CEB No. 21: Recent Developments of Data Governance in China and Implications for Foreign Investment – The Chinese (Corporate) Social Credit System
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The Chinese (Corporate) Social Credit System: From Experimentation towards a Policy Model for the World?
Where does the social credit system come from?
In 2014, the state council of the People’s Republic of China (hereafter “China”) adopted the “Planning Outline for the Construction of a Social Credit System (2014–2020)”, that aimed at establishing a comprehensive rating system assessing both, economic and social behaviour of natural and legal persons in China (Ohlberg et al. 2018: 4). Elaborated by an interministerial conference since 2012 and adopted by the state council in June 2014, the outline defined clear goals to be achieved by 2020 such as the construction of a credit information system covering the entire society, the set-up of credit supervisory authorities and a punishment and reward system (State Council 2014; Creemers 2018: 12). The document also identified four key areas, where a social credit system seemed necessary: government affairs, commerce, judicial credibility, and civil society (von Blomberg 2018: 87).
In general, the social credit system is located within Chinese social management, which refers to the political-administrative control of the population (Shi-Kupfer/Heilmann 2016: 235; Creemers 2018: 2). Other prominent examples of social management are the hukou residence registration system or the former one-child policy (Shi-Kupfer/Heilmann 2016: 235). The term social credit system first appeared in the context of the Chinese market economy’s development when violations of intellectual property rights and scandals of contaminated food promoted mistrust of economic reforms (Creemers 2018: 8).
In order to simplify the granting of loans, especially in rural areas of China where a large proportion of the inhabitants could not provide the necessary documents on their creditworthiness, a credit rating system was discussed as early as the 1990s (Drinhausen/Brussee 2021). Besides, the social credit system is seen as a response by the central government to the moral crisis within the CCP arising from corruption (Drinhausen/Brussee 2021). Its roots grew in a time of decentralised politics “where the political initiative had moved from the centre to the localities, resulting in perceptions of weak central leadership and rampant local corruption” (Creemers 2018: 7). Another factor was the lack of enforcement capacity of the Chinese judiciary (Ojeda 2019: 4). Chinese citizens often evaded prosecution, which further weakened the trust in Chinese courts within the political system (Ojeda 2019: 4).
Thus, the social credit system does not merely aim to evaluate each Chinese citizen’s behaviour. Rather, it is a multi-layered concept that addresses several aspects of state regulation: On one hand, the system aims to assess the creditworthiness of companies and private-sector actors, but on the other hand, it also aims to increase moral values such as trust and integrity (Ohlberg et al. 2018: 5).
Already in the 1990s, first e-government projects started, connecting China's public security bureaus through an online network to increase both efficiency and control within public administration (Mistreanu 2018). Between 2001 and 2007, local initiatives and pilot projects were rolled out in individual provinces and cities aimed at better controlling their citizens’ behaviour (Ohlberg et al. 2018: 9). At the central government level, an inter-ministerial conference was established in 2007, tasked with planning the construction of a financial credit rating system, designing new policies, and overseeing policy implementation (Creemers 2018: 9). The body was expanded in 2012 to include new key actors (from both party and state), for example, the Central Commission for Discipline Inspection, the Central Propaganda Department, the Central Political and Legal Affairs Commission, and the Supreme People's Court and by 2014, the interministerial conference had drafted the “Planning Outline for the Establishment of a Social Credit System (2014–2020)” (Creemers 2018: 9).
Policy experimentation in times of top-level design
Since the adoption of the 2014 planning outline, international media has been reporting on an all-encompassing evaluation system that uses artificial intelligence and big data to record the moral behaviour of China’s approximately 1.4 billion citizens, then converting it into a rating system (Horsley 2018). A system in which low score citizens experience systematic repression, whereas others with morally impeccable conduct enjoy a variety of benefits (Marr 2019). Other authors referred to the planned system as a digital dictatorship or compared it with George Orwell’s dystopia “1984” (The Economist 2016). However, contrary to what is portrayed in media reports, the social credit system envisaged by the Chinese central government is not an already existing, uniform system for recording human behaviour. Instead, a variety of different (local) pilot projects and initiatives can be identified in provinces and cities that have already established their own version of a social credit system and among which the State Council had intended to select some elements for national expansion by the end of 2020 (Drinhausen/Brussee 2021). Since 2014, a total of 43 local pilot projects were launched of which 28 cities were selected “between 2018 and 2019 as test beds for nationwide implementation” (Drinhausen/Brussee 2021).
The gradual testing of different local projects is reminiscent of the Chinese “policy experimentation”, a concept put forward by political scientist Sebastian Heilmann. Accordingly, policy experimentation describes a type of policy making in which decentralised experimentation is intended “to generate institutional and policy innovations” (Heilmann 2008a: 1) to increase economic adaptability (Heilmann 2008a: 1), while policy implementation precedes national legislation (Heilmann 2008b: 4). Going back to the early land reforms of the Chinese Communist Party in communist-controlled areas during the Chinese civil war (Heilmann 2008a: 4), it is also a prominent approach to describe and understand the Chinese policy process of the reform era (Schubert/Alpermann 2019: 204), where policies were primarily driven by decentral experiments, which were, however, subject to interventions by higher party cadres and government officials, resulting in an “interplay between local initiative and central auspices” (Heilmann 2008b: 13).
