Financial Risk Management of Small and Medium Sized Enterprises in the Internet Environment

Tan, Yaxin

doi:10.1007/978-981-16-7469-3_23

2021 International Conference on Big Data Analytics for Cyber-Physical System in Smart City

2022

DOI: 10.1007/978-981-16-7469-3_23

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Financial Risk Management of Small and Medium Sized Enterprises in the Internet Environment

Yaxin Tan

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Cited by 2 publications

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Construction of an enterprise financial risk management system based on F-score model

2023

Applied Mathematics and Nonlinear Sciences

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With the development of socialist market economy, enterprises are faced with an increasingly complex development environment. In the context of socialist market economy, enterprises can only obtain better development if they continuously promote the improvement of internal control and management system, and effectively carry out financial risk control and management. This paper discusses the procedures and construction measures of the internal control and management system of the enterprise from the requirements and contents of the enterprise financial risk management, using the F-score model. We hope to strengthen the exploration of enterprise financial risk management measures by further improving the enterprise’s internal control system, so as to further enhance the quality of enterprise financial risk management, effectively predict, prevent, control and respond to the relevant financial risks of the enterprise, and build a stable development path for the enterprise.

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Construction of an enterprise financial risk management system based on F-score model

2023

Applied Mathematics and Nonlinear Sciences

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Financial Risk Early Warning Model Combining SMOTE and Random Forest for Internet Finance Companies

Zheng

2024

Journal of Cases on Information Technology

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At present, there have been many achievements on enterprise financial risk early warning model, but relatively few early warning studies focusing on the Internet industry. Research shows that the model has stable recognition accuracy and good prediction performance. The improved SMOTE algorithm based on PCA can realize the equalization of unbalanced data sets and use random forest as a classifier to classify and predict geological data. Because the noise data in the original data set may cause the change of the data distribution after interpolation, it is proposed to combine the PCA algorithm and the SMOTE algorithm, first perform noise reduction and dimension reduction, and then perform data interpolation to improve the classification performance of imbalanced data sets. my country's Internet financial listed companies conduct experiments on research samples, algorithm can better improve the classification accuracy and provide new ideas for the classification and prediction of unbalanced data.

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Financial Risk Management of Small and Medium Sized Enterprises in the Internet Environment

Cited by 2 publications

References 7 publications

Construction of an enterprise financial risk management system based on F-score model

Construction of an enterprise financial risk management system based on F-score model

Financial Risk Early Warning Model Combining SMOTE and Random Forest for Internet Finance Companies

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