-03/21/content_5179369.htm.

61 General Office of the State Council of the People’s Republic of China, Guiding Opinions of the General Office 

of the State Council on Accelerating the Construction of a Social Credit System and Building a New Credit-based 

Supervisory Mechanism (国务院办公厅关于加快推进社会信用体系建设构建以信用为基础的新型监管机制的

指导意见), July 16, 2019. Translation. http://webcache.googleusercontent.com/search?q=cache:http://www.gov.cn/

zhengce/content/2019-07/16/content_5410120.htm.

62 National Public Credit Information Center, “Comprehensive Evaluation Results of the Public Credit of Some 

Natural Gas Related Enterprises (Phase IV)” (涉部分天然气领域企业公共信用综合评价结果(第四期)), June 20, 

2019. Translation. https://www.creditchina.gov.cn/xinxigongshi/strqqy/201906/t20190620_159295.html; Sichuan 

Development and Reform Commission Party Branch of the General Credit Office, “Taking the Lead to Make Good 

Use of the Results of Public Credit Evaluation and do a Good Job of Credit Supervision in Five Major Industries” (

牵头开展用好公共信用评价结果切实做好五大行业信用监管工作), January 16, 2019. Translation. http://www.

scjgdj.gov.cn/B000000237/201901/69711.html.

63 National Development and Reform Commission and People’s Bank of China, Guiding Opinions on Strengthening and Regulating the Management of the List of Targets for Joint Incentives for Trustworthiness and Joint Punishment for Dishonesty (关于加强和规范守信联合激励和失信联合惩戒对象名单管理工作的指导意见), October 

30, 2017. Translation. https://webcache.googleusercontent.com/search?q=cache:hze2bITWZMEJ:https://www.ndrc.

gov.cn/xxgk/zcfb/ghxwj/201711/t20171103_960925.html+&cd=1&hl=en&ct=clnk&gl=ph.

64 National Public Credit Information Center, “2018 Project Research Solicitation Notice” (国家公共信用信息中

心2018年课题研究征集公告), October 10, 2018. Translation. http://webcache.googleusercontent.com/search?q=-

cache:https://www.ndrc.gov.cn/xwdt/tzgg/201810/t20181010_959241.html.

65 General Office of the State Council of the People’s Republic of China, Guiding Opinions of the General Office 

of the State Council on Accelerating the Construction of a Social Credit System and Building a New Credit-based 

Supervisory Mechanism (国务院办公厅关于加快推进社会信用体系建设构建以信用为基础的新型监管机制的

指导意见), July 16, 2019. Translation. http://webcache.googleusercontent.com/search?q=cache:http://www.gov.cn/

zhengce/content/2019-07/16/content_5410120.htm.

66 State Information Center, Big Data Report on Trade Cooperation Under the Belt and Road Initiative (“一带一

路”贸易合作大数据报告), May 2018. Translation.

67 State Information Center of the People’s Republic of China, “General Overview of the National E-government 

Extranet in the First Half of 2019” (2019年上半年国家电子政务外网总体概况), December 12, 2019. Translation. 

http://webcache.googleusercontent.com/search?q=cache:http://www.sic.gov.cn/News/462/10367.htm.

68 Central Guidance Commission for Building Spiritual Civilization of the People’s Republic of China, Opinions 

on Promoting the Institutionalization of Integrity Construction (关于推进诚信建设制度化的意见), July 23, 2014. 

Translation. http://webcache.googleusercontent.com/search?q=cache:http://www.gov.cn/xinwen/2014-08/01/content_2728487.htm.

69 China Pharmaceutical Industry Association, Administrative Measures for the List of Untrustworthy Subjects 

in the Pharmaceutical Industry (Trial) (医药行业失信主体名单管理办法 (试行)), Credit China, November 19, 

2019. Translation. https://www.creditchina.gov.cn/hangyexinyong_824/faguiguifanbiaozhun/quanguoxinghangyexiehui/201911/t20191119_175873.html.

70 Jeremy Daum, “Social Credit & the Law,” China Law Translate, July 29, 2020. https://www.chinalawtranslate.

com/en/social-credit-the-law.

71 General Administration of Customs of the People’s Republic of China, Measures of the General Administration 

of Customs of the People’s Republic of China on Enterprise Credit Management (中华人民共和国海关企业信用管

理办法), March 3, 2018. Translation. http://webcache.googleusercontent.com/search?q=cache:http://www.customs.

gov.cn/customs/302249/302266/302268/1471430/index.html.
83

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72 Jeremy Daum, “The redlists are coming! The blacklists are coming!” China Law Translate, March 3, 2018. 

https://www.chinalawtranslate.com/en/the-redlists-are-coming-the-blacklists-are-coming/.

73 State Administration of Work Safety of the People’s Republic of China, Implementation Measures for Joint 

Incentives for Trustworthy Behaviors in Work Safety (对安全生产领域守信行为开展联合激励的实施办法), December 7, 2017. Translation. http://webcache.googleusercontent.com/search?q=cache:https://www.mem.gov.cn/gk/

gwgg/gfxwj/2017/201801/t20180117_242812.shtml.

74 National Development and Reform Commission and Supreme People’s Court, Memorandum of Cooperation 

on Joint Punishment of Seriously Untrustworthy Entities in the Field of Foreign Economic Cooperation (关于印

发对失信被执行人实施联合惩戒的合作备忘录的通知), January 1, 2016. Translation. http://webcache.googleusercontent.com/search?q=cache:NpVKk_JoKrsJ:www.csrc.gov.cn/pub/newsite/flb/flvcxjs/cxjslhjcbwl/201805/

t20180530_338881.html+&cd=1&hl=en&ct=clnk&gl=ph.

75 National Development and Reform Commission and People’s Bank of China, Memorandum of Cooperation 

on Joint Punishment of Seriously Untrustworthy Entities in the Field of Oil and Natural Gas (关于对石油天然

气行业严重违法失信主体实施联合惩戒的合作备忘录), August 2, 2017. Translation. http://www.gov.cn/xinwen/2017-08/28/content_5221065.htm.

76 Meng Meng and Aizhu Chen, “Factbox: Catching tigers and hidden flies in China’s energy sector,” Reuters, 

September 21, 2018. https://www.reuters.com/article/us-china-corruption-energy-factbox/factbox-catching-tigersand-hidden-flies-in-chinas-energy-sector-idUSKCN1M1120.

77 Jeremy Daum, “Social Credit & the Law,” China Law Translate, July 29, 2020. https://www.chinalawtranslate.

com/en/social-credit-the-law.

78 National Public Credit Information Center, National Credit Information Sharing Platform Credit Information 

Collection Catalogue (2019 Edition) (全国信用信息共享平台信用信息归集目录(2019年版)), June 2019. Translation. http://www.hbcredit.gov.cn/gywm/xyml/201909/P020190903352933734904.pdf.

79 Ministry of Agriculture and Rural Affairs of the People’s Republic of China, Memorandum of Cooperation on 

Jointly Punishing Seriously Dishonest Production and Distribution Entities and Their Relevant Personnel in the 

Field of Agricultural Supplies (关于对农资领域严重失信生产经营单位及其有关人员开展联合惩戒的合作备忘

录), February 23, 2017. Translation. http://webcache.googleusercontent.com/search?q=cache:http://www.jgj.moa.

gov.cn/xytx/201904/t20190418_6186180.htm.

80 State Taxation Administration of the People’s Republic of China, Memorandum of Cooperation on Joint Incentives for Trustworthy Enterprises in the Fields of Transportation Engineering and Construction (印发《关于对

交通运输工程建设领域守信典型企业实施联合激励的合作备忘录》的通知), February 28, 2018. Translation. 

http://webcache.googleusercontent.com/search?q=cache:http://www.chinatax.gov.cn/n810341/n810755/c3412441/

content.html.

81 Jeremy Daum, “Social Credit & the Law,” China Law Translate, July 29, 2020. https://www.chinalawtranslate.

com/en/social-credit-the-law.

82 Jeremy Daum, “Social Credit & the Law,” China Law Translate, July 29, 2020. https://www.chinalawtranslate.

com/en/social-credit-the-law.

