The Essential Role of Big Data: Could it Effectively Mitigate Non-Performing Loans?

Lianhong Qiu, Haidan Su (), Chi-Wei Su and Meng Qin
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Lianhong Qiu: School of Marxism, Guangdong Provincial Party School of the CPC
Haidan Su: Party School of the Central Committee of the Communist Party of China (National Academy of Governance)
Chi-Wei Su: Professor, School of Economics, Qingdao University
Meng Qin: School of Marxism, Qingdao University

Journal for Economic Forecasting, 2024, issue 3, 140-160

Abstract: Investigating the role of digital technology in non-performing loans is crucial for China to prevent financial risks effectively. This analysis utilises the full-sample and advanced sub-sample methods, utilising quarterly data from the first quarter of 2010 to the fourth quarter of 2022, to examine the interplay between big data and non-performing loans, exploring whether big data serves as an innovative tool to reduce financial risks in China. The conclusions ascertain positive and adverse impacts exist from the big data index (BDI) to the non-performing loan ratio (NPLR). The negative effects point out that the accelerated development of big data technology promotes the reduction of financial risks and vice versa. However, the positive influence would refute this idea; the leading cause is that the economic situation might influence non-performing loans. Conversely, there is a negative effect of NPLR on BDI, highlighting that low NPLR accompanied by economic recovery might facilitate investors to invest in big data-related stocks. Under the background of the fourth industrial revolution and unstable international financial environment, this discussion would provide significant suggestions for China to mitigate non-performing loans by applying big data technology.

Keywords: big data; non-performing loans; time-varying; causal relation; China (search for similar items in EconPapers)
JEL-codes: C32 G38 O33 (search for similar items in EconPapers)
Date: 2024
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