The Social Credit System and Governmentality in China by Mario Tümmler

This essay analyses the Chinese Social Credit System regarding its effects on governmentality. In that, it goes beyond the predominant discussion which focuses only on the coercive capabilities of the state. The Chinese Social Credit System reinforces power-relations within Chinese society, as individuals start to monitor their behaviour regarding its effect on their credit score. Thus, they engage in a form of self-disciplining based on principles inscribed into the system’s algorithm. In this way, power-relations are reproduced indirectly by orienting one’s behaviour on the centralised credit score. However, the adherence to it is safeguarded through decentralised self-disciplining.

Digitalisation in China: First Steps toward an Orwellian Dystopia?

When thinking of digitalisation, names like Google and other large internet companies come to mind. This also true for China albeit the companies are named Alibaba or Tencent. While in Europe much discussion surrounds limiting the influence of such companies, the Chinese Communist Party (CCP) seeks to utilise their data to expand its power over Chinese society. In fact, a strong public-private nexus between the Chinese government and private internet companies has emerged (cf. Diab 2017: 12). Most prominently, the CCP plans to create a Social Credit System that combines data by government and internet companies to calculate a score for each citizen. Its goal is to calculate a rating of ‘trustworthiness and sincerity’ on which all social and commercial interactions should be based.

Many argue that this is the beginning of an Orwellian dystopia, propelling the capacity of the CCP to coerce citizens into obedience to a hitherto unknown level. While it is true that the coercive power can be vastly increased through such a system, its impact goes beyond that. Rather its effects on Chinese society should be understood as governmentality. Next to direct coercion, social credit systems pertain to subjectification itself, reinforcing power relations through self-disciplining without the need for coercive power. Direct enforcement is replaced by a calculative practice encouraging individuals to monitor all areas of their life based on a credit score. Enforcement of control becomes decentralised without coordination by any government agency, but it is immanent to market transactions, interactions with the government, and the subject’s conduct in the public sphere.

Social Credit Systems in China – Current Application and Future Plans

The objectives of the Social Credit System in China have changed over time and they are not simply a government policy, but part of a public-private nexus between the government and internet companies. Initially, the government-run Social Credit System was limited to loans, it was proposed as a solution to the lack of trust in the market place that limits lending and economic growth. Particularly those excluded from credit should be enabled to take out loans by proving their creditworthiness through the Social Credit System. However, its potential was soon realised and its scope was expanded to compliance with legal requirements, court judgements, and, finally, to the broader notion of moral conduct and trust-keeping (cf. Creemers 2016b: 10). Hereby, the CCP seeks to address distrust in the Chinese society, which is of particular importance to it, as a lack of social trust can erode social stability and eventually undermine its rule (cf. Hawkins 2017).

The State Council of China first laid out a plan for the implementation of a social credit system in 2014. It is supposed to become a nation-wide system by 2020 rating all behaviours of citizens according to an algorithm as either positive or negative. This should show the trustworthiness of citizens publicly and comparable to others, promoting ‘trust’ and building a ‘culture of sincerity’ (cf. Botsman 2017). However, the definition of trust or sincerity is left open. As the policy states “It will forge a public opinion environment where keeping trust is glorious” (Creemers 2014). And it should “strengthen sincerity in government affairs, commercial sincerity, social sincerity and the construction of judicial credibility” (Creemers 2014). In 2016, the State Council outlined further details, covering sanctions for citizens with a low credit score that supposedly ‘break trust’ providing an insight into the scope of the planned Social Credit System. These include comparatively harmless measures as slower internet speeds and restricted access to restaurants and nightclubs. But they will also include more crucial areas as housing, insurance, loans, social security benefits, and restrictions to travel freely abroad. In addition, citizens with low scores should be banned from certain jobs as civil servants, journalists, and lawyers. (cf. Botsman 2017; cf. Creemers 2016c; cf. Denyer 2016). The sanctions aim to “allow the trustworthy to roam everywhere under heaven, while making it hard for the discredited to take a single step” (Creemers 2016d). Thus, compared to current trust-building technologies like rating systems, the Social Credit System incorporates all areas of life so that misdeeds in one area have consequences for a person’s whole life (cf. Hawkins 2017).