83 State Administration for Industry and Commerce of the People’s Republic of China, “Creating a National 

Network - One of the Records of the Construction of the National Enterprise Credit Information Publicity System” (

织好织密 ‘全国一张网’—国家企业信用信息公示系统建设纪实之一), March 21, 2017. Translation. http://webcache.googleusercontent.com/search?q=cache:http://www.gov.cn/xinwen/2017-03/21/content_5179369.htm.

84 China Securities Regulatory Commission, Memorandum of Cooperation on Imposing Joint Punishment on 

Persons with Serious Financial Dishonesty (印发《关于对涉金融严重失信人实施联合惩戒的合作备忘录》的

通知), May 31, 2018. Translation. http://webcache.googleusercontent.com/search?q=cache:zfpvwPuO3GIJ:www.

csrc.gov.cn/pub/newsite/flb/flvcxjs/cxjslhjcbwl/201805/t20180531_338899.html+&cd=1&hl=en&ct=clnk&gl=ph.
84

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85 National Development and Reform Commission of the People’s Republic of China, the Supreme People’s 

Court and the Ministry of Land and Resources of the People’s Republic of China, Notice on Implementing Punitive Measures of Restrictions on Real Estate Transactions against Dishonest Persons Subject to Enforcement (关

于对失信被执行人实施限制不动产交易惩戒措施的通知), March 1, 2018. Translation. http://webcache.googleusercontent.com/search?q=cache:9mz97Gtz60wJ:www.gov.cn/xinwen/2018-03/16/content_5274726.htm+&cd=1&hl=en&ct=clnk&gl=ph.

86 National Development and Reform Commission and People’s Bank of China, Guiding Opinions on Strengthening and Regulating the Management of the List of Targets for Joint Incentives for Trustworthiness and Joint Punishment for Dishonesty (关于加强和规范守信联合激励和失信联合惩戒对象名单管理工作的指导意见), October 

30, 2017. Translation. https://webcache.googleusercontent.com/search?q=cache:hze2bITWZMEJ:https://www.ndrc.

gov.cn/xxgk/zcfb/ghxwj/201711/t20171103_960925.html+&cd=1&hl=en&ct=clnk&gl=ph.

87 Pan Ting, “Lian Weiliang: Credit Repair is not a Simple “Whitewashing the Record,” nor is it a Simple Way 

to “Get out of Punishment” (连维良:信用修复不是简单的“洗白记录” ,也不是简单的“退出惩戒”), National 

Business Daily, July 19. 2019. Translation. http://webcache.googleusercontent.com/search?q=cache:http://www.

nbd.com.cn/articles/2019-07-18/1355463.html.

88 Jeremy Daum, “Social Credit & the Law,” China Law Translate, July 29, 2020. https://www.chinalawtranslate.

com/en/social-credit-the-law.

89 Credit China, “Credit Repair Procedures Process Guide” (信用修复流程指引), Translation. https://www.creditchina.gov.cn/xyxf/lczy/.

90 General Office of the National Development and Reform Commission of the People’s Republic of China, 

Notice on Further Improving the ‘Credit China’ Website and Local Credit Portal Website Mechanisms for Credit 

Repair of Information on Administrative Punishments (国家发展改革委办公厅关于进一步完善“信用中国”网站

及地方信用门户网站行政处罚信息信用修复机制的通知), April 30, 2019. Translation. http://webcache.googleusercontent.com/search?q=cache:https://www.ndrc.gov.cn/xxgk/zcfb/tz/201905/t20190514_962445.html.

91 Geoffrey Smith, “OSI axes Shanghai firm that sold tainted food to KFC, McDonald’s,” Fortune, September 22, 

2014. https://fortune.com/2014/09/22/osi-axes-shanghai-firm-that-sold-tainted-food-to-kfc-mcdonalds.

92 Shanghai Food Safety Network, “Announcement Regarding the Key Supervision List of Serious Violator 

among Food and Drug Manufacturers and Related Responsible Persons (No. 2017004) (June 2, 2017)” (上海市食

品药品严重违法生产经营者与相关责任人员重点监管名单公告(2017004号)(2017年6月2日)), September 

22, 2014. Translation. http://www.spaq.sh.cn/renda/n36574/n36754/n36755/u1ai6245860.html.

93 Wu Chunwei, “Hufuxi Foods Produces Fake and Shoddy Products and is Included in the Illegal and Dishonest 

Enterprise Blacklist” (沪福喜食品生产伪劣产品 被纳入违法失信”黑名单”), Eastday, October 4, 2016. http://

sh.eastday.com/m/20161004/u1a9784299.html.

94 Caixin, “The Second Anniversary of Shanghai Fuxi’s Expired Meat Incident” (上海福喜过期肉事件两周年). 

Translation. http://special.caixin.com/event_0720_1/.

95 Qichacha, “OSI Investment Group” (欧喜投资). https://www.qcc.com/groupdetail_m0eb351db16f535e0550ead2fdccbf72.html.

96 Credit China, “Credit Repair Procedures Process Guide” (信用修复流程指引), Translation. https://www.creditchina.gov.cn/xyxf/lczy/.

97 Credit China, “Credit Repair Procedures Process Guide” (信用修复流程指引), Translation. https://www.creditchina.gov.cn/xyxf/lczy/.

98 State Administration for Market Regulation of the People’s Republic of China, Measures for the Administration 

of the List of Serious Illegal and Dishonest Acts (Draft for Comments) (严重违法失信名单管理办法 [修订草案征

求意见稿]), July 10, 2019. Translation. http://webcache.googleusercontent.com/search?q=cache:http://www.moj.
85

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gov.cn/news/content/2019-07/10/zlk_3227858.html. ; State Council of the People’s Republic of China, Transcript of 

the Policy Briefing of the State Council of the People’s Republic of China (国务院政策吹风会文字实录), July 18, 

2019. Translation. http://webcache.googleusercontent.com/search?q=cache:http://www.gov.cn/xinwen/2019zccfh/49/

wzsl.htm. ; “‘Credit China’ Website Administrative Penalty Information Credit Repair Guide (“信用中国”网站行政

处罚信息信用修复指南),” Credit China, July 1, 2019. Translation. https://www.creditchina.gov.cn/xyxf/xfzn/.

99 Stacey Vanek Smith and Cardiff Garcia, “What It’s Like to Be on the Blacklist in China’s New Social Credit 

System,” National Public Radio, October 31, 2018. https://www.npr.org/2018/10/31/662696776/what-its-like-to-beon-the-blacklist-in-chinas-new-social-credit-system.

100 Zhou Tailai and Matthew Walsh, “In Depth: How Chinese Companies Can Get Off Social Credit Blacklists,” 

Caixin, May 27, 2020. https://www.caixinglobal.com/2020-05-27/in-depth-how-chinese-companies-can-get-off-social-credit-blacklists-101559282.html.

101 “Action Plan on Implementing Joint Disciplinary Measures for Untrustworthy Subjects Related to Credibility 

in the Field of E-Commerce and the Sharing Economy (关于对电子商务及分享经济领域炒信行为相关失信主体

实施联合惩戒的行动计划), Credit China, January 9, 2018. Translation. https://www.creditchina.gov.cn/biaozhunguifan/hangyexingbiaozhunguifan/201801/t20180109_105897.html. ; State Council of the People’s Republic of China, The National Development and Reform Commission and other 8 Departments Jointly Issued the ‘Action Plan on 

Implementing Joint Disciplinary Measures for Untrustworthy Subjects Related to Credibility in the Field of E-Commerce and the Sharing Economy’ (国家发展改革委等8部门联合发布 ‘关于对电子商务及分享经济领域炒信行

为相关失信主体实施联合惩戒的行动计划’), November 11, 2016. Translation. http://webcache.googleusercontent.

com/search?q=cache:http://www.gov.cn/xinwen/2016-11/11/content_5131427.htm.

102 General Office of the State Council of the People’s Republic of China, Guiding Opinions of the General Office 

of the State Council on Accelerating the Construction of a Social Credit System and Building a New Credit-based 

Supervisory Mechanism (国务院办公厅关于加快推进社会信用体系建设构建以信用为基础的新型监管机制的

指导意见), July 16, 2019. Translation. http://webcache.googleusercontent.com/search?q=cache:http://www.gov.cn/

zhengce/content/2019-07/16/content_5410120.htm.

