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Wu Haifeng: Practice of Data Equality in Inclusive Finance
Release time:2021-12-16Views:

The 4th China Fintech Industry Summit and the 3rd China-Singapore (Suzhou) Fintech Expo, academically supported by the Shenzhen Finance Institute, was successfully held at the Suzhou International Expo Center on October 29. The summit was held in 2021, the opening year of the 14th Five-Year Plan. It focuses on the general environment of the new development of the financial technology industry, with the theme of “convergent technology, comprehending finance, convenient life”, aiming to gather the latest achievements of financial technology and showcase the technology-enabled financial industry.

Professor Wu Haifeng, Executive Director of the Fintech Center of Shenzhen Institute of Data Economy and Executive Director of the Research Center for Intelligent Network and Clean Energy, was invited to deliver a speech on the theme of Practice of Data Equality in Inclusive Finance.

Professor Wu Haifeng firstly explained the concept and definition of inclusive finance, and pointed out the problems in the implementation of inclusive finance. For example, some inclusive financial institutions have a rather one-sided and single-minded understanding of “inclusive finance”, and there are three unhealthy development models: 1. one-sided pursuit of quantitative growth; 2. sacrificing costs in exchange for passing targets; 3. relying on a single model for development. At the same time, Professor Wu also put forward measures and suggestions to promote the healthy development of digital inclusive finance. Firstly, financial institutions should further discover and meet real financial needs; Secondly, financial institutions should provide financial services that can iron out business cycles and income fluctuations to prevent customers from stopping production and affecting their lives due to changes in business cycles and income fluctuations.

At the summit, Professor Wu proposed an Inclusive Finance Solution Version 2.0 - data equality - and the main paths to achieve it. The paths include: firstly, introducing data factorization, to ensure that the initial allocation state of data resources can profoundly affect every aspect of digital economy activities; Second, balancing data security, privacy and value empowerment, to circulate data and share its value, while protecting its privacy and security; Third, focus on data flow, trading and pricing. Finally, he further pointed out that the key to data equality lies in data trading.