Multidimensional Financial Metrics for Corporate Financial Risk Assessment and Early Warning Mechanisms

By constructing a comprehensive multi-dimensional financial index evaluation system, this study effectively identifies, evaluates, and forewarns the financial risks of enterprises. Utilizing public financial data from S&P Global and Alpha Vantage, a BP neural network-based enterprise financial risk assessment framework is built, and the KMO method analyzes different risk factors. This comprehensive evaluation model, paired with a risk warning mechanism, assesses financial situations through financial leverage, profitability, solvency, operating efficiency, growth indicators, and cash flow indicators. The example analysis shows: 1) The RMSE value ranges from 46.71 to 64.94, indicating high accuracy and stability in predicting financial risk; 2) The R value is very close to 1, demonstrating high stability.

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Publication Details

Journal
Journal of Organizational and End User Computing
Published
2024-08-05
DOI
https://doi.org/10.4018/joeuc.350268
Citations
4
Primary Topic
Advanced Technologies in Various Fields
Type
article
Field-Weighted Citation Impact
1.39
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article

Multidimensional Financial Metrics for Corporate Financial Risk Assessment and Early Warning Mechanisms

Ran Wei, Eugene Y. Wong, Matthew Sun, Zhaoqi Wang
4 citations
Journal of Organizational and End User Computing
Advanced Technologies in Various Fields
1.39
article

Multidimensional Financial Metrics for Corporate Financial Risk Assessment and Early Warning Mechanisms

Ran Wei, Eugene Y. Wong, Matthew Sun, Zhaoqi Wang
article en
4 citations

Abstract

By constructing a comprehensive multi-dimensional financial index evaluation system, this study effectively identifies, evaluates, and forewarns the financial risks of enterprises. Utilizing public financial data from S&P Global and Alpha Vantage, a BP neural network-based enterprise financial risk assessment framework is built, and the KMO method analyzes different risk factors. This comprehensive evaluation model, paired with a risk warning mechanism, assesses financial situations through financial leverage, profitability, solvency, operating efficiency, growth indicators, and cash flow indicators. The example analysis shows: 1) The RMSE value ranges from 46.71 to 64.94, indicating high accuracy and stability in predicting financial risk; 2) The R value is very close to 1, demonstrating high stability.

Journal of Organizational and End User ComputingVol. 36(1)
Hang Seng University of Hong Kong (HK), University of Hong Kong (HK)
Decent work and economic growth
Openalex Percentile: Top 16%
Advanced Technologies in Various Fields
1.39
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