103 China Pharmaceutical Industry Association, Administrative Measures for the List of Untrustworthy Subjects 

in the Pharmaceutical Industry (Trial) (医药行业失信主体名单管理办法 (试行)), Credit China, November 19, 

2019. Translation. https://www.creditchina.gov.cn/hangyexinyong_824/faguiguifanbiaozhun/quanguoxinghangyexiehui/201911/t20191119_175873.html.

104 Larry Catá Backer, “And an Algorithm to Bind Them All? Social Credit, Data Driven Governance, and the 

Emergence of an Operating System for Global Normative Orders,” Entangled Legalities Workshop 24 & 25 May 

2018, May 21, 2018.

105 State Administration for Market Regulation, Exploring Credit Grading and Classification, and Strengthening 

Post-event Supervision (探索信用分级分类 加强事中事后监管), October 21, 2019. Translation. http://webcache.

googleusercontent.com/search?q=cache:42xf4inA2B4J:www.samr.gov.cn/zljds/sjdt/gzdt/201910/t20191021_307507.

html+&cd=1&hl=en&ct=clnk&gl=ph.

106 General Office of the State Council of the People’s Republic of China, Guiding Opinions of the General Office 

of the State Council on Accelerating the Construction of a Social Credit System and Building a New Credit-based 

Supervisory Mechanism (国务院办公厅关于加快推进社会信用体系建设构建以信用为基础的新型监管机制的

指导意见), July 16, 2019. Translation. http://webcache.googleusercontent.com/search?q=cache:http://www.gov.cn/

zhengce/content/2019-07/16/content_5410120.htm.

107 European Union Chamber of Commerce in China. “The Digital Hand: How China’s Corporate Social Credit 

System Conditions Market Actors.” August 28, 2019.

108 State Taxation Administration of the People’s Republic of China, Announcement on Issuing “Tax Payment 

Credit Evaluation Indicators and Evaluation Methods (Trial)” (关于发布《纳税信用评价指标和评价方式(试

行)》的公告), October 25, 2014. Translation. http://www.chinatax.gov.cn/n810341/n810765/n812141/n812242/
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c1078412/content.html?wscckey=3b691335dffeb926_1593333695. ; State Taxation Administration of the People’s Republic of China, Announcement on Issuing the “Tax Payment Credit Management Measures (Trial)” (关于

发布《纳税信用管理办法(试行)》的公告), July 4, 2014. Translation. http://webcache.googleusercontent.com/

search?q=cache:http://www.chinatax.gov.cn/n810341/n810755/c1150610/content.html.

109 Ministry of Ecology and Environment of the People’s Republic of China, Opinions on Further Deepening 

Ecological and Environmental Regulatory Services to Promote High-Quality Economic Development (关于进一步

深化生态环境监管服务推动经济高质量发展的意见), September 8, 2019. Translation. http://webcache.googleusercontent.com/search?q=cache:http://www.mee.gov.cn/xxgk2018/xxgk/xxgk03/201909/t20190911_733474.html.

110 Datong Health and Family Planning Commission, Datong City Medical Institution Credit Management 

Evaluation Implementation Plan (大同市卫生和计划生育委员会关于印发《大同市医疗机构信用管理

评价实施方案》的通知), November 13, 2017. Translation. http://www.dt.gov.cn/dtzww/tzggnr/201711/59b8594818da4508a7b1649127a20b77.shtml.

111 Ministry of Civil Affairs of the People’s Republic of China, Comprehensive Supervision Measures for Industry Associations and Chambers of Commerce (十部门印发《行业协会商会综合监管办法》), December 19, 

2016. Translation. http://webcache.googleusercontent.com/search?q=cache:P25NZmMroyYJ:www.gov.cn/xinwen/2016-12/29/content_5154008.htm+&cd=1&hl=en&ct=clnk&gl=ph.

112 China Construction Machinery Association, “Notice on the Issuance of the ‘Administrative Measures on 

Credit Rating Evaluation of Enterprises in the Chinese Construction Machinery Industry’” (关于发布《中国工程机

械行业企业信用等级评价管理办法》的通知), China Industrial News Network, May 7, 2020. Translation. https://

webcache.googleusercontent.com/search?q=cache:Uztjj7ISvNQJ:https://epaper.gmw.cn/gmrb/html/2019-08/04/

nw.D110000gmrb_20190804_4-03.htm+&cd=1&hl=en&ct=clnk&gl=ph.

113 Wuhan Software Industry Association, “Wuhan Software Enterprise Credit AAA Grade Certification Process 

and Requirements” (武汉市软件企业信用AAA等级证书办理流程和要求), May 9, 2020. Translation. https://

webcache.googleusercontent.com/search?q=cache:Uztjj7ISvNQJ:https://epaper.gmw.cn/gmrb/html/2019-08/04/

nw.D110000gmrb_20190804_4-03.htm+&cd=1&hl=en&ct=clnk&gl=ph.

114 China Industrial Gases Industry Association, China Gas Industry Enterprise Credit Rating Evaluation Management Measures (中国气体行业企业信用等级评价管理办法), August 3, 2017. Translation. http://www.cigia.org.cn/

uploads/soft/170803/14-1FP3141J9.pdf.

115 “Lian Weilang: Realize the Role of Industry Associations in Promoting the Social Credit System” (连维良:

发挥行业协会作用 更积极有效推动社会信用体系建设 ), Credit China, November 24, 2017. Translation. https://

www.creditchina.gov.cn/zhengcefagui/xianjixiance/201711/t20171121_96522.html.

116 National Development and Reform Commission of the People’s Republic of China, “Jointly Constructing the 

Shared Credit China System - Deputy Director Lian Weijing During the Meeting of Credit Bureaus” (共建共享信

用中国-连维良副主任主持出席部分征信机构座谈会), May 17, 2016. Translation. http://webcache.googleusercontent.com/search?q=cache:https://www.ndrc.gov.cn/fzggw/jgsj/cjd/sjdt/201605/t20160517_1111376.html. ; Wen 

Yuan, “Promote the high-quality development of the enterprise credit market” (推动企业征信市场高质量发展), 

Guang Ming Daily, August 4, 2019. Translation. https://webcache.googleusercontent.com/search?q=cache:Uztjj7ISvNQJ:https://epaper.gmw.cn/gmrb/html/2019-08/04/nw.D110000gmrb_20190804_4-03.htm+&cd=1&hl=en&ct=-

clnk&gl=ph. ; General Office of the National Development and Reform Commission of the People’s Republic 

of China, Notice of the General Office of the National Development and Reform Commission on Promoting and 

Applying the Comprehensive Evaluation Results of the Public Credit of Market Subjects (国家发展改革委办公

厅关于推送并应用市场主体公共信用综合评价结果的通知), September 1, 2019. Translation. http://webcache.

googleusercontent.com/search?q=cache:http://www.gov.cn/xinwen/2019-09/16/content_5430181.htm.

117 National Public Credit Information Center of People’s Republic of China, “Announcement of the Comprehensive Evaluation Results (Phase 3) of the Public Credit of Some Road Passenger Transport Enterprises” (关于公布部

分道路客运企业公共信用综合评价结果 [第三期] 的公告), May 15, 2019. Translation. http://fgw.nmg.gov.cn/xynmg/gndt/4428.jhtml. ; National Public Credit Information Center, “Comprehensive Evaluation Results of the Public 
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Credit of Some Natural Gas Related Enterprises (Phase IV)” (涉部分天然气领域企业公共信用综合评价结果(第

四期)), June 20, 2019. Translation. https://www.creditchina.gov.cn/xinxigongshi/strqqy/201906/t20190620_159295.

html.

118 General Office of the National Development and Reform Commission of the People’s Republic of China, 

Notice of the General Office of the National Development and Reform Commission on Promoting and Applying the 

Comprehensive Evaluation Results of the Public Credit of Market Subjects (国家发展改革委办公厅关于推送并应

用市场主体公共信用综合评价结果的通知), September 1, 2019. Translation. http://webcache.googleusercontent.

com/search?q=cache:http://www.gov.cn/xinwen/2019-09/16/content_5430181.htm; Credit China, “Comprehensive 

Evaluation Results of Public Credit,” https://www.creditchina.gov.cn/xinxigongshi/strqqy/.