The earliest pilot scheme for the Social Credit System started in 2010 with a government-run system in Jiangsu province. By now, a dozen government-run systems exist, which are supposed to be integrated into a nation-wide system (cf. Hvistendahl 2018). Even though the first system faced a strong public backlash (cf. The Economist 2016), in 2015 eight companies were licensed to implement social credit systems that should act as a model for the nation-wide system (cf. Hvistendahl 2018). Out of these, the internet giants Alibaba, Tencent, and Baidu built the most important ones (cf. Horwitz 2017). Here Alibaba’s Sesame Credit serves as an example for the planned national-wide system, since it is the market leader and similar to all major systems.

Sesame Credit was established in 2013 by Ant Financial, an affiliate of the Alibaba Group, and is integrated into Alibaba’s vast payment system Alipay. It can access all payments made through Alipay and includes data from other platforms like dating apps, taxi services, and bike rentals. Digital payment has become extremely widespread in China’s metropolitan areas and Alipay is almost ubiquitous in many branches, thus providing Sesame Credit with a near complete payment history of its users (cf. Hvistendahl 2018). It calculates a monthly updated score between 350 and 950 points based on five factors. First, the traditional payment history. Second, the fulfilment capacity, which is the user’s ability to fulfil his/her contract obligations. Next, are personal characteristics, which include information such as phone numbers and current residency. Fourth, behaviour and preferences, evaluating shopping habits and time spent on different activities. Lastly, interpersonal relationships including online friends and statements on social media. Crucially, friends with low credit scores affect a user’s score negatively. So far, no penalties are enforced, but it provides access to privileges like loans, car and bike rental without deposits, faster check-in at Beijing Airport, and fast track application to a pan-European Schengen visa (cf. Hvistendahl 2018).

The potential impact a Social Credit System incorporating private and public data can have is demonstrated by looking at the ‘Judgement Defaulter’s List’ of the Chinese government. It covers those who defied civil court orders and is accessible to government departments and party organs which can impose sanctions based on it. This already occurs in the form of bans from long-distance trains, airline tickets or restricted promotion. The list has already been integrated into Sesame Credit by lowering the scores of listed citizens (cf. The Economist 2016; cf. Hvistendahl 2018). Conversely, data collected by private companies has not been integrated into government-run systems, but the ‘Judgement Defaulter’s List’ shows that the public-private link already exists. So far, the Social Credit System is incomplete, but the integration of ever more public data is an official goal of the Chinese government (cf. Hvistendahl 2018). Equally, private companies will likely be allowed to integrate further data into their Systems.

Social Credit Systems as a Technology of Government

Existing studies on the Social Credit System almost exclusively address its potential for coercive power (cf. Hoffman 2017: 4-6; cf. Lubman 2016; cf. Crossley 2016; cf. Creemers 2016a, 2016b; cf. Meissner 2016). Only few studies ask how the Chinese Social Credit Systems impacts subjectification through self-disciplining, elaborating much on it (cf. Hoffman/Mattis 2016; cf. Salim Diab 2017). To shed light on this blind spot, I use the concept of governmentality by Michel Foucault, which highlights the influence of power on subjectification. It encompasses control and management by the state as well as self-control of the individual (Foucault 1993: 203-204; cf. Lemke 2001: 191). Governmentality can be described as the ‘conduct of conduct’, meaning the power to structure the possible field of action of others by shaping subjectification (cf. Paterson/Stripple 2010: 343; cf. Dean 1996: 60–61). Thus, concerning the immanent power relations of the Social Credit System, it is insufficient to look at the coercive capability of the state. What needs to be considered is the way that individuals act upon themselves based on certain issues that are identified as problematic. To handle problematic issues individuals rely on systems of thought that can be called rationalities of government, these rationalise the exercise of power by defining the ideals that direct government. (cf. Lemke 2001: 191; cf. Paterson/Stripple 2010: 346). However, the connection to the actions of individual is only established by technologies of government, which provide techniques and procedures that render problematised issues operable and connect the aspirations of authority with the subjectification of individuals. In this way, power becomes part of the structures shaping subjectification and how the individual disciplines itself in its day to day conduct. Self-disciplining does not have to be in line with ideals outlined by the rationality of government. However, it occurs in relation to problematised the issues, because they become the basis for the decisions of individuals (cf. Rose/Miller 1992: 179–183).

