Artificial intelligence, data assets and enterprise credit risk
Youyuan Li, Jia Chen, Chaohui XuPurpose
This study aims to examine the impact of data assets on enterprise credit risk and investigate the moderating role of artificial intelligence (AI) in this relationship. Furthermore, it takes into account the heterogeneity caused by differences in ownership structure, innovation intensity, firm size, and regional marketization levels.
Design/methodology/approach
The authors employ regression analysis using a sample of Chinese A-share listed companies from 2007 to 2023 to assess the impact of data assets on enterprise credit risk and test the moderating effect of AI.
Findings
This study reveals a significant negative correlation between data assets and enterprise credit risk. Moreover, the application of AI exerts a significantly negative moderating effect on the relationship between data assets and credit risk mitigation.
Practical implications
This study offers valuable insights for enterprise credit management in the digital economy. First, enterprises and regulators should strengthen the standardized governance and quality certification of data assets. Second, collaborative strategies integrating AI and data assets ought to be tailored to different types of enterprises, so as to balance technological innovation and credit risk control effectively.
Originality/value
This study identifies an innovative pathway through which data assets mitigate enterprise credit risk. It explicitly introduces AI as a moderating variable into the analytical framework linking data assets and enterprise credit risk, and empirically verifies a significant negative moderating effect of AI in this relationship.