119 General Office of the National Development and Reform Commission of the People’s Republic of China, 

Notice of the General Office of the National Development and Reform Commission on Promoting and Applying the 

Comprehensive Evaluation Results of the Public Credit of Market Subjects (国家发展改革委办公厅关于推送并应

用市场主体公共信用综合评价结果的通知), September 1, 2019. Translation. http://webcache.googleusercontent.

com/search?q=cache:http://www.gov.cn/xinwen/2019-09/16/content_5430181.htm.

120 “National Development and Reform Commission of the People’s Republic of China: Promote and Apply the 

Comprehensive Evaluation Results of the Public Credit of Market Subjects” (发改委:推送并应用市场主体公共

信用综合评价结果), Shanghai Securities News, September 16, 2019. Translation. http://webcache.googleusercontent.com/search?q=cache:http://news.cnstock.com/news,bwkx-201909-4430717.htm.

121 National Development and Reform Commission of the People’s Republic of China, “Lian Weiliang, Deputy 

Director, State Council Policy Routine Briefing, Question Two: About the Comprehensive Evaluation System of 

Public Credit” (连维良副主任国务院政策例行吹风会答问之二:关于公共信用综合评价制度), July 24, 2019. 

Translation. http://webcache.googleusercontent.com/search?q=cache:https://www.ndrc.gov.cn/fzggw/jgsj/zys/

sjdt/201907/t20190724_970461.html.

122 State Council of the People’s Republic of China, Guiding Opinions of the State Council on Vigorously 

Advancing “Internet Plus” (国务院关于积极推进“互联网+”行动的指导意见), July 4, 2015. Translation. http://

webcache.googleusercontent.com/search?q=cache:Ya82k-pxBvkJ:www.gov.cn/zhengce/content/2015-07/04/content_10002.htm+&cd=1&hl=en&ct=clnk&gl=ph.

123 General Office of the Hubei Provincial Government, Hubei Province ‘Internet + Supervision’ System Construction Plan (湖北省“互联网+监管”系统建设方案), July 29, 2019. Translation. http://webcache.googleusercontent.com/search?q=cache:PN6lJPqUvbIJ:www.hubei.gov.cn/govfile/ezbh/201908/t20190823_1408363.shtml+&cd=1&hl=en&ct=clnk&gl=ph.

124 General Office of the State Administration for Market Regulation of the People’s Republic of China, Notice on 

the Implementation of Enterprise Credit Risk Classification Management Pilots in Some Regions (关于在部分地区

开展企业信用风险分类管理工作试点的通知), September 2, 2019. Translation. http://zjj.fujian.gov.cn/wj/201910/

P020191018621976110866.pdf.

125 European Union Chamber of Commerce in China. “The Digital Hand: How China’s Corporate Social Credit 

System Conditions Market Actors.” August 28, 2019. ; China Government Procurement Network, “National Government Service Platform ‘Internet + Supervision’ Application System Construction Project Winning Announcement” (国家政务服务平台“互联网+监管”应用系统建设项目中标公告), August 3, 2017. Translation. http://www.

ccgp.gov.cn/cggg/zygg/zbgg/201903/t20190321_11786081.htm. 

126 Henan Daily, “Henan Explores ‘One-stop Online Government Administration’ Henan Leads the Country in 

Constructing its ‘Internet + Supervision’ System” (‘一网通管’ 的河南探索 我省 ‘互联网+监管’ 系统建设走在

全国前列), Henan Big Data Administration, December 24, 2019. Translation. https://webcache.googleusercontent.

com/search?q=cache:ZEaEV9WPUAkJ:https://dsj.henan.gov.cn/2019/12-24/1101428.html+&cd=1&hl=en&ct=-

clnk&gl=ph.

127 Zhejiang Provincial Development and Reform Commission, Notice of the Provincial Development and Re-
88

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form Commission on Printing and Distributing the “Guidelines for the Evaluation of the Public Credit of Five Types 

of Subjects in Zhejiang Province (2019 Version)” (省发展改革委关于印发《浙江省五类主体公共信用评价指

引(2019版)》的通知), August 9, 2019. Translation. http://webcache.googleusercontent.com/search?q=cache:xfybUXYRQBcJ:fzggw.zj.gov.cn/art/2019/8/9/art_1599552_36655868.html+&cd=1&hl=en&ct=clnk&gl=ph.

128 General Office of Zhejiang Provincial People’s Government, “Credit ‘531X’ Project” (信用“531X”工程), 

Zhejiang Government Service Network. Translation. http://webcache.googleusercontent.com/search?q=cache:WzgACEntcLMJ:zld.zjzwfw.gov.cn/art/2020/4/10/art_1229004464_42545501.html+&cd=1&hl=en&ct=clnk&gl=ph.

129 Karen Yeung, “Algorithmic Regulation: A Critical Interrogation,” TLI Think! Paper 62/2017 (May 2017). 

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2972505.

130 Karen Yeung, “Algorithmic Regulation: A Critical Interrogation,” TLI Think! Paper 62/2017 (May 2017). 

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2972505.

131 John E. Baiden, “The 5 C’s of Credit in the Lending Industry,” June 26, 2011. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1872804.

132 Lin Junyue, “Credit Concepts” (信用概念) in Principles of the Social Credit System (社会信用体系原理), 

China Fangzheng Press, January December 2002, 2-24. Translation. 

133 Credit Reference Center of the People’s Bank of China, “Explanation of the Personal Credit Report (Personal 

Version)” (个人信用报告(个人版)解读), January 14, 2014. Translation. http://webcache.googleusercontent.com/

search?q=cache:http://www.pbccrc.org.cn/zxzx/grzx/201401/dcf00b0b7b88405280dd0b7923c09fda.shtml.

134 World Bank Group, “The Global Findex Database 2017: Measuring Financial Inclusion and the Fintech Revolution”. https://globalfindex.worldbank.org/sites/globalfindex/files/chapters/2017%20Findex%20full%20report_chapter2.pdf.

135 Virgilio Bisio, “China’s Banking Sector Risks and Implications for the United States,” U.S.-China Economic and 

Security Review Commission, May 27, 2020. 

136 Zhao Meng, “Central Bank Media: It is Difficult to Resolve the Financing Problem of Private Enterprises (

央行媒体:化解民企融资难须跳出’唯抵押物论’)”, Finance Daily, November 27, 2018. https://webcache.

googleusercontent.com/search?q=cache:wp4cOFTMbfoJ:https://www.financialnews.com.cn/gc/sd/201811/

t20181127_150132.html+&cd=1&hl=en&ct=clnk&gl=ph.

137 Legal Daily, “Analysis of the Three Major Focuses of the New Report on Social Credit” (新版个人征信

报告三大焦点解析), April 19, 2019. Translation. http://www.legaldaily.com.cn/locality/content/2019-04/19/content_7835493.htm. 

138 CFPB Office of Research. “Data Point: Credit Invisibles,” Consumer Financial Protection Bureau, May 2015. 

https://files.consumerfinance.gov/f/201505_cfpb_data-point-credit-invisibles.pdf. ; Experian, “New Experian credit 

score may improve access to credit for more than 40 million credit invisibles,” PR Newswire, November 7, 2019. 

https://www.prnewswire.com/news-releases/new-experian-credit-score-may-improve-access-to-credit-for-more-than40-million-credit-invisibles-300953246.html . 

139 Record of Zhu Rongji’s Speeches Volume III (朱镕基讲话实录 第三卷), People’s Publishing House, 2011, 37.

140 Record of Zhu Rongji’s Speech Volume III (朱镕基讲话实录 第三卷), People’s Publishing House, 2011, 275.

141 People’s Bank of China and China Banking and Insurance Regulatory Commission, 2018 China Small and 

Micro Enterprises Financial Services Report (中国小微企业金融服务报告[2018]), China Financial Publishing 

House, June 2019. Translation. : Scott Kennedy, “China’s Emerging Credit Rating Industry: The Official Foundations of Private Authority,” The China Quarterly 193 (March 2008): 65-83. 

142 “Government Work Report - Second Session of the Thirteenth National People’s Congress March 5, 

2019 (政府工作报告—2019年3月5日在第十三届全国人民代表大会第二次会议上),” Xinhua, March 5, 
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2019. Translation. http://webcache.googleusercontent.com/search?q=cache:http://www.xinhuanet.com/politics/2019-03/05/c_1124194454.htm.

