Prediction and Analysis of Corporate Financial Risk Assessment Using Logistic Regression Algorithm in Multiple...

Area of Science:

• Business and Economics
• Financial Management
• Risk Analysis

Background:

• Global economic expansion increases market pressures and environmental uncertainties for organizations.
• Unstable internal and external environments heighten corporate financial risks.
• Effective corporate financial risk management is crucial for sustained growth and stability.

Purpose of the Study:

• To develop and evaluate a logistic regression model for predicting and analyzing corporate financial risk.
• To enhance early warning systems for financial risks.
• To improve corporate financial management standards and economic advantages.

Main Methods:

• Utilized a logistic regression model for financial risk prediction and examination.
• Analyzed discrete and continuous variables simultaneously.
• Investigated interactions and confounding effects of external variables.

Main Results:

• The logistic regression model demonstrated superior performance in financial risk management.
• Achieved a 16.24% improvement compared to conventional methods.
• The model effectively identifies potential hazards and mitigates financial crisis losses.

Conclusions:

• Logistic regression is a powerful tool for comprehensive financial risk analysis.
• The proposed model offers a practical and effective approach to early warning systems.
• Implementation can lead to better financial decision-making and reduced economic losses.