Indeed, a closer look at the Social Credit System’s policy process reveals elements of Heilmann's policy experimentation: China's State Council already sought reforms to capture entrepreneurial creditworthiness between 1990 and 2000; from the early 2000s, public demands for a social credit system also increased as part of deeper modernization efforts, which together also led to the establishment of credit rating agencies (Creemers 2018: 6). Furthermore, the first local financial creditworthiness registration projects emerged between 2003 and 2007, which were then consolidated in 2006 by the People’s Bank of China “Center for Credit Reporting” (Chorzempa et al. 2018: 3). However, the initiative to combine financial creditworthiness with the principle of social management clearly came from individual cities and provinces, as demonstrated by the “grid management” in Shanghai from 2001 or by the “Credit Hangzhou Mechanism” in Hangzhou from 2004 (Chorzempa et al. 2018: 3).
While the first key document of the State Council, “Opinions of the General Office of the State Council concerning the Building of a Social Credit System” (Shen 2019: 22) from 2007, focused only on the aspect of financial creditworthiness and described the establishment of a social credit system as necessary to protect the socialist market economy from fraud, tax evasion and product piracy, a well-known pilot project in Suining from 2010 led to a political turnaround at the state level. The project assigned residents 1000 points across a rating scale from A to D (Creemers 2018: 10). Residents were rewarded with points for exemplary behaviour (e.g. volunteering) and penalised with point deduction for poor behaviour (e.g. traffic violations) (Ohlberg et al. 2018: 4). Those with a better score were given better chances for a promotion in their job or when applying for social housing (The Economist 2016). The project failed mainly due to incomplete data (The Economist 2016; Bing 2018) and public media criticised the project of arbitrary scoring and compared it with the “good citizen” certificates during the Japanese occupation (Mistreanu 2018; The Economist 2016), the project was discontinued and declared a disaster (Mistreanu 2018; The Economist 2016). Despite the official failure, the central government drew consequences from the project in Suining (Mistreanu 2018; The Economist 2016), recognizing the link between financial creditworthiness and moral action as a method of governance in party, state, and economy (Creemers 2018: 10) and devoted the sixth plenary session of the 17th CPC Central Committee to culture and ideology (Creemers 2018: 12). The subsequently adopted “Decision Concerning Cultural Structural Reform” (Central Committee 2011) then called for the establishment of a social credit system to promote sincerity in society in commercial as well as social and political spheres (Central Committee 2011; Creemers 2018: 12). Shortly thereafter, as mentioned above, the interministerial conference was expanded to include a number of stakeholders, and by 2014, the “Planning Outline for the Construction of a Social Credit System (2014–2020)” had been elaborated.
It can be noted that although an improvement in financial creditworthiness was initiated centrally in order to solve the problems raised in connection with market economic reforms, the link to moral action was tested and developed decentrally. In turn, the central government responded with a discernible policy shift and by incorporating some elements into national policy, such as the appropriate link between creditworthiness and morality, the punishment and reward system, or public exposure for moral transgressions. Moreover, the 43 pilot cities proclaimed by the Chinese central government since 2014 can be understood as official experimental points according to Heilmann's concept of policy experimentation.
This policy experimentation strongly contrasts with the “top level design” observed under Xi Jinping, which describes increasing centralization and hierarchization as well as agenda-setting within the centre of the CCP, and stricter control of policy implementation by higher-level authorities (Schubert/Alpermann 2019: 205). While in the course of top level design, a decline in official pilot projects was also noticeable – between 2010 and 2016, official experiments dropped from 500 to fewer than 100 projects (Schubert/Alpermann 2019: 205) – the political system continues to experiment in various policy fields, as with the (Corporate) Social Credit System or with the testing of blockchain technology (Ekman 2021: 3).
However, the testing of different projects and initiatives and the interplay between local and central levels also makes it particularly difficult for foreign companies to adapt to local and national conditions and also entails the risk of missing out on important measures and obligations.
Fragmented and inconsistent regulation
Although 2020 marked the official and formal “end of its crucial six-year construction phase” (Drinhausen/Brussee 2021), the regulatory framework of the social credit system remains highly fragmented and inconsistent (Drinhausen/Brussee 2021). As mentioned before, there is no unified, standardised system and even the term “social credit” is still not clearly defined, resulting in a rather patchy framework with some local initiatives focusing on financial credit worthiness while others aim at law enforcement or moral behaviour (Drinhausen/Brussee 2021).
