<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>With the rapid development of artificial intelligence technology, its application in financial management is increasingly widespread. This study aims to explore how to build a first-class financial management system with the help of artificial intelligence technology. We adopt the improved BP algorithm and ant colony algorithm to conduct in-depth research on financial risk early warning, financial analysis and financial forecasting. In terms of financial Risk early warning, a neural network-based risk early warning model is studied, and the improved model increases the prediction accuracy by 15%. The complex correlation between corporate financial status and market performance is found in economic analysis of multiple financial indicators. In terms of financial forecasting, a combination forecasting model is introduced and the weights are optimized by the ant colony algorithm, which improves the accuracy and reliability of the forecast and reduces the forecasting error by 20%. Artificial intelligence technology can effectively improve the efficiency and accuracy of financial management, provide powerful support for enterprise economic decision-making, and provide new ideas for building a first-class financial management system.</p>
</abstract>

With the rapid development of artificial intelligence technology, its application in financial management is increasingly widespread. This study aims to explore how to build a first-class financial management system with the help of artificial intelligence technology. We adopt the improved BP algorithm and ant colony algorithm to conduct in-depth research on financial risk early warning, financial analysis and financial forecasting. In terms of financial Risk early warning, a neural network-based risk early warning model is studied, and the improved model increases the prediction accuracy by 15%. The complex correlation between corporate financial status and market performance is found in economic analysis of multiple financial indicators. In terms of financial forecasting, a combination forecasting model is introduced and the weights are optimized by the ant colony algorithm, which improves the accuracy and reliability of the forecast and reduces the forecasting error by 20%. Artificial intelligence technology can effectively improve the efficiency and accuracy of financial management, provide powerful support for enterprise economic decision-making, and provide new ideas for building a first-class financial management system.

Artificial intelligence empowers the construction of first-class financial management system

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

With the rapid development of artificial intelligence technology, its application in financial management is increasingly widespread. This study aims to...

Artificial intelligence empowers the construction of first-class financial management system

Publié en ligne: 26 févr. 2024

Pages: -

Reçu: 12 janv. 2024

Accepté: 22 janv. 2024

DOI: https://doi.org/10.2478/amns-2024-0518

Mots clés
Artificial intelligence, Financial management, Risk warning, Financial forecasting

© 2024 Mingdong Wang, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Artificial intelligence empowers the construction of first-class financial management system

Publié en ligne: 26 févr. 2024

Pages: -

Reçu: 12 janv. 2024

Accepté: 22 janv. 2024

DOI: https://doi.org/10.2478/amns-2024-0518

Mots clésArtificial intelligence, Financial management, Risk warning, Financial forecasting

© 2024 Mingdong Wang, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
Artificial intelligence, Financial management, Risk warning, Financial forecasting