143 “General Office of the CPC Central Committee, General Office of the State Council: Opinions on Promoting 

the Healthy Development of Small and Medium-sized Enterprises” (中共中央办公厅 国务院办公厅印发 [关于

促进中小企业健康发展的指导意见]), Xinhua, April 7, 2019. Translation. http://webcache.googleusercontent.

com/search?q=cache:JbajF3t4zaQJ:www.xinhuanet.com/2019-04/07/c_1124335674.htm+&cd=1&hl=en&ct=-

clnk&gl=ph; National Development and Reform Commission of the People’s Republic of China and China Banking 

and Insurance Regulatory Commission, NDRC and CBIRC Jointly Issue ‘Notice on Further Developing ‘Xinyi 

Loan’ to Support the Financing of Micro, Small, and Medium-sized Micro Enterprises (国家发展改革委、银保监

会联合印发[关于深入开展 ‘信易贷’ 支持中小微企业融资的通知]), September 21, 2019. Translation. http://webcache.googleusercontent.com/search?q=cache:AMATxedoVIcJ:www.gov.cn/xinwen/2019-09/21/content_5431882.

htm+&cd=1&hl=en&ct=clnk&gl=ph.

144 Scott Kennedy, “China’s Emerging Credit Rating Industry: The Official Foundations of Private Authority,” The 

China Quarterly 193 (March 2008): 65-83. 

145 Miles Livingston et al., “Are Chinese Credit Ratings Relevant? A Study of the Chinese Bond Market and 

Credit Rating Industry,” Journal of Banking & Finance 87 (February 2018): 216-232. 

146 Scott Kennedy, “China’s Emerging Credit Rating Industry: The Official Foundations of Private Authority,” 

The China Quarterly 193 (March 2008): 65-83.

147 John E. Baiden, “The 5 C’s of Credit in the Lending Industry,” June 26, 2011. https://papers.ssrn.com/sol3/

papers.cfm?abstract_id=1872804. ; Lin Junyue, “The Credit Market and its Data Environment” (征信市场及其数

据环境) in Principles of the Social Credit System (社会信用体系原理), China Fangzheng Press, December 2002, 

61-122. Translation.

148 Scott Kennedy, “China’s Emerging Credit Rating Industry: The Official Foundations of Private Authority,” 

The China Quarterly 193 (March 2008): 65-83.

149 Xiaofei Jinrong Fengkong Lianmeng, “List of 130 National Credit Reporting Agencies (全国企业征信机

构备案数量130家名单 ),” Sohu, July 2, 2019. Translation. http://webcache.googleusercontent.com/search?q=-

cache:azECeQ4A0eoJ:www.sohu.com/a/324254065_99917536+&cd=1&hl=en&ct=clnk&gl=ph. 

150 “Letter Regarding the Introduction of Third-party Credit Service Agencies to Participate in Multi-field and 

Specific Field Industry Credit Construction and Credit Supervision” (关于引入第三方信用服务机构协同参与多

领域及特定领域行业信用建设和信用监管工作的函), Credit China, October 16, 2017. Translation. https://www.

creditchina.gov.cn/toutiaoxinwen/201710/t20171016_57942.html.

151 National Development and Reform Commission of the People’s Republic of China, “Jointly Constructing the 

Shared Credit China System - Deputy Director Lian Weijing During the Meeting of Credit Bureaus” (共建共享信

用中国-连维良副主任主持出席部分征信机构座谈会), May 17, 2016. Translation. http://webcache.googleusercontent.com/search?q=cache:https://www.ndrc.gov.cn/fzggw/jgsj/cjd/sjdt/201605/t20160517_1111376.html. ; Wen 

Yuan, “Promote the high-quality development of the enterprise credit market (推动企业征信市场高质量发展),” 

Guang Ming Daily, August 4, 2019. Translation. https://webcache.googleusercontent.com/search?q=cache:Uztjj7ISvNQJ:https://epaper.gmw.cn/gmrb/html/2019-08/04/nw.D110000gmrb_20190804_4-03.htm+&cd=1&hl=en&ct=-

clnk&gl=ph.

152 General Office of the National Development and Reform Commission of the People’s Republic of China, 

Notice of the General Office of the National Development and Reform Commission on Promoting and Applying the 

Comprehensive Evaluation Results of the Public Credit of Market Subjects (国家发展改革委办公厅关于推送并应

用市场主体公共信用综合评价结果的通知), September 1, 2019. Translation. http://webcache.googleusercontent.

com/search?q=cache:http://www.gov.cn/xinwen/2019-09/16/content_5430181.htm.

153 Ministry of Housing and Urban-Rural Development of the People’s Republic of China, “Joint Punishment 

Records” (失信联合惩戒记录), http://jzsc.mohurd.gov.cn/since/punish.
90

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154 China Government Procurement Network, “List of Records of Serious, Illegal, and Untrustworthy Acts in 

Government Procurement” (政府采购严重违法失信行为记录名单). http://www.ccgp.gov.cn/search/cr/.

155 Ministry of Culture and Tourism of the People’s Republic of China, “National Tourism Regulatory Service 

Platform” (全国旅游监管服务平台). http://jianguan.12301.cn/.

156 Supreme People’s Court of the People’s Republic of China, “China Legal Enforcement Information Disclosure Network” (中国执行信息公开网), http://zxgk.court.gov.cn/shixin/.

157 China Government Procurement Network, “National Credit Information Sharing Platform Project (Phase 2) 

(National Information Center Construction Portion) ‘Credit China’ Announcement of the Winning Bid for the Website Upgrade and Software Customization Project” (全国信用信息共享平台项目 [二期] [国家信息中心建设部

分] ‘信用中国’ 网站升级改版软件定制开发项目中标公告), August 3, 2017. Translation. http://www.ccgp.gov.cn/

cggg/zygg/zbgg/201708/t20170803_8628900.htm.

158 China Government Procurement Network, “National Credit Information Sharing Platform Project (Phase 2) 

(National Information Center Construction Portion) Announcement of the Winning Bid for the Credit China Mobile 

Application and Service System Custom Development Project” (全国信用信息共享平台项目[二期] [国家信息中

心建设部分] 信用中国移动应用及服务支撑系统定制开发项目中标公告), August 12, 2019. Translation. http://

www.ccgp.gov.cn/cggg/zygg/zbgg/201908/t20190812_12665053.htm.

159 China Government Procurement Network, “National Credit Information Sharing Platform Project (Phase 2) 

(National Information Center Construction Portion) Announcement of the Winning Bid for the Partial Software and 

Hardware System Integration, Partial Application System Demand Analysis and Detailed Design, and Data Exchange Platform Custom Development Project” (全国信用信息共享平台项目 [二期] [国家信息中心建设部分] 部

分软硬件系统集成, 部分应用系统需求分析及详细设计, 数据交换平台定制开发项目建设中标公告), November 14, 2017. Translation. http://www.ccgp.gov.cn/cggg/zygg/zbgg/201711/t20171114_9161418.htm.

160 Xuancheng City Information Work Office, “Bidding Announcement for the Procurement Project of the 

City and County Integrated Public Credit Information Sharing Service Platform” (市县一体化公用信用信息

共享服务平台采购项目招标公告), June 1, 2017. Translation. http://www.ccgp.gov.cn/cggg/dfgg/gkzb/201706/

t20170601_8319825.htm.

161 Sugon, “Won the National Information Center Bid to Help Build a National Credit Information Sharing 

Platform” (中标国家信息中心,助力全国信用信息共享平台建设), Kuaibao, December 4, 2018. Translation. https://webcache.googleusercontent.com/search?q=cache:tMhpLUYlYKQJ:https://www.sugon.com/cut%-

3Fid%3D968%26nav_id%3D48+&cd=1&hl=en&ct=clnk&gl=ph.

162 National Development and Reform Commission of the People’s Republic of China, Explanation of the Credit 

Information Collection Interface of the National Credit Information Sharing Platform (全国信用信息共享平台信

用信息归集接口说明), DOC Appendix 3, June 2019. Translation. http://www.hbcredit.gov.cn/gywm/xyml/201909/

P020190903352933990385.pdf.

