A Fuzzy Comprehensive Evaluation and Random Forest Model for Financial Account Audit Early Warning

Abstract

Financial risk is objective, developmental, and predictable and has an important impact on the development and operation of enterprises. China’s economy is currently facing major changes, and with the introduction of the “Made in China 2025” plan, deepening supply-side reform, and the rapid development of artificial intelligence, blockchain, and big data technology, the importance of enterprise financial early warning is becoming increasingly prominent. Therefore, by establishing and studying the changes in some financial indicators and establishing an effective enterprise financial early warning model, the signals of financial crisis can be found in time, to prevent and eliminate the hidden danger of enterprise financial crisis and ensure the financial security of the enterprise. The enterprise financial system and business management system are running well. Based on this, a financial early warning model is proposed in this study. First, financial early warning indicators are constructed, and the existing financial indicators are used to establish an early warning indicator system that can detect and identify the financial risks of the enterprise. Then, the financial early warning model based on the fuzzy comprehensive evaluation model and random forest algorithm for fuzzy comprehensive evaluation is constructed using the advantages and noise resistance of the integrated model of fuzzy comprehensive evaluation model and random forest algorithm. The financial data set is used to verify the model constructed in this study. The experimental results show that the model in this study not only is beneficial for enterprises to control financial crisis but also plays a financial early warning role.