Financial inclusion and financial technology: finance for everyone?

Due to technological advances, financial services have been transformed, exhibiting increased competition and market entries by non-banks. In particular, in China FinTech has seen rapid growth with Tech Giants such as Alibaba (Ant Group) rewriting the rules of banking and finance in the twenty-first century. More convenient forms of banking (e.g. mobile banking) promise better access to finance and financial inclusion for poorer households. The merging of finance and technology (e.g. machine learning, artificial intelligence) creates opportunities – but also risks. The special issue on ‘Financial Inclusion and Fintech' provides empirical evidence and theoretical underpinnings to explore the role of FinTech in the context of financial inclusion.

All papers published in the special issue were presented and discussed at the conference on Financial Inclusion and Fintech hosted by SOAS University of London from 25th to 26th March 2019. We wish to thank the Economic and Social Research Council (ESRC) and the National Natural Science Foundation of China (NSFC) for their generous financial support.

The seven papers address a wide range of issues, including barriers to financial inclusion, sustainability, and income inequality. Alternative forms of finance such as peer-to-peer lending platforms and cryptocurrencies are analysed. Empirical evidence is based on a large variety of micro and macro-level data. Finally, theoretical modelling is used to understand the link between financial inclusion and income inequality.

Markose, Arun, and Ozili (2021) focus on the supply-side argument and demonstrate the considerable costs involved in enhancing financial inclusion. This aspect is often overlooked in the policy debate. Peer-to-peer (P2P) lending platforms have rapidly developed in China, offering access to finance for households and small and medium-sized enterprises. As demonstrated by Shao and Bo (2021) and Caglayan et al. (2021), the behavioural difference can predict outcomes on P2P platforms. The paper by Cheah et al. (2021) shows how to predict Bitcoin returns, which will be of interest to academics and practitioners. Demir et al. (2021) contend that financial inclusion significantly reduces inequality – but this effect seems to be stronger in high-income countries. Kanga et al. (2021) show that the diffusion of technology and financial inclusion affect economic growth and investment in fixed and human capital in the long term. Finally, Kling et al. (2021) develop a theory that connects financial inclusion to income inequality. It is not guaranteed that increasing financial inclusion leads to lower levels of income inequality. Theoretical predictions are tested using data on Chinese households.

These papers demonstrate several promising directions for future research. In particular, the idea that better access to finance leads to less inequality and better outcomes needs to be challenged with further empirical and theoretical research. There is a tendency that public services such as health care are privatised and then financed through loans. For instance, out-of-pocket expenses account for more than 60% of health expenditures in India and Bangladesh. It is questionable whether more loans are the only solution.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Lihui Tian

Lihui Tian is a University Professor of Finance, Vice Chancellor of Guangxi University, Dean of the China-ASEAN Finance Cooperation Institute, Dean of the Nankai University Institute of Finance & Development. He also serves in the trustee councils for the China Forum of Financial Development, the China Cloud OS Alliance and the Hong Kong Society for Enterprise Improvement. He is enrolled in China's National Talent Program. He received a Ph.D. in Finance and Economics at London Business School and a Bachelor of Economics at Peking University.

Professor Gerhard Kling holds a Chair in Finance at the University of Aberdeen. He received a Ph.D. in Economics from the University of Tuebingen. He studied Economics and Mathematics.