The rationality of government of the Chinese Social Credit System can be assessed via government documents. Here, the lack of social trust and sincerity in society is identified as the underlying problem, thus problematising interactions of citizen as whole. The problem is thus constructed to rationalise a form of government that encompasses all social interactions. The ideals directing the Social Credit System are stated in the 2014 plan which seeks to “broadly strengthen the sense of sincerity in the entire society, [achieving] a clear improvement in the credit environment for economic and social development, and a market improvement of the economic and social order” (Creemers 2014). Additionally, the plans state that mutual trust in society should be advanced in order to reduce social contradictions (cf. Creemers 2014).

The technology of government which links the rationality of government to the individual is the credit score, it allows for unprecedented reach, impact, and centralisation. As most technologies of government, the Social Credit System uses a multitude of procedures to collect data, but the individual is confronted with the different ratings in one single numerical score. Its effect transcends the sum of its parts: while financial credit scores and criminal records certainly impact the life of individuals, these ratings can safely be ignored in unrelated interactions. The Social Credit System is different, because it utilises the same data as existing ratings but produces a single numeral. Transforming vast amounts of data into this single score allows individuals to act upon it and to conduct their conduct through it, thus making the Chinese Social Credit System a much more effective technology than previous applications of data.

Next to its accessibility, the credit score is also normatively charged through its connection to the ideals of ‘sincerity and trustworthiness’. This increases its impact, as individuals are likely to want a high rating to portray themselves as sincere and trustworthy. This is independent from any actual believe in the validity of the score or its factual validity. As long as it functions as a signifier for ’sincerity and trustworthiness’, it fulfils its function as a technology of government. When individuals start to orient their actions on the assumed impact they have on their credit score, the score becomes part of their techniques for self-disciplining. It thus structures the field of action of individuals participating in the Social Credit System through self-disciplining rather than coercion. Josh Chin and Gillian Wong cite Alibaba’s executive vice chairmen who identifies this self-disciplining principle as a key aspect of Sesame Credit: “Especially for young people, your online behaviour goes towards building up your online credit profile and we want people to be aware of that so they to behave themselves better” (cf. 2016).

Self-disciplining to evade negative credit scores affects all areas integrated into the system. A nation-wide and mandatory system might require individuals to monitor most areas of their social and economic life. Otherwise, an action that is operationalised as negative for one’s score, has the potential to infringe all other interactions. Even more so, if the interpersonal relations aspect of Sesame Credit is adopted in the nation-wide system, individuals must monitor the credit scores of online friends as well, if they want to safeguard their own. Possibly, the negative impact of other’s credit scores might expand beyond social media to other digitally tracked connections. This would add a need to monitor the scores and actions of online contacts in addition to self-discipling, thus creating a two-fold form of decentralised control. This decentralised control makes coercion only a secondary aspect in the government rationale. Rather than enforcing adherence, the struggle over dissent or adherence is delegated to the individual. This constitutes an indirect power relation, as it aligns the self-disciplining of individuals and their monitoring of social peers with the principles inscribed into the calculation of the social credit score by the government.

The Social Credit System has yet another effect, as it is also a numerical measurement it enables self-disciplining to become a calculative practice. Social credit systems further a technological orientation of the individual’s conduct. Instead of being based on political or moral requirements, the conduct of individuals becomes based on their performance regarding the credit score. This constitutes a strategic rationality towards one’s conduct, because the Social Credit System connects government requirements of conduct with technical requirements of performance. While the former usually have a moral or political shaping, the Social Credit System transforms government requirements into the maximisation and optimisation of performance. Here, the credit score serves as an indicator that renders conduct calculable. This enables and urges individuals to engage in a calculative practice in which they monitor and optimise their conduct instead of adhering to moral and political principles alone. In this way, the calculative practice of monitoring one’s credit score becomes part of the subjectification of individuals (cf. Dean 1996: 60–61). Sesame Credit provides the basis for such calculative practices, however the comparability with the scores of others is limited curtailing its performance aspect. This is likely to change, as Sesame Credit already contains the feature to compare scores on a voluntary basis and the internet company Baidu also built a website that allows to compare credit scores of individuals (cf. Creemers 2016b: 5).