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According to an analysis by the Mercator Institute for China Studies, more than 47 (central) institutions are involved in the system’s development and the total output of SCS-related regulations rose steadily, especially since the adoption of the 2014 planning outline, with a clear peak in 2019 (Drinhausen/Brussee 2021). However, due to a lack of clarity and manageability of all regulations, the system is rather a “regulatory jungle” (Drinhausen/Brussee 2021). Obviously, the Chinese central government realised the growing trend of “a system of systems” (Drinhausen/Brussee 2021) and the need for harmonisation and elaborated a first draft of a Social Credit Law in 2020.
The 2014 planning outline originally demanded a system that would incorporate information on all societal actors, from private individuals to enterprises and government authorities (State Council 2014). However, by now, “companies are the main target of the social credit system” (Drinhausen/Brussee 2021). In contrast to the social credit system for individuals, the Corporate Social Credit System is already more comprehensively implemented, although a large number of local pilot projects/pilot cities can still be identified (EU Chamber of Commerce in China 2019: 7).
By now, the Corporate Social Credit System primarily consists of three elements – national and local databases, red- and blacklisting, and rewards and punishments (German Chamber of Commerce in China 2020: 4). Two national databases, the National Enterprise Credit Information Publicity System as well as CreditChina, are publicly available (German Chamber of Commerce in China 2020: 5). Additionally, the National Credit Information Sharing Platform was launched in 2015, controlled by the State Information Center of the National Development and Reform Commission (NDRC) (German Chamber of Commerce in China 2020: 4).
The mechanism behind each database follows three main steps, whereby
Ratings may be both, sector- or topic-specific (e.g. concerning environmental protection) while some are rated on a scale (points or letters) and some are merely assessed binary by distinguishing “compliance” from “non-compliance” (EU Chamber of Commerce in China 2019: 11). The collection and monitoring of business data and information is either based on data transferred by companies, government inspections, or digital inspections including data acquired by third parties (e.g. companies like Tencent and Alibaba), by video surveillance or even by instruments for remote and real-time monitoring “of product performance, emissions and logistics” (EU Chamber of Commerce in China 2019.: 14).
Depending on a company’s performance or compliance and its credit score and rating, the company can also become subject to rewards or sanctions, the latter including blacklisting which comes with a set of joint sanctions (German Chamber of Commerce in China 2020: 6). Joint sanctions also range from penalty rates, court orders, targeted audits, higher inspection rates to being even excluded from public procurement and to public shaming (EU Chamber of Commerce 2019: 25). However, the implementation “of the sanctioning mechanisms is still incomplete” (EU Chamber of Commerce in China 2019: 3).
Implications for German businesses
In principle, the system does not create any new obligations to be fulfilled, but merely aims at “tracking compliance with, and enforcement of, laws and regulations” (Drinhausen/Brussee 2021). However, the system increasingly requires companies to report their data to government authorities and bears some specific implications for German and international companies operating in China that need to be taken into account (Drinhausen/Brussee 2021).
As multinational companies are likely to “be affected by 25 to 30 ratings and compliance records” (EU Chamber of Commerce in China 2019: 20), it is necessary to first increase corporate awareness for different rating systems and databases and resulting responsibilities/obligations depending on the credit score. Identifying the applicable grading systems and blacklists, based on the individual business sector, should therefore have highest priority (German Chamber of Commerce in China 2020: 13). Thanks to clear definitions on the respective ratings, companies will be able to prepare and adjust their compliance, however, the exact ratings are extremely sector- and company-specific, meaning that individual and detailed analysis becomes necessary but time-consuming.
In general, important steps when adjusting to the Corporate Social Credit System may include:
Multinational companies might also consult data bases of other rating agencies (Cheng.Xin or HiggsCredit) or privately-run rating platforms (e.g. Tianyancha) for evaluating social credit records as they “often have a more accessible user interface” (EU Chamber of Commerce in China 2019: 17) and offer complex meta-ratings (EU Chamber of Commerce in China 2019: 17).
Although most of the requirements for companies are basically well defined, the Corporate Social Credit System seems very intransparent due to the sheer overabundance of documents and regulations at various levels (EU Chamber of Commerce in China 2019: 11). Thus, it is crucial for international companies “to allocate resources to credit data monitoring and managing” (German Chamber of Commerce in China 2020: 13). Understanding the requirements resulting from the system and assessing the company’s operations will be as important in the future as are close contacts to Chinese government authorities for signalling and clarifying forthcoming problems and questions (EU Chamber of Commerce in China 2019: 32). Likewise, networking and cooperation among actors of specific industries as well as between different industry sectors becomes even more important in order to facilitate dialogue between international actors in China and the Chinese government. As it is expected that the Corporate Social Credit System will also consider the behaviour of business partners in the future (German Chamber of Commerce in China 2020: 14), monitoring the credit score of affiliated or cooperating enterprises might be decisive for a company’s full compliance record, too.
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References
Authors:?Jasper Habicht, Isabeau H?hn, Jessica K?hler