163 State Administration for Industry and Commerce of the People’s Republic of China, “Creating a National 

Network - One of the Records of the Construction of the National Enterprise Credit Information Publicity System” (

织好织密 ‘全国一张网’—国家企业信用信息公示系统建设纪实之一), March 21, 2017. Translation. http://webcache.googleusercontent.com/search?q=cache:http://www.gov.cn/xinwen/2017-03/21/content_5179369.htm.

164 Yichun Economic and Technical Development Zone, “Online Monitoring Platform for Pollution Sources in 

District is Officially Put into Use” (我区污染源在线监控平台正式投入使用), January 5, 2018. Translation. http://

jkq.yichun.gov.cn/news-show-1176.html. ; Environmental Protection Bureau of Yichun Economic Development 

Zone, “There is a ‘Weapon’ for Environmental Protection in the Economic Development Zone! Online Monitoring 

Platform Officially Put into Use” (经开区环境保护有“利器”!在线监控平台正式投入使用 ), Sohu, January 3, 

2018. Translation. https://www.sohu.com/a/214441348_664462.

165 Changshu High-tech Industrial Development Zone, “Changshu High-tech Zone Implements ‘No Disturbance 

Supervision’” (常熟高新区实施“无打扰监管”), March 18, 2020. Translation. http://www.changshu.gov.cn/zgcs/
91

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InfoDetail/Default.aspx?infoid=106ebfee-6f3c-4436-ab76-288eae4b348c,001006007.

166 Zhang Liu, “Benefits for Enterprises with ‘One-Stop’ Service,” (惠企服务“最多点一次”), Zhejiang Daily, 

March 2, 2020. Translation. http://zjrb.zjol.com.cn/html/2020-03/03/content_3310216.htm?div=-1.

167 Yongxi Chen and Anne S. Y. Cheung, “The Transparent Self Under Big Data Profiling: Privacy and Chinese 

Legislation on the Social Credit System,” The Journal of Comparative Law 12:2 (June 2017): 356-378.

168 Rogier Creemers, “China’s Social Credit System: An Evolving Practice of Control,” May 2018. https://papers.

ssrn.com/sol3/papers.cfm?abstract_id=3175792.

169 Robert Brauneis and Ellen P. Goodman, “Algorithmic Transparency for the Smart City” Yale Journal of Law & 

Technology, Volume 20, 2018. https://yjolt.org/sites/default/files/20_yale_j._l._tech._103.pdf.

170 Roger Creemers and China Law Translate trans., “State Council Notice Concerning Issuance of the Planning 

Outline for the Establishment of a Social Credit System (2014-2020),” State Council of the People’s Republic of China, 

April 27, 2015. https://www.chinalawtranslate.com/en/socialcreditsystem/.

171 State Administration for Market Regulation of the People’s Republic of China, “2019 Overview of the Development of the National Market” (2019年全国市场主体发展基本情况), March 5, 2020. Translation. http://www.

samr.gov.cn/sj/tjsj/202003/t20200305_312509.html; China Organization Data Service, “Code Data”, accessed May 

1, 2020. Translation. https://www.cods.org.cn/sjzs/dmsj.

172 Credit Shenyang, “National Public Credit Information Center Documents” (国家公共信用信息中心文件), 

March 31, 2020. Translation. http://webcache.googleusercontent.com/search?q=cache:_sHEd9WhdvUJ:xysy.shenyang.gov.cn/contents/31/91120.html+&cd=1&hl=en&ct=clnk&gl=ph.

173 Shanghai Public Credit Information Service Center, Operational Status Report (运行情况报告), 2019. Translation. http://www.creditshanghai.org.cn/resource/upload/cxw/201905/23103028syuo.pdf.

174 China Government Procurement Network, “Public Bidding for Constructing the Integrated Social Credit Platform of Each City in Yunnan Province” (云南省各州市社会信用平台一体化建设项目中标公示), December 20, 

2019. Translation. http://webcache.googleusercontent.com/search?q=cache:K-QSYoQRZJIJ:www.ccgp.gov.cn/cggg/

dfgg/zbgg/201912/t20191220_13609456.htm+&cd=1&hl=en&ct=clnk&gl=ph.

175 Xiamen Social Credit System Construction Leading Group Office, Notice on the Inclusion of Behaviors in 

Credit Records and the Implementation of Credit Rewards and Punishments According to Law During the Novel 

Coronavirus Pneumonia Epidemic Prevention and Control Period (关于在新冠肺炎疫情防控期间将有关行为

列入信用记录依法实施信用奖惩的通知), February 17, 2020. Translation. http://www.xm.gov.cn/zxgg/202002/

t20200220_2423189.htm.

176 Li Mu, “The Use of Blacklists Should be Regulated by Unified Legislation” (黑名单的运用应统一立法予

以规制), Legal Daily, December 11, 2019. Translation. http://webcache.googleusercontent.com/search?q=cache:i9yoJ6txdSoJ:www.legaldaily.com.cn/commentary/content/2019-12/11/content_8071205.htm+&cd=1&hl=en&ct=-

clnk&gl=ph.

177 National Development and Reform Commission and People’s Bank of China, Guiding Opinions on Further 

Regulating the Scope of Inclusion of Public Credit Information, Punishment for Untrustworthiness, and Credit 

Restoration to Build a Long-term Mechanism for Credit Construction (Draft for Solicitation of Comments) (关于进

一步规范公共信用信息纳入范围、失信惩戒和信用修复构建诚信建设长效机制的指导意见(征求意见稿)), 

July 22, 2020. Translation. https://hd.ndrc.gov.cn/yjzx/yjzx_add.jsp?SiteId=339.

178 “The National Development and Reform Commission Organized a Social Credit Legislation Forum,” Interface 

News, September 2, 2019. https://baijiahao.baidu.com/s?id=1643532806855141610.

179 Wikisource, “13th NPCSC Legislative Plan”. https://zh.wikisource.org/wiki/User:NPCObserver/13thNPCSCLegislativePlan.
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180 Standing Committee of Shanghai Municipal People’s Congress, China (Shanghai) Pilot Free Trade Zone 

Regulations (中国[上海]自由贸易试验区条例), 39, July 25, 2014. Translation. http://webcache.googleusercontent.com/search?q=cache:aXgJVoD3Jq4J:www.shanghai.gov.cn/nw2/nw2314/nw32419/nw32510/nw32512/

u26aw40132.html+&cd=1&hl=en&ct=clnk&gl=ph.

181 Standing Committee of Shanghai Municipal People’s Congress, Shanghai Social Credit Regulations (上海市

社会信用条例), July 23, 2017. Translation. http://webcache.googleusercontent.com/search?q=cache:QE0bO7hK3sEJ:www.spcsc.sh.cn/n1939/n2440/n3898/u1ai149901.html+&cd=1&hl=en&ct=clnk&gl=ph; Shanghai Municipal 

People’s Government, Measures of Shanghai Municipality on the Collection and Use of Public Credit Information (

上海市公共信用信息归集和使用管理办), December 23, 2015. Translation. http://webcache.googleusercontent.

com/search?q=cache:klxtdI7jfWwJ:www.shanghai.gov.cn/nw2/nw2314/nw2319/nw12344/u26aw46212.html+&cd=1&hl=en&ct=clnk&gl=ph.

182 Jiangsu Provincial Government, Jiangsu Province Social Credit Regulations (Draft for Comments) (江苏

省社会信用条例(草案) [征求意见稿]), April 28, 2020. Translation. https://webcache.googleusercontent.com/

search?q=cache:LR6aDvMKDxMJ:https://credit.suzhou.gov.cn/news/show/370099.html+&cd=1&hl=en&ct=-

clnk&gl=ph.

183 Laurie Burkitt and Colum Murphy, “China Using Antimonopoly Law to Pressure Foreign Businesses,” Wall 

Street Journal, August 4, 2014. https://www.wsj.com/articles/china-using-antimonopoly-law-to-pressure-foreign-businesses-1407154916.

