The rapid development of China’s digital economy has generated a massive amount of data resources, which can be used to develop local economies and finances. Professor Zhu Yangyong of Fudan University introduced “data finance” in 2015, suggesting China may be at an opportune moment to activate government data resources and establish data finance.
In 2022, China’s Big Data industry reached a scale of RMB 1.57 trillion, marking an 18% year-on-year growth and becoming a significant driving force behind the development of the digital economy. Promoting “data finance” not only brings tangible income to local governments but also advances the utilization of public data resources, enhancing the value of data as an asset. This stimulates the development of the digital economy and generates substantial economic benefits.
This strategy resembles “land finance” and “land economy,” where local governments profit from monopolizing public data resources and businesses. Through the development of these resources, local governments gain increased returns, leading to mutual promotion and providing funds for economic digitization and development.
With the arrival of the “post-land economy” period, the “land finance” model formed during the “golden age” of real estate faces challenges. Local governments are exploring alternative ways of revenue beyond taxes and land income, with fiscal pressure providing a practical and urgent motivation for localities to promote the development of the data industry.
Local governments are generally in an advanced position in promoting the development of the data-related industry chain, with many regions actively promoting the construction of data centers and aiming to secure a “first-mover advantage” for local development. However, the data industry is still in its initial stages, with immature models, and realizing the value of data resources faces considerable obstacles. As a result, they hope to monetize these investments through data finance.
Researchers at ANBOUND believe that it is not advisable to massively promote data finance while the data industry is still in the exploratory stage. The current development of the data industry faces numerous controversies, obstacles, and uncertainties.
Challenges in data sourcing and development persist, with only ChatGPT gaining traction in China’s AI model research, and significant resources in economic activities remaining undigitized.
While attempts at data trading have commenced, the scale of transactions remains negligible, and more obstacles stem from constraints in developing data resources and applying data, preventing the full realization of data value. Pushing for data finance to gain additional income adds more costs to investments in data applications and stifles various innovations, hindering industrial digitization.
Data finance is a crucial issue in transforming data into an asset, but it faces challenges in pricing, standardization, and circulation, making it difficult to establish exclusive ownership. This requires continuous consolidation at both legal and financial infrastructure levels. Implementing basic legal protection of data ownership requires participation from various stages and roles. The entry of data into the system is still in the initial stages of experimentation, so pushing for rights transfers on top of the foundation of data assets may be premature.
Under the trend of digital economic development, the assetization of data resources is inevitable. Data finance can be explored and experimented with through pilot initiatives, but local governments must balance short-term gains with long-term benefits.
