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The purpose of this paper is twofold: first, to explore how China uses a social credit system as part of its “data-driven authoritarianism” policy; and second, to investigate how datafication, which is a method to legitimize data collection, and dataveillance, which is continuous surveillance through the use of data, offer the Chinese state a legitimate method of monitoring, surveilling and controlling citizens, businesses and society. Taken together, China’s social credit system is analyzed as an integrated tool for datafication, dataveillance and data-driven authoritarianism.

This study combines the personal narratives of 22 Chinese citizens with policy analyses, online discussions and media reports. The stories were collected using a scenario-based story completion method to understand the participants’ perceptions of the recently introduced social credit system in China.

China’s new social credit system, which turns both online and offline behaviors into a credit score through smartphone apps, creates a “new normal” way of life for Chinese citizens. This data-driven authoritarianism uses data and technology to enhance citizen surveillance. Interactions between individuals, technologies and information emerge from understanding the system as one that provides social goods, using technologies, and raising concerns of privacy, security and collectivity. An integrated critical perspective that incorporates the concepts of datafication and dataveillance enhances a general understanding of how data-driven authoritarianism develops through the social credit system.

This study builds upon an ongoing debate and an emerging body of literature on datafication, dataveillance and digital sociology while filling empirical gaps in the study of the global South. The Chinese social credit system has growing recognition and importance as both a governing tool and a part of everyday datafication and dataveillance processes. Thus, these phenomena necessitate discussion of its consequences for, and applications by, the Chinese state and businesses, as well as affected individuals’ efforts to adapt to the system.

China is establishing a social credit rating system with the aim to score the trust level of citizens. The scores will be based on an integrated database that includes a vast range of information sources, rating aspects like professional conduct, corruption, type of products bought, peers’ own scores and tax evasion. While this form of gamification is expected to have dire consequences on brands and consumers alike, the literature in that particular area of interest remains non-existent. The paper aims to discuss these issues.

A conceptual framework is suggested that highlights early on the risks and implications on brands and companies operating in that particular upcoming landscape.

The gamification of trust that the social credit system focuses on presents potential risks on brand and consumer relationships. This in turn will affect brand sustainability vis-à-vis the expected drastic changes in the Chinese business landscape. This study suggests the strategies to follow which will be of high interest to companies, consumers, as well as to the Chinese authorities during and after implementation stage.

This paper is amongst the first to discuss the potential effects of the Chinese social credit rating system on brands. The conceptual framework fills a sizeable gap in the literature and pioneers the discussion on potential dilemmas brands will be faced with within this new business landscape.

The aim of this paper is to show that there are workable alternatives to the debt‐finance system in the form of “state credit.”

The example used for the practical application of “state credit” is the State Housing programme of the 1935 New Zealand Labour Government. The primary sources are mainly the pamphlets of John A. Lee, responsible for the State Housing and Labour finance policies.

The paper shows that “state credit” was used on a large‐scale for constructive purposes, which not only provided debt‐free funding for an enduring construction programme, but one that did so without accompanying inflation or other adverse consequences which are warned of by orthodox economists.

The paper focuses on a single example of the use of state credit, albeit an important and large‐scale one.

State credit was used in a major way during the 1930s to overcome unemployment while constructing something lasting and of enduring social benefit. It is a method that can be reapplied in the present time at a period where debt is reaching crisis point from entire nations down to families and individual consumers; with the most common remedy suggested relief being “austerity” and welfare cuts.

State credit is a means of achieving large‐scale public works, while reducing unemployment, and reducing taxes, rates and prices which generally incorporate into costs the servicing of debts. The social implications are wide‐ranging.

The 1935 State Housing programme had endured as part of an iconic New Zealand social experiment, but one of which the method of funding is now virtually unknown.

What counts as evidence of good performance, behaviour or character? While quantitative metrics have long been used to measure performance and productivity in schools, factories and workplaces, what is striking today is the extent to which these calculative methods and rationalities are being extended into new areas of life through the global spread of performance indicators (PIs) and performance management systems. What began as part of the neoliberalising projects of the 1980s with a few strategically chosen PIs to give greater state control over the public sector through contract management and mobilising ‘users’ has now proliferated to include almost every aspect of professional work. The use of metrics has also expanded from managing professionals to controlling entire populations. This chapter focuses on the rise of these new forms of audit and their effects in two areas: first, the alliance being formed between state-collected data and that collected by commercial companies on their customers through, for example loyalty cards and credit checks. Second, China’s new social credit system, which allocates individual scores to each citizen and uses rewards of better or privileged service to entice people to volunteer information about themselves, publish their ‘ratings’ and compete with friends for status points. This is a new development in the use of audit simultaneously to discipline whole populations and responsibilise individuals to perform according to new state and commercial norms about the reliable/conforming ‘good’ citizen.

This paper aims to survey the credit scoring literature in the past 41 years (1976-2017) and presents a research agenda that addresses the challenges and opportunities Big Data bring to credit scoring.

Content analysis methodology is used to analyze 258 peer-reviewed academic papers from 147 journals from two comprehensive academic research databases to identify their research themes and detect trends and changes in the credit scoring literature according to content characteristics.

The authors find that credit scoring is going through a quantitative transformation, where data-centric underwriting approaches, usage of non-traditional data sources in credit scoring and their regulatory aspects are the up-coming avenues for further research.

The paper’s findings highlight the perils and benefits of using Big Data in credit scoring algorithms for corporates, governments and non-profit actors who develop and use new technologies in credit scoring.

This paper presents greater insight on how Big Data challenges traditional credit scoring models and addresses the need to develop new credit models that identify new and secure data sources and convert them to useful insights that are in compliance with regulations.