Informal Finance in China: Risks, Potential and Transformation (CBR project)

Overview

Background

China’s rapid economic growth in recent decades has been attributed to its reliance on informal contracting and trust-based relationships (guanxi). his claims builds on the absence in China of some of the more formal legal and regulatory institutions of the market economies of the global north. Although the claim that China lacks formal legal mechanisms of market governance may have been somewhat overstated, it is the case that informal finance, particularly in the form of trade credit, family lending and communal investing, has played a major role in supporting China’s growth. The prevalence of informal finance presents a significance source of flexibility for China’s economy given the limitations of the formal sector, which remains dominated by state-owned banks lending largly to state-owned enterprises. Informal finance is also evolving quickly and is converging with the use of internet technologies to deliver finance (‘fintech’) through such mechanisms as crowdsourcing.

However, there are downsides to the reliance of the Chinese economy on informal finance and significant risks arise from its convergence with fintech. The large shadow banking sector, by virtue of its positioning outside most of the regulations applying to mainstream banks, adds to systemic risks. The formal and informal sector coexist in an uneasy relationship: they may substitute for each other, or provide complementary modes of finance, but they can also operate to reinforce and magnify systemic risks.

Similarly, the rise of fintech is a double edged sword. On the one hand, cloud computing and big data may be facilitating new forms of social credit and collective investment schemes which have the potential to meet the needs of the growing social credit sector. Crowdsourcing may provide a new and flexible form of financing for startups and innovative ventures. However, these new forms of finance also have the potential to undercut or render otiose regulations designed to maintain market transparency, and to intensify the risks facing investors. 

Aims and objectives

This an interdisciplinary research project exploring informal finance in China, the risks it is generating, its potential to support economic growth, and its transformation in the light of new technologies and a developing regulatory agenda. The work is being carried out by the CBR in collaboration with the School of Law, University of Sheffield, the School of Law, Renmin University, Beijing, and the College of Finance and Statistics, Hunan University. The project has the following aims:

  • To understand the potential, but also the limits, of systems of informal financing in China
  • To analyse the relationship between formal and informal finance in China
  • To examine the risks posed by China’s shadow banking system
  • To study the emergence in China of new forms of financing using big data and cloud computing to drive financial innovation, including P2P lending, crowd funding and similar collective investment schemes 
  • To explore the scope for the development of social credit systems in China.

Method

Part of the work involves fieldwork and surveys with internet financing companies and supervisory bodies in order to better understand the operation of the sector at both national and regional levels. We are also using law and economics analysis to build conceptual models of the likely options for regulation of internet finance and fintech-informed universal banking. A comparative legal study is being undertaken to assess the current state of law and regulation in China and the UK on these issues. In addition we are using questionnaires, face to face interviews and archival/documentary research to build up a picture of the current state of the shadow banking sector and its supervision, related aspects of informal finance, and the operation of social credit systems in China.

Progress and dissemination

The work began in February 2017 and was completed in January 2019. An initial round of interviews was carried out in China in April 2017. On 15-16 April 2017 a conference on Fintech was held in Hangzhou, Zhejiang Province, organised with our Chinese research partners, and with the participation of industry-level actors, policy makers and regulators. In July 2017 the Cambridge team convened meetings with each of the Chinese teams and UK financial regulators based at the Financial Conduct Authority and Bank of England (Prudential Regulation Authority). Further interviews were carried out in China in September 2017 and in January 2018, when a workshop was held at Hunan University. In December 2018, a final round of interviews was completed in Beijing, Hangzhou (including a visit to the Hangzhou Internet Court), Wenzhou, and Shenshen.

Progress has also been made on the econometric aspects of the research. An event study analysis of the impact of regulation in the Chinese P2P sector has been completed, complementing the fintech fieldwork. In addition we have been working on a cross-national study of the respective roles of law and culture in influencing financial development and a study of the interactions between labour regulation, firm-level productivity and shareholder returns in different Chinese provinces. We are also working on a paper on the use of machine learning in legal adjudication and decision making.

A workshop was held in Cambridge in June 2018 with visiting Chinese commercial law judges and UK-based experts in insolvency and commercial law (Professor Gerry McCormack and Dr Xinian Zhang of Leeds University and Dr Natalie Mrockova of Oxford University), and an academic workshop was held at Sheffield University in September 2018. In March 2019 members of the Cambridge team took part in a conference on financial inclusion and fintech held at SOAS, University of London. In April 2019 Simon Deakin presented the results of the fintech fieldwork and case study to a workshop organised by the Financial Services Authority, Tokyo, and in June 2019 he presented the same research to a meeting of financial professions in the City of London, organised under the auspices of the Cambridge Endowment on Research in Finance. Simon Deakin and Ding Chen gave presentations to academic workshops at SOAS, University of London, in May and June 2019.