Calculative practices can already be found in descriptions of Chinese citizen handling Sesame Credit. Mara Hvistendahl accompanied a young man who starts using Sesame Credit, he quickly starts to test what he can do to improve his low score and begins checking his score even more frequently than it is updated. Calculative practices aiming at optimising one’s score are also highlighted by the existence of special chatrooms for people with high scores seeking to gain new online friends with equally high scores to further improve their scores (cf. Hvistendahl 2018). These calculative practices serve the creation of reflective subjects combining rough-and-ready calculations that assess the likely impact of actions on their score, with a constant evaluation of their own behaviour (cf. Paterson/Stripple 2010: 350). Thus, by transforming individual’s conduct of conduct into a calculative practice, Social Credit System produce reflective subjects that engage in much more rigorous self-discipling, than is possible through other – less centralised and quantifiable – forms of governmentality.

The Thought Police Inside Your Head

The Chinese Social Credit System does not merely constitute greater coercive capability for the CCP. Instead, its ideology of so called sincerity and trustworthiness is inscribed into its algorithm, forming the political rationality underlying the Social Credit System. The credit score becomes the basis on which individuals measure their conduct, while the Social Credit System is getting more and more wide-spread. As a quantitative reference with increasing importance for the life of individuals, the credit score functions as a basis for self-disciplining. In this way, the Social Credit System is part of governmentality, because it affects how individual organise their behaviour in line with the objectives of the Chinese government reinforcing the power relations on a subtler level. While this is based on a centralised score, adherence and self-disciplining works through decentralised mechanisms that affect the subjectification of individuals. It produces reflective subjects questioning their behaviour regarding its impact of their credit score. Thus, when invoking the notion of Orwell’s Thought Police regarding the Chinese Social Credit Systems, it rather resides in people’s own minds, than in a Ministry of Trustworthiness.

It is easy to dismiss the idea that something like the Chinese Social Credit System could be implemented in Europe or the US, because no democratically elected government would dare to do so. While it might be less likely that a social credit system will be introduced by a western government, this does not hold up for private companies. All the data utilised by Sesame Credit is also collected by internet companies in Europe and the US, since a social credit system is ultimately only a recombination of existing data and technologies. What makes a credit score so appealing for Westerners just as for Chinese citizens is not the fear of government sanctions, but the large range of practical advantages it offers. These advantages do not rely on the involvement of any government but can be implemented by internet companies alone. This raises the questions for each inhabitant of the digital world: will they resist the temptations of a credit score or will they embrace the social credit systems just like any other new social media?


Botsman, Rachel (2017): Big data meets Big Brother as China moves to rate its citizens. The Chinese government plans to launch its Social Credit System in 2020. The aim? To judge the trustworthiness – or otherwise – of its 1.3 billion residents. In: „Wired“, 21.10.2017. Availiable online at, (23.3.2018).

Chin, Josh/Wong, Gillian (2016): China’s New Tool: A Social Credit Score. Beijing wants to rate citizens on daily behavior to reward or punish. In: „Wall Street Journal (Eastern Edition)“, 29.11.2016. Available online at, (27.03.2018.

Creemers, Rogier (2014): Planning Outline for the Construction of a Social Credit System (2014-2020) (GF No. (2014) 21). In: „China Copyright and Media“, 25.04.2015. Available online at, (24.03.2018).

Creemers, Rogier (2016a): Is Big Data Increasing Beijing’s Capacity for Control?. In: „ChinaFiles (ChinaFile Conversation)“, 10.08.2016. Available online at, (24.03.2018).

Creemers, Rogier (2016b): Disrupting the Chinese State: New Actors and New Factors. In: Conference Digital Disruption in Asia: Methods and Issues, 24.05.2016, Available online at, (03.08.2018).

Creemers, Rogier (2016c): State Council Guiding Opinions concerning Establishing and Perfecting Incentives for Promise-keeping and Joint Punishment Systems for Trust-Breaking, and Accelerating the Construction of Social Sincerity (GF No. (2016) 33). In: „China Copyright and Media“, 30.05.2016. Available online at, (23.03.2018).