184 Xia Xutian, “Ministry of Commerce: 20 New Measures to Stabilize Foreign Investment are Coming Soon” (

商务部:20条稳外资新措施即将出台), 21st Century Business Herald, October 30, 2019. Translation. http://webcache.googleusercontent.com/search?q=cache:vvOrsscnPN0J:www.21jingji.com/2019/10-30/2NMDEzNzlfMTUxNDY2Nw.html+&cd=1&hl=en&ct=clnk&gl=ph.

185 Credit China, “Google Information Technology (China) Co., Ltd.” (谷歌信息技术(中国)有限公司). 

https://www.creditchina.gov.cn/xinyongxinxixiangqing/xyDetail.html?searchState=1&entityType=1&keyword=%E8%B0%B7%E6%AD%8C%E4%BF%A1%E6%81%AF%E6%8A%80%E6%9C%AF(%E4%B8%AD%

E5%9B%BD)%E6%9C%89%E9%99%90%E5%85%AC%E5%8F%B8&uuid=62a6ee4bcc209eb5f7193ef787b27b53&tyshxydm=91110108795101314G. 

186 Credit China, “Federal Express (China) Co.,Ltd.” (联邦快递(中国)有限公司). https://

www.creditchina.gov.cn/xinyongxinxixiangqing/xyDetail.html?searchState=1&entityType=1&keyword=%E8%81%94%E9%82%A6%E5%BF%AB%E9%80%92(%E4%B8%AD%E5%9B%BD)%E6%9

C%89%E9%99%90%E5%85%AC%E5%8F%B8&uuid=48d45498494d36914813e8dd9e5744af&tyshxy

dm=911100007109207250.

187 Mark Bergen, “Google in China: When ‘Don’t Be Evil’ Met the Great Firewall,” Bloomberg Businessweek, 

November 9, 2018. https://www.bloomberg.com/news/features/2018-11-08/google-never-stopped-trying-to-go-tochina. ; Jane Li, “China Says FedEx Lied about its ‘Mishandling’ of Huawei Packages,” Quartz, July 26, 2019. https://

qz.com/1675374/china-suspects-fedex-of-violating-laws/.

188 Qichacha, “Tianjin Binhai New Area State-Owned Commercial Investment Group Co., Ltd.” (天津市滨海新

区国有商业投资集团有限公司). https://www.qcc.com/firm/51N4KS9.shtml#susong.

189 Qichacha, “Sichuan Coal Industry Group Co., Ltd.” (四川省煤炭产业集团有限责任公司). https://www.qcc.

com/firm/2720GBO.shtml.

190 Qichacha, “Shenyang Hunnan Water Group Co., Ltd.” (沈阳浑南水务集团有限公司). https://www.qcc.com/

firm/ddd58a7eea835b885099cdb719c9e66b.html.

191 Qichacha, “Yinchuan Cultural Tourism Investment Group Co., Ltd.” (银川文化旅游投资集团有限公司). 

https://www.qcc.com/firm/1b93c3a3543409ea175fd764485ea82c.html.

192 Ministry of Commerce of the People’s Republic of China, Measures for Reporting Foreign Investment In-
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formation (Draft for Comments) (外商投资信息报告办法(征求意见稿)), November 8, 2019. Translation. http://

webcache.googleusercontent.com/search?q=cache:http://www.mofcom.gov.cn/article/b/g/201911/20191102915702.

shtml. 

193 Ministry of Commerce of the People’s Republic of China and the State Administration for Market Regulation 

of the People’s Republic of China, Measures for the Reporting of Foreign Investment Information (外商投资信息报

告办法), December 30, 2019. Translation. http://webcache.googleusercontent.com/search?q=cache:e5mskC2tsAYJ:www.gov.cn/zhengce/content/2019-02/15/content_5365945.htm+&cd=1&hl=en&ct=clnk&gl=ph.

194 American Chamber of Commerce in the People’s Republic of China, “2020 China Business Climate Survey 

Report,” March 2020. https://www.amchamchina.org/policy-advocacy/business-climate-survey/.

195 Office of the United States Trade Representative, Findings of the Investigation into China’s Acts, Policies, and 

Practices Related to Technology Transfer, Intellectual Property, and Innovation Under Section 301 of the Trade Act 

of 1974, March 22, 2018. https://ustr.gov/sites/default/files/Section%20301%20FINAL.PDF.

196 Jing Zhan, “The Art of Political Ambiguity: Top-down Intergovernmental Information Asymmetry in China,” 

Journal of Chinese Governance, 2017. https://www.researchgate.net/publication/309634977_The_Art_of_Political_Ambiguity_Top-down_Intergovernmental_Information_Asymmetry_in_China.

197 State Council of the People’s Republic of China, Opinions of the State Council on Comprehensively Implementing the Joint Regulation of Random Selection of Subjects and Inspectors and Public Disclosure by Departments 

in Market Regulation (国务院关于在市场监管领域全面推行部门联合“双随机、一公开”监管的意见), January 27, 2019. Translation. http://webcache.googleusercontent.com/search?q=cache:e5mskC2tsAYJ:www.gov.cn/

zhengce/content/2019-02/15/content_5365945.htm+&cd=1&hl=en&ct=clnk&gl=ph.

198 Jeremy Daum, “China through a Glass, Darkly,” China Law Translate, December 24, 2017. https://www.

chinalawtranslate.com/en/china-social-credit-score.

199 Jeremy Daum, “China through a Glass, Darkly,” China Law Translate, December 24, 2017. https://www.

chinalawtranslate.com/en/china-social-credit-score.

200 State Administration for Market Regulation of the People’s Republic of China, Measures for the Administration of the List of Serious Illegal and Dishonest Acts (Draft for Soliciting Comments) (严重违法失信名单管

理办法 [修订草案征求意见稿]), July 10, 2019. Translation. http://webcache.googleusercontent.com/search?q=-

cache:http://www.moj.gov.cn/news/content/2019-07/10/zlk_3227858.html.

201 Ministry of Finance of the People’s Republic of China, Notice of the Ministry of Finance on the Inquiry and 

Use of Credit Records in Government Procurement Activities (财政部关于在政府采购活动中查询及使用信用记

录有关问题的通知), August 1, 2016. Translation. http://www.ccgp.gov.cn/zcfg/mof/201608/t20160811_7169275.

htm.

202 General Office of the State Council of the People’s Republic of China, Guiding Opinions of the General Office 

of the State Council on Accelerating the Construction of a Social Credit System and Building a New Credit-based 

Supervisory Mechanism (国务院办公厅关于加快推进社会信用体系建设构建以信用为基础的新型监管机制的

指导意见), Article 17, July 16, 2019. Translation. http://webcache.googleusercontent.com/search?q=cache:http://

www.gov.cn/zhengce/content/2019-07/16/content_5410120.htm.

203 Ministry of Public Security of the People’s Republic of China, Regulation on Graded Cybersecurity Protections (Draft for Solicitation of Comments) (网络安全等级保护条例(征求意见稿), June 27, 2018. Translation. 

https://www.mps.gov.cn/n2254536/n4904355/c6159136/content.html.

204 Yongxi Chen and Anne S. Y. Cheung, “The Transparent Self Under Big Data Profiling: Privacy and Chinese 

Legislation on the Social Credit System,” The Journal of Comparative Law 12:2 (June 2017): 356-378.

205 Ministry of Commerce of the People’s Republic of China and the State Administration for Market Regulation 

of the People’s Republic of China, Measures for Reporting Foreign Investment Information (外商投资信息报告办
94

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法), December 30, 2019. Translation. http://webcache.googleusercontent.com/search?q=cache:v8dXX4JUx2wJ:www.fdi.gov.cn/1800000121_23_75233_0_7.html+&cd=1&hl=en&ct=clnk&gl=ph.

206 Ministry of Commerce of the People’s Republic of China and the State Administration for Market Regulation 

of the People’s Republic of China, Measures for Reporting Foreign Investment Information (外商投资信息报告办

法), December 30, 2019. Translation. http://webcache.googleusercontent.com/search?q=cache:v8dXX4JUx2wJ:www.fdi.gov.cn/1800000121_23_75233_0_7.html+&cd=1&hl=en&ct=clnk&gl=ph.

