Risk Measurement, Analysis, and Prediction Methods for Online Financial Services
DOI:
https://doi.org/10.54097/q7byhn66Keywords:
Financial model, financial technology, data analysis, risk management, big data.Abstract
The analysis and research on the risk of online financial business is divided into four main areas; the construction of metrics, analysis and modeling, risk prediction, and risk monitoring and control. It mainly uses high-frequency data to update the dynamic factor model, converts the results to low-frequency data to derive the systematic risk indicators; based on the Markov interval transformation model, the unpredictable and uncertain mechanisms are used as stochastic variables to identify the characteristics of the risk changes to cope with the Internet financial risks. The study concludes that the Internet financial risk has a certain trend and periodicity, and the presented market is relatively stable; due to the close connection between Internet finance and traditional financial industry, the resonance effect can bring certain risk to the whole financial market, and it is still necessary to pay attention to the changing risk factors and take corresponding risk management measures.
Downloads
References
Y. He, "Enterprise financial risk intelligent control system based on artificial intelligence algorithm," 2021 International Conference of Social Computing and Digital Economy (ICSCDE), Chongqing, China, 2021, pp. 161-164, doi: 10.1109/ICSCDE54196.2021.00045.
D. Yuezhong, X. Xiguo, J. Yongsheng and C. Che, "A New Financial Risk Management Model," 2009 Third International Symposium on Intelligent Information Technology Application, Nanchang, China, 2009, pp. 194-197, doi: 10.1109/IITA.2009.140.
Z. Hua, S. Ji-dong, L. Xin and S. Li-guo, "An Innovative Research on the Mechanism of Integrated Strategic Financial Risk Management in the State-Owned Enterprise Group - Based on the Balanced Scorecard," 2006 International Conference on Management Science and Engineering, Lille, France, 2006, pp. 1696-1702, doi: 10.1109/ICMSE.2006.314063.
X. Peng, "An Integrated Risk Management Model for Financial Institutions," 2009 International Conference on Business Intelligence and Financial Engineering, Beijing, China, 2009, pp. 414-418, doi: 10.1109/BIFE.2009.100.
M. Karimi, F. Moztarzadeh, A. Pakzad, A. Beynaghi and M. Mozafari, "Application of Fuzzy TOPSIS for group decision making in evaluating financial risk management," 2012 International Conference on Innovation Management and Technology Research, Malacca, Malaysia, 2012, pp. 215-219, doi: 10.1109/ICIMTR.2012.6236391.
Li Ze-hong and S. Peng, "The Application of Improved Gray Correlative Analysis in Evaluating of Financial Risks of Enterprise," 2007 International Conference on Management Science and Engineering, Harbin, China, 2007, pp. 1900-1904, doi: 10.1109/ICMSE.2007.4422117.
C. Gang, "Mathematics and applications of risk management in e-commerce," 2009 ISECS International Colloquium on Computing, Communication, Control, and Management, Sanya, China, 2009, pp. 160-163, doi: 10.1109/CCCM.2009.5267956.
Y. Hu and Y. Jiang, "Research on Financial Risk Management Early Warning Method Based on Neural Network," 2022 4th International Conference on Applied Machine Learning (ICAML), Changsha, China, 2022, pp. 425-429, doi: 10.1109/ICAML57167.2022.00086.
Zhang Ying and Sun Houquan, "Research on financial risk management in business activities," 2011 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), Dengleng, 2011, pp. 3259-3262, doi: 10.1109/AIMSEC.2011.6010755.
Qiong Liu, "The construction of enterprise financial risk management system," 2011 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), Dengleng, 2011, pp. 5212-5214, doi: 10.1109/AIMSEC.2011.6010209.
P. Du and H. Shu, "Design and Implementation of China Financial Risk Monitoring and Early Warning System Based on Deep Learning," in IEEE Access, vol. 11, pp. 78052-78058, 2023, doi: 10.1109/ACCESS.2023.3280934.
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
