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.
Authors
- Ran Wei (ORCID: https://orcid.org/0000-0002-1889-0158)
- Eugene Y. Wong (ORCID: https://orcid.org/0000-0001-7416-9405)
- Matthew Sun (ORCID: https://orcid.org/0009-0002-5128-6259)
- Zhaoqi Wang (ORCID: https://orcid.org/0009-0008-3849-1649)
Institutions
- Hang Seng University of Hong Kong (HK)
- University of Hong Kong (HK)
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