Creemers, Rogier (2016d): Opinions concerning Accelerating the Construction of Credit Supervision, Warning and Punishment Mechanisms for Persons Subject to Enforcement for Trust-Breaking. In: „China Copyright and Media“, 25.09.2016. Available online at, (23.03.2018).

Crossley, Pamela Kyle (2016): Is Big Data Increasing Beijing’s Capacity for Control?. In: „ChinaFiles (ChinaFile Conversation)“, 10.08.2016. Available online at, (26.04.2018).

Dean, Mitchell (1996): Putting the technological into government. In: History of the Human Sciences Jg. 9/3, p. 47–68.

Denyer, Simon (2016): China’s plan to organize its society relies on ‘big data’ to rate everyone. In: „Washington Post“, 22.10./2016. Available online at, (27.03.2018).

Diab, Ramon Salim (2017): Becoming-Infrastructure. Datafication, Deactivation and the Social Credit System. In: Journal of Critical Library and Information Studies Jg. 1/1, p. 1-25.

Foucault, Michel (1993): ‘About the beginning of the hermeneutics of the self’ (transcription of two lectures in Dartmouth on 17 and 24 November 1980). In: Political Theory Jg. 21/2, p. 198–227.

Hawkins, Amy (2017): Chinese Citizens Want the Government to Rank Them. The government thinks „social credit“ will fix the country’s lack of trust – and the public agrees. In: „Foreign Policy“, 24.05.2017. Available online at, (23.03.2018).

Hoffman, Samantha (2017): Managing the State: Social Credit, State Surveillance and the CCP’s Plan for China. In: China Brief Jg. 17/11, p. 1–6.

Hoffman, Samantha/Mattis, Peter (2016): Is Big Data Increasing Beijing’s Capacity for Control? In: „ChinaFiles (ChinaFile Conversation)“, 10.08.2016. Available online at, (24.03.2018).

Horwitz, Josh (2017): China’s Tencent is quietly testing a “social credit score” based on people’s online behavior. In: „Quartz“, 09.08.2018. Available online at, (23.03.2018).

Hvistendahl, Mara (2018): You Are A Number. In: „Wired“, 26.01.2018. Online available at, (03.08.2018).

Lemke, Thomas (2001): ‚The birth of bio-politics‘. Michel Foucault’s lecture at the Collège de France on neo-liberal governmentality. In: Economy and Society Jg. 20/2, p. 190–207.

Lubman, Stanley (2016): The Unprecedented Reach of China’s Surveillance State. In: „ChinaFiles“, 15.09.2016. Available online at, (24.03.2018).

Meissner, Miriam (2016): Is Big Data Increasing Beijing’s Capacity for Control? In: „ChinaFiles (ChinaFile Conversation)“, 10.08.2016. Available online at, (24.03.2018).

Paterson, Matthew/Stripple, Johannes (2010): My Space: Governing individuals’ carbon emissions. In: Environment and Planning D: Society and Space Jg. 28/2, p. 341–362.

Rose, Nikolas/Miller, Peter (1992): Political Power beyond the State. Problematics of Government. In: The British Journal of Sociology Jg. 43/2, p. 173–205.

The Economist (2016): China invents the digital totalitarian state. The worrying implications of its social-credit project. In: „The Economist“, 17.10.2016. Available online at, (23.03.2018).

Der Autor

Mario Tümmler, 25, studiert an der Goethe Universität Frankfurt am Main im Masterstudium Politikwissenschaften. Seine Interessengebiete umfassen die Themen Internationale Politische Ökonomie, Entwicklungspolitik, Finanz-marktregulation und Europäische Integration.

Der Beitrag wurde redaktionell von Tamara Schwertel betreut und von Hendrik Erz lektoriert.

Das könnte Dich auch interessieren …

Schreibe einen Kommentar

Deine E-Mail-Adresse wird nicht veröffentlicht.

Diese Website verwendet Akismet, um Spam zu reduzieren. Erfahre mehr darüber, wie deine Kommentardaten verarbeitet werden.