Abstract
The accuracy of traditional financial system operational risk monitoring is low. Therefore, this paper proposes a method of intelligent financial system operational risk monitoring based on deep learning and improved RPA. Set the financial monitoring index and obtain the warning threshold parameters; Using deep neural network method to mine key risk indicators and obtain reconstruction coefficients of data mining errors of financial system; By improving the RPA method to calculate the fit degree of financial risk, it matches the internal business process of the enterprise; The operational risk monitoring algorithm of financial system is designed to realize the operational risk monitoring of financial system. The experimental results show that the risk monitoring accuracy of the design method is 80.3%, and the overall test threshold of the model is 0.5 after the introduction of non-financial indicators, which shows that it can be applied in practice.
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© 2023 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Yuan, L., Zhu, H. (2023). Research on Operational Risk Monitoring Method of Intelligent Financial System Based on Deep Learning and Improved RPA. In: Fu, W., Yun, L. (eds) Advanced Hybrid Information Processing. ADHIP 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 468. Springer, Cham. https://doi.org/10.1007/978-3-031-28787-9_42
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DOI: https://doi.org/10.1007/978-3-031-28787-9_42
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