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Neural Network Technology-Based Optimization Framework of Financial and Management Accounting Model
1Wuhan College, Wuhan 430000, China.
Artificial Intelligence (AI) enhances financial management. An AI-based BP Neural Network (BPNN) model achieves over 90% accuracy in predicting financial distress, proving its feasibility for early warning systems.
Area of Science:
- Accounting and Financial Management
- Artificial Intelligence in Finance
- Machine Learning for Financial Analysis
Background:
- Traditional financial accounting is evolving into management accounting.
- Accountants need enhanced skills for the AI era.
- Adapting to technological advancements is crucial for business survival.
Purpose of the Study:
- To design an AI-based financial management optimization system.
- To propose an AI-based framework for accounts receivable management.
- To develop and test a financial distress early-warning model using AI.
Main Methods:
- Utilizing an Artificial Intelligence (AI) based approach.
- Implementing a BP Neural Network (BPNN) model for financial distress prediction.
- Iterative processing of listed companies' financial data using neural network algorithms.
Main Results:
- The BPNN model demonstrated significantly higher prediction accuracy compared to other models.
- Prediction accuracy exceeded 90% with extensive historical data.
- The AI-based financial early-warning method proved to be feasible and effective.
Conclusions:
- AI integration is vital for modern financial management.
- BPNN offers a powerful tool for financial distress early warning.
- Continuous professional development is essential for accountants in the AI era.
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