Discussion on the Establishment of Financial Early Warning System in Non-financial Corporate

The establishment of a financial early warning system (FEWS) in non-financial corporations is critical to mitigating risks arising from internal factors such as poor management, excessive debt, and resource misallocation. Drawing on Ulrich Beck's risk society theory, this study emphasizes the alignment of risk and return to prevent systemic crises, particularly in industries like China's real estate sector, where capital chain fragility highlights the urgency of robust risk control. The proposed FEWS integrates financial statements, business plans, and analytical tools such as cash flow analysis, financial ratios, and Edward Altman's Z-score model. Key indicators include cash flow sufficiency, debt repayment capacity (e.g., interest coverage ratio, asset-liability ratio), profitability (ROE), and operational efficiency metrics. The Z-score model, incorporating liquidity, profitability, and leverage indicators, quantifies bankruptcy risk and categorizes firms into stable, grey, or high-risk zones. Budget management is underscored for its role in resource allocation, risk identification, and process control, ensuring liquidity and operational stability. Principles such as integration, timeliness, comprehensiveness, and risk-return balance guide system implementation, emphasizing governance structures, stress testing, and risk-oriented strategies. By embedding risk management into strategic decision-making and operational workflows, corporations can enhance value creation while safeguarding against financial instability. This framework provides actionable insights for enterprises to navigate uncertainties and sustain long-term growth in volatile economic environments.

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Publication Details

Journal
Financial Engineering and Risk Management
Published
2025-01-01
DOI
https://doi.org/10.23977/ferm.2025.080117
Primary Topic
Safety and Risk Management
Type
article
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Discussion on the Establishment of Financial Early Warning System in Non-financial Corporate

Financial Engineering and Risk Management
Safety and Risk Management
article

Discussion on the Establishment of Financial Early Warning System in Non-financial Corporate

article en

Abstract

The establishment of a financial early warning system (FEWS) in non-financial corporations is critical to mitigating risks arising from internal factors such as poor management, excessive debt, and resource misallocation. Drawing on Ulrich Beck's risk society theory, this study emphasizes the alignment of risk and return to prevent systemic crises, particularly in industries like China's real estate sector, where capital chain fragility highlights the urgency of robust risk control. The proposed FEWS integrates financial statements, business plans, and analytical tools such as cash flow analysis, financial ratios, and Edward Altman's Z-score model. Key indicators include cash flow sufficiency, debt repayment capacity (e.g., interest coverage ratio, asset-liability ratio), profitability (ROE), and operational efficiency metrics. The Z-score model, incorporating liquidity, profitability, and leverage indicators, quantifies bankruptcy risk and categorizes firms into stable, grey, or high-risk zones. Budget management is underscored for its role in resource allocation, risk identification, and process control, ensuring liquidity and operational stability. Principles such as integration, timeliness, comprehensiveness, and risk-return balance guide system implementation, emphasizing governance structures, stress testing, and risk-oriented strategies. By embedding risk management into strategic decision-making and operational workflows, corporations can enhance value creation while safeguarding against financial instability. This framework provides actionable insights for enterprises to navigate uncertainties and sustain long-term growth in volatile economic environments.

Financial Engineering and Risk ManagementVol. 8(1)
Northeastern University (CN)
Climate action
Openalex Percentile: Top 91%
Safety and Risk Management
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