Work on writing up the results of the interviews is continuing, along with statistical analysis of the effects of regulation of the fintech sector in China and of trends in insolvencies. Differences in institutional quality across Chinese provinces are also being explored through econometric analysis. A number of project-related articles have appeared or are forthcoming in peer-reviewed journals including the Journal of Law, Finance and Accounting and the Journal of Comparative Law. Working papers are being written up on various aspects of the research including the regulation of the P2P sector in China; the role of the law in financial sector development; informal and formal finance in Wenzhou following the crisis of 2011; an historical analysis of the formalisation of finance in the UK the relationship between firm-level productivity, shareholder returns and labour regulation; and the use of AI and machine learning techniques in the context of legal adjudication and decision making.

Project leaders

  • Simon Deakin (CBR)
  • Boya Wang (CBR)
  • Ding Chen (University of Sheffield)
  • Andrew Johnston (University of Sheffield)
  • Navajoti  Samanta (University of Sheffield)
  • Frank Stephen (University of Manchester)

Project status

Ongoing

Project dates

2017-2019

Funding

ESRC Newton Fund and National Science Foundation of China

Output

Journal articles

Chen, D. (2018) ‘Why is China’s SOEs reform always disappointing? A new political economy explanation’ Journal of Comparative Law, forthcoming.

Chen, D. (2018) ‘Changes in corporate governance in China and their impact on financial market growth: an empirical analysis (1995-2014)’, Corporate Governance, forthcoming.

Stephen, F.H (2017), ‘The institutional environment required to support, China’s new normal economy’, China-EU Law Journal, 5:119–134 (DOI 10.1007/s12689-016-0071-x).

Book chapters

Stephen, F.H (2017), ‘New Institutional Economics, Culture and Corporate Governance’ pp. 45-60 in Franklin, N.N, Onyeka, K.O and Stephen, F.H (eds) Corporate Governance in Developing and Emerging Markets, London: Routledge.

Books

Ngwu, F.N, Onyeka K.O and Stephen, F.H (eds) (2017), Corporate Governance in Developing and Emerging Markets, London: Routledge.

Stephen, F.H (forthcoming January 2018), Law and Development: an Institutional Critique, Edward Elgar Publishing.

Other publications

Chen, D., “Fintech in the UK 2017”, Chapter for Jingdong 2017 Fintech Annual Report.

Conference/Workshop papers

Deakin, S. (2017) ‘Law, trust and institutional change in China’, paper presented to the Conference on Fintech in China, Hangzhou, 16 April 2017.

Stephen, F. (2017) ‘Law and development: an institutional critique’, paper presented to the Conference on Fintech in China, Hangzhou, 16 April 2017.

Results

The sustainability of the Chinese model of fintech

China’s approach has been promoted as a means of meeting Sustainable Development Goals related to financial inclusion. However, the rapid growth Chinese fintech has been at least in part the result of regulatory arbitrage, given the relative weakness of the regulations governing Chinese fintech firms by comparison to those applying to the formal banking sector in China and to fintech firms in neighbouring jurisdictions, including Hong Kong. Regulation in China was significantly tightened from 2015 and there was then a shake out of firms, particularly in the P2P sector. There are continuing concerns about the opacity of techniques used in data analytics and hence of their adequacy as a replacement for more traditional mechanisms of credit evaluation.

A related issue is the sustainability of marketplace funding from the point of view of risk allocation. P2P financing, in a context where the platform is a pure information intermediary, entails the transfer of risk to a diffuse group of individual lenders. The experience of past financial crises suggests that such wide diffusion of risk, far from allowing for optimal risk spreading, can exaggerate the effects of information asymmetries and give rise to herding. The Chinese model could be vulnerable to ‘contagion’ effects which could trigger a negative market-wide reaction to systemic shocks.

The distinctiveness of Chinese fintech

This issue involves a consideration of how far the rapid growth of fintech in China is the result of country-specific factors which cannot easily be replicated elsewhere. Among the factors considered significant for the promotion of fintech are investment in internet infrastructure and training of fintech specialists with the relevant financial and technical skills.

While there would not seem to be insuperable barriers to the recreation of these conditions elsewhere, other factors inherent in the Chinese success story so far may not be so readily transferable. The fieldwork carried out for the project suggests that Chinese fintech firms owe much of their stability and sustainability to their embeddedness in networks characterised, as elsewhere in the Chinese economy, by a high degree of repeated trading and interpersonal trust. Thus some of the more successful P2P platforms supplement data analytics with offline credit checks and relationship building (the ‘O2O’ or ‘online to offline’ model). There is also evidence that interlocking ownership structures and alliances between platforms and more traditional financial institutions, including state-owned banks, play a role in cushioning platforms against the risks of credit defaults (Chen et al., 2019).