207 Suzhou Development and Reform Commission, Implementation Plan to Accelerate the Construction of the 

Kunshan Social Credit System and Build a New Regulatory Mechanism Based on Credit (关于加快推进昆山社会

信用体系建设构建以信用为基础的新型监管机制的实施方案), April 9, 2020. Translation. https://www.suzhou.

gov.cn/szsshyhtxjs/xgzx/202004/34bc0b1bdbcf4c2caf7530e512789169.shtml; General Office of the State Council 

of the People’s Republic of China, Guiding Opinions of the General Office of the State Council on Accelerating the 

Construction of a Social Credit System and Building a New Credit-based Supervisory Mechanism (国务院办公厅

关于加快推进社会信用体系建设构建以信用为基础的新型监管机制的指导意见), July 16, 2019. Translation. 

http://webcache.googleusercontent.com/search?q=cache:http://www.gov.cn/zhengce/content/2019-07/16/content_5410120.htm.

208 General Office of the National Development and Reform Commission of the People’s Republic of China, 

Notice on Further Improving the “Credit China” Website and Local Credit Portal Website Mechanisms for Credit 

Repair of Information on Administrative Punishments (国家发展改革委办公厅关于进一步完善“信用中国”网站

及地方信用门户网站行政处罚信息信用修复机制的通知), April 30, 2019. Translation. http://webcache.googleusercontent.com/search?q=cache:https://www.ndrc.gov.cn/xxgk/zcfb/tz/201905/t20190514_962445.html.

209 Cyberspace Administration of China, Measures on Credit Administration for Seriously Untrustworthy 

Internet Information Services Entities (互联网信息服务严重失信主体信用信息管理办法), July 22, 2019. 

Translation. http://webcache.googleusercontent.com/search?q=cache:QwklsNMO8dcJ:www.cac.gov.cn/2019-

07/22/c_1124782573.htm+&cd=1&hl=en&ct=clnk&gl=ph.

210 Tara Francis Chan, “It Looks Like China is Extending its Black Mirror-like ‘Social Credit System’ to Overseas Companies,” Business Insider, July 3, 2018. https://www.businessinsider.com/china-social-credit-system-controlling-foreign-companies-2018-6.

211 Jeremy Daum, “Credible Threat? Taiwan, Websites, and Social Credit,” China Law Translate, June 30, 2018. 

https://www.chinalawtranslate.com/en/credible-threat-taiwan-websites-and-social-credit/.

212 Ministry of Foreign Affairs of the People’s Republic of China, Memorandum of Cooperation on Joint Punishment of Seriously Untrustworthy Entities in the Field of Foreign Economic Cooperation (关于对对外经济合作领

域严重失信主体开展联合惩戒的合作备忘录), October 31, 2017. Translation. https://www.ndrc.gov.cn/fggz/lywzjw/zcfg/201711/t20171128_1047046.html.

213 Jonathan E. Hillman, “Corruption Flows Along China’s Belt and Road,” Center for Strategic and International Studies, January 18, 2019. https://www.csis.org/analysis/corruption-flows-along-chinas-belt-and-road.

214 Pu Xiaolei, “Important! ‘Export Control Law Draft’ submitted for deliberation! Proposed to include military 

products, nuclear, etc. into controlled items” (重磅!《出口管制法草案》提请审议!拟将军品、核等纳入管制

物项), Chain News, December 24, 2019. Translation. https://www.chainnews.com/articles/400810253071.htm.

215 Trey McArver, “China’s Failing Fight Against Overcapacity,” Trusted Sources, January 22, 2016. 

216 Credit China, “National Urban Credit Status Monitoring Platform” (全国城市信用状况监测平台), https://

creditcity.creditchina.gov.cn/Index.aspx.

217 Xin Dai, “Toward a Reputation State: The Social Credit System Project of China,” (June 2018). https://doi.

org/10.2139/ssrn.3193577.

218 Yuval Harari, Homo Deus: A Brief History of Tomorrow, Harvill Secker, September 2016, 369.
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219 David Freeman Engstrom et al., “Government by Algorithm: Artificial Intelligence in Federal Administrative 

Agencies,” Administrative Conference of the United States (February 2020). https://law.stanford.edu/wp-content/

uploads/2020/02/ACUS-AI-Report.pdf.

220 “What Drives Legitimacy in Government?” Centre for Public Impact, September 26, 2017. https://resources.

centreforpublicimpact.org/production/2017/07/What-drives-legitimacy-in-government1.pdf; Bruce Gilley, “The 

Determinants of State Legitimacy: Results for 72 Countries,” International Political Science Review 27:1 (January 

2006): 47-71.

221 Richard McGregor, “Xi Jinping’s Ideological Ambitions,” Wall Street Journal, March 1, 2018. https://www.

wsj.com/articles/xi-jinpings-ideological-ambitions-1519950245.

222 Xin Dai, “Toward a Reputation State: The Social Credit System Project of China,” June 10, 2018. https://doi.

org/10.2139/ssrn.3193577.

223 Wu Weihai and Zhang Shaoli, Credit of Great Powers: The Global Vision of China’s Social Credit System (大

国信用 全球视野的中国社会信用体系), China Planning Press, January 2017. Translation. 

224 Wu Weihai and Zhang Shaoli, Chapter 14, Credit of Great Powers: The Global Vision of China’s Social Credit 

System (大国信用 全球视野的中国社会信用体系), China Planning Press, January 2017, 379-401. Translation. 

225 Huang Ying, “Opportunities and Challenges of Establishing China’s Leading Credit Rating Agency” (建立

我国主导信用评级机构的机遇与挑战), China Economic and Social Council, July 18, 2018. Translation. http://

webcache.googleusercontent.com/search?q=cache:CVAp6TkLQToJ:www.china-esc.org.cn/c/2018-07-18/2115894.

shtml+&cd=1&hl=en&ct=clnk&gl=ph.

226 Daniel Cash, “The Universal Credit Rating Group: Measuring Debt Ethically,” World Economics, November 

13, 2016, 67-74. https://www.researchgate.net/publication/317304903_The_Universal_Credit_Rating_Group_Rating_Debt_Ethically.

227 Gao Pan and Jiang Yujuan, “Lou Jiwei: International Rating Agencies are Biased Against the Chinese Economy” (楼继伟:国际评级机构对中国经济存在偏见), Xinhua, April 16, 2016. Translation. http://webcache.

googleusercontent.com/search?q=cache:jGQkhxE0Z98J:news.xinhuanet.com/world/2016-04/16/c_1118641709.

htm+&cd=1&hl=en&ct=clnk&gl=ph. ; Li Xuanmin, “Global Rating Agency’s Politically Biased Decision ‘Harms 

Itself,” Global Times, September 8, 2019. http://webcache.googleusercontent.com/search?q=cache:70sMO6KPEZsJ:www.globaltimes.cn/content/1163998.shtml+&cd=1&hl=en&ct=clnk&gl=ph. ; Risk Management Institute, “An 

Improved Regulatory Framework for Credit Rating Agencies?” Global Credit Review Volume 2 (2013): 31.

228 Samantha Hoffman, “Social Credit,” Australian Strategic Policy Institute, June 2018. https://www.aspi.org.au/

report/social-credit.

229 Shirley Yam, “How Chinese Corporates Owe a Debt to Ratings Agencies,” South China Morning Post, October 25, 2012. https://www.scmp.com/business/banking-finance/article/1068900/ratings-agencies-china-russia-andus-take-big-three.

230 “Repeatedly Receiving ‘Bad Reviews’ How can Emerging Market Countries Break the ‘Rating Barrier’?” (

屡获“差评” 新兴市场国家如何打破“评级藩篱”?), China News, July 19, 2016. Translation. http://webcache.

googleusercontent.com/search?q=cache:Fwx54Khm5a4J:www.chinanews.com/cj/2016/07-19/7945041.shtml+&cd=1&hl=en&ct=clnk&gl=ph.

231 Elizabeth C. Economy, written testimony for U.S.-China Economic and Security Review Commission, Hearing on a “China Model,” March 13, 2020, 1-9.

232 Yuka Kobayashi, “China’s Creative Compliance in the WTO,” in: Ka Zeng and Wei Liang (eds.), China and 

Global Trade Governance: China’s First Decade in the World Trade Organization,” Routledge, 103-125; China 

Power, “How influential is China in the World Trade Organization?” July 31, 2019. https://chinapower.csis.org/china-world-trade-organization-wto/.