Strong financial regulation and the intelligent transformation of enterprises

Baizhen Zhang and Meiting Guo

Economic Analysis and Policy, 2025, vol. 85, issue C, 186-207

Abstract: Artificial intelligence, as a strategic technology leading the future, has emerged as a key field where nations worldwide are actively vying for leadership. In 2018, China issued new asset management regulations, which had a significant impact on the intelligent transformation of enterprises. However, there are no scholars to carry out research. In order to fill this gap, this paper is based on the natural experiment of China's the new asset management regulation released in 2018, this paper analyzes the impact of strong financial regulation on enterprise AI. The primary contribution of this paper is the establishment of a new mathematical model for stringent financial supervision and the deduction that new regulations guide funds by targeting shadow banking, curbing corporate financialization, alleviating financing constraints, and optimizing resource allocation, thereby fostering the intelligent transformation of enterprises. Addressed the shortcomings in existing quantitative research. Finally, further analysis reveals that this positive effect is mainly reflected in state-owned enterprises, high-tech enterprises, private financial development degree is higher, and relatively developed eastern regions and large urban agglomeration areas. This study provides micro evidence for the intelligent effect of financial strong regulation, and provides important policy enlightenment for further releasing the dividends of financial regulation system reform and promoting the high-quality development of real economy.

Keywords: Strict financial regulation; The new asset management regulation; Artificial intelligence; “Crowding Out” effect; “Optimizing Credit Allocation” effect (search for similar items in EconPapers)
JEL-codes: D22 G18 H32 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecanpo:v:85:y:2025:i:c:p:186-207

DOI: 10.1016/j.eap.2024.11.017

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