Lessons of the Chinese experience for the evolving regulatory framework of fintech

Traditional approaches to financial regulation, in so far as they rely on licensing, information disclosure and supervision by state agencies, are in danger of appearing antiquated in the context of the rapidly developing fintech sector. This poses the question of how far these can approaches be effectively applied when technology is changing the very nature of the business model in question. A further issue is concerned with the risk that existing regulatory models cannot iterate with the pace of change in the industry. Here, the UK FCA’s ‘sandbox’, which provide a controlled environment within which experimental business models can be tried out and tested under close regulatory supervision, suggests a way forward. The sandbox model has the potential to trigger regulatory learning both for firms in the fintech sector and for the regulator itself. This experience has prompted a debate in China about the adoption of the sandbox there. However, it is unclear how new business models work once they graduate from the sandbox, and there are concerns that the sandbox does not provide a scalable model as fintech continues to evolve.

The changing nature of informal finance in China: the Wenzhou model

The coastal city of Wenzhou in Zhejiang province has a reputation as the birthplace of China’s private sector economy and is also well known as a centre of informal finance. In 2011, it was badly hit by a regional financial crisis. This crisis is widely believed to have been caused by the collapse of Wenzhou’s informal financial market and has therefore been referred as the ‘informal financial crisis’ (minjian jinrong weiji). The crisis drew a great deal of attention from policy makers in China and their interventions led to a pilot reform in 2012. The project studied the Wenzhou crisis through interviews with key actors (business owners and managers, officials and judges) conducted between 2016 and 2018. While the crisis of 2011 has been attributed to weaknesses in the system of informal finance, including predatory interest rates, the study (Chen and Deakin, 2019) finds that the roots of the failure lay in the way that the formal and informal systems became intertwined in the period following the global financial crisis of 2008 and the expansionary monetary policy initiated by the Chinese authorities to counter its effects. The research highlights the effects of the over-supply of formal credit in this period and the encouragement of group lending, a practice relatively unknown prior to 2008, and which magnified the effects of the crisis. It concludes that the lesson to draw from Wenzhou is not that informal finance is inherently more instable or inefficient than formal finance, but that encounters between formal and informal finance can trigger instabilities in both.

The role of legal systems in financial sector development

An econometric paper by Frank Stephen, Simon Deakin and Boya Wang (Stephen et al., 2019) examines the relationship between the legal system and financial sector development using a New Institutional Economics based model developed by Frank Stephen (2018) and using the Cambridge leximetric data set and the rule of law index published by the World Bank. The paper tests the claim of legal origin theory, that common law jurisdictions have superior investor and creditor protection civil law jurisdictions; the impact of the publication of the World Bank’s Doing Business reports on reform of investor and creditor protection laws and regulations leading to a convergence in such laws across jurisdictions; the impact of such reforms on the perceptions of economic agents on the functioning of the economic and legal systems; and the relative importance of ‘law on the books’ and ‘law in action’ in influencing financial sector development. The results do not support legal origin theory but do find evidence of a ‘transplant’ effect suggesting that legal norms do not bed down well in country environments to which they are ill suited. While the publication of Doing Business rankings has led to increased levels of investor and creditor protection particularly in civil law jurisdictions, such reforms do not necessarily lead to higher confidence among economic agents in the functioning of markets and the legal system. The paper finds no evidence that higher levels of formal investor and creditor protection (formal law), but does find that increasing trust in economic and legal system as a whole enhances financial sector development.

The relationship between labour law protection, shareholder returns, and total factor productivity

A paper by Boya Wang and Simon Deakin reports the findings of an econometric analysis of the impacts on shareholder returns and firm level performance of pro-worker laws coming into force in China in 2008 (the Labour Contracts Act). The analysis finds that increases in labour protection are negatively correlated with share values in the short run: event study analysis shows that the immediate reaction of investors to the passage of the law was negative. The passage of pro-worker labour law is also correlated with reduced profitability for firms. However, labour law protections are positively correlated to employment levels, capital investment, and total factor productivity (TFP), which in this context is an unobserved residual value signifying technological and organisational efficiencies at firm level. The positive correlations between labour law protections and TFP are most marked in provinces with more developed non-state sectors and higher legal quality. Thus the strengthening of labour laws has produced certain societal benefits (firm-level efficiency and employment levels both rise) even if these do not include augmenting shareholders’ short-term returns (Wang and Deakin, 2019).

Uses of machine learning and related forms of artificial intelligence in law and finance

A significant focus of the project has been on the use of machine learning or artificial intelligence in assessing credit risk. AI is being used in China more as a technique to aid legal decision making. The use of AI in adjudication has been trialled in several Chinese ‘internet courts’. Ding Chen and Simon Deakin were invited to visit the first internet court, the Hangzhou Court of the Internet, in 2018. A paper by Christopher Markou and Simon Deakin (Markou and Deakin, 2019) sets out a conceptual framework for the analysis and evaluation of the uses of AI in legal decision making.

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