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https://doi.org/10.62836/iaet.v5i1.0006
Qin, P., Xu, M., Zhao, S., Xin, Y., Huo, Z., Zhang, G., Li, H., Zhong, Q., & Guo, J. (2026). AI Algorithms and Large Models in Financial Intelligence: A Modular Framework for Forecasting, Risk Control, and Enterprise Decision-Making. Innovations in Applied Engineering and Technology, 5(1), 0006. https://doi.org/10.62836/iaet.v5i1.0006
Volume 5, Issue 1, 2026

AI Algorithms and Large Models in Financial Intelligence: A Modular Framework for Forecasting, Risk Control, and Enterprise Decision-Making

This paper presents the framework of AI-finance applications as a system where all the algorithms, large language models and enterprise governance are combined into one system. The proposed framework is based on the concept of financial machine learning, time series prediction, risk management in model, responsible AI theory and four layers that interact with each other (multi-source data sensing, representation learning, decision-oriented modeling, and governance feedback). Apart from enhancing its predictive capabilities, the system can be applied to the real-life financial requirements like credit risk control, portfolio distribution, fraud prevention, regulatory analysis and smart customer service. The authors believe that the idea of financial AI cannot be simplified to a forecasting model but should be developed as a socio-technical capability system where the algorithms, people, institutional systems and business situations are interdependent. In this article, there is a well-organized guide to banks, securities companies, insurance companies, and departments of finance at enterprises who would like to implement large-model software without any risks.

financial intelligence large language models financial machine learning risk control enterprise AI model governance time-series forecasting

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Supporting Agencies

  1. Funding: This work was supported by Postgraduate Education Reform and Quality Improvement Project of Henan Province (Grant No. YJS2025XQLH10), the Henan Provincial Key Science and Technology Research Program (Grant No. 262102211082) and Postgraduate Education Reform and Quality Improvement Project of Henan Province (Grant No. YJS2026ZYJC12).