Open Access
| Issue |
SHS Web Conf.
Volume 225, 2025
2025 3rd International Conference on Financial Management and the Digital Economy (ICFMDE 2025)
|
|
|---|---|---|
| Article Number | 02025 | |
| Number of page(s) | 7 | |
| Section | Finance, Risk & Global Markets | |
| DOI | https://doi.org/10.1051/shsconf/202522502025 | |
| Published online | 13 November 2025 | |
- Chen, L., & Xu, Y. Machine learning for financial risk prediction: Applications in credit scoring and fraud detection. Journal of Financial Analytics, 14(2), 55–70 (2020). [Google Scholar]
- Duan, J., Wang, X., & Liu, Z. Explainable AI in finance: A review of model transparency and regulatory implications. International Journal of Financial Technology, 6(3), 88–102 (2021). [Google Scholar]
- Huang, M., & Li, T. AI-Driven Risk Management in Chinese Securities Firms: Empirical Evidence and Industry Impacts. China Finance Review International, 11(1), 34–49 (2023). [Google Scholar]
- Wang, J. Sentiment Analysis and Market Prediction in the Age of AI. Financial Technology Studies, 9(4), 102–118 (2022). [Google Scholar]
- Zhang, Q., & Liu, H. Artificial Intelligence in Financial Services: Challenges and Opportunities. Asia-Pacific Journal of Finance and Economics, 18(1), 45–67 (2021). [Google Scholar]
- Li, S., & Feng, Y. Regulatory Responses to AI in Financial Services. Journal of Financial Regulation and Compliance, 28(3), 198–213 (2020). [Google Scholar]
- Gao, R. Big Data and AI in Modern Investment Banking. Global Finance Review, 7(2), 77–92 (2019). [Google Scholar]
- Yu, C., & Wang, F. Enhancing Risk Prediction Accuracy Using Hybrid AI Models. Journal of Computational Finance, 19(1), 120–138 (2022). [Google Scholar]
- Tang, Z., & Zhou, J. Financial Risk Early Warning Systems Based on Deep Learning. Quantitative Finance Research, 15(4), 210–229 (2021). [Google Scholar]
- Ren, M., & Shi, K. Cross-Department AI Integration in Securities Firms: A Case-Based Study. Journal of Applied Finance and Technology, 13(1), 99–115 (2023). [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.

