Research on the optimization and coordination mechanism of early warning indicators for financial crises under the trend of financial regulatory innovation

Shixuan Xu

doi:10.54254/2977-5701/2025.26202

Journal of Applied Economics and Policy StudiesOpen access

Research on the optimization and coordination mechanism of early warning indicators for financial crises under the trend of financial regulatory innovation

Research Article

Open Access

Research on the optimization and coordination mechanism of early warning indicators for financial crises under the trend of financial regulatory innovation

Shixuan Xu ^1*

¹ School of Business, City University of Macau, Macau, China, 999078

^*Corresponding author: 942711512@qq.com

Published on 27 August 2025

JAEPS Vol.18 Issue 8

ISSN (Print): 2977-571X

ISSN (Online): 2977-5701

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Abstract

To effectively prevent the outbreak of financial crises, constructing a resilient early-warning mechanism now constitutes a core mandate in macroprudential supervision. This paper employs literature review methods, combined with case analysis and the macroprudential regulatory framework, to explore optimization methods for early warning indicators of financial crises under new trends in financial regulation, and proposes innovative approaches. The paper investigates how to identify and quantify the three key drivers of financial crises: macroeconomic imbalances, market over-speculation, and financial institution risks; innovative approaches leveraging high-frequency financial datasets with ensemble learning algorithms to enhance the real-time accuracy of early warning indicators; the synergistic effects of cross-level regulatory information sharing, multi-stakeholder collaborative processes, and two-way feedback mechanisms; and demonstrates that constructing a multi-dimensional indicator system covering macro, market, and institutional levels can comprehensively reflect the accumulation and propagation of systemic risks. The utilization of big data feature engineering and machine learning models has significantly improved the prompt detection of warning signals, resulting in a marked decrease in false alarm rates. Information sharing and multi-party collaborative warning processes, combined with two-way feedback between market participants and regulators, have achieved closed-loop management and synergistic efficiency gains in the warning system.

Keywords:

financial crisis, risk warning, collaborative regulatory mechanism, big data, new trends in financial regulation

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References

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References

[1]. Fang, S. (2024). Research on the financial risk early warning indicator system for commercial banks in China.Financial Customer, 12, 15–17.

[4]. Zhang, J. (2023). Research on the financial risk warning indicator system for commercial banks.Chinese Collective Economy, 30, 121–124.

[5]. Yu, M. (2022). Analysis of risks and preventive measures in the financial economy.China Market, 35, 42–44.

[6]. Wu, W., Jiang, H., & Lu, C. (2022). Reconstruction and effectiveness of systemic financial risk warning indicators: A perspective based on financial innovation.Financial Forum, 27(10), 23–32.

[7]. Zhao, Y. (2022). Early warning analysis of systemic financial risk levels based on the entropy method.Industrial Innovation Research, 7, 115–117.

[8]. Du, R. (2022). On the financial risk warning indicator system of Chinese commercial banks.China Collective Economy, 9, 112–113.

[9]. Liu, X. (2022). Analysis of the construction strategy for a financial risk statistical monitoring and early warning indicator system.Finance and Economics, 6, 11–13.

Cite this article

Xu,S. (2025). Research on the optimization and coordination mechanism of early warning indicators for financial crises under the trend of financial regulatory innovation. Journal of Applied Economics and Policy Studies,18(8),32-36.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Journal: Journal of Applied Economics and Policy Studies

Volume number: Vol.18

Issue number: Issue 8

ISSN: 2977-5701(Print) / 2977-571X(Online)

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