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https://doi.org/10.62836/jissh.v3i3.0025
Zhao, S., Guo, J., Zhang, Y., Tang, Y., Qin, P., Xin, Y., Huo, Z., Zhang, G., Li, H., Xu, M., & Zhong, Q. (2026). Reconfiguring Financial Technology Education through AI Algorithms and Large Language Models: An Industry-Responsive Framework for Innovation Capacity Development. Journal of Integrated Social Sciences and Humanities, 3(3), 0025. https://doi.org/10.62836/jissh.v3i3.0025
Volume 3, Issue 3, 2026

Reconfiguring Financial Technology Education through AI Algorithms and Large Language Models: An Industry-Responsive Framework for Innovation Capacity Development

The Financial institutions are now being influenced by the introduction of artificial intelligence (AI) algorithms and large language models (LLMs) to perform risk management, investment analysis, compliance checks, and customer service. The new generation of financial technology experts is expected to have a different knowledge and skill set as well as the ability to work with the current technological advancements. This will be done through the application of educational ecology, which focuses on the development of competencies, the integration of education in industry, and the role of financial technology talent. It identifies enterprise needs and student capabilities, curriculum design based on scenarios, and feedback on the governance of the situation. In this way it can be considered that the AI algorithms and LLMs are not just tools of learning but also means of acquiring interdisciplinary problem solving, engineering skills, and financial literacy and responsible use of AI. The research thus offers a step-by-step procedure towards the creation of an expert in financial technology who is ready to serve the industry with the help of reliable AI in financial services.

financial technology talent development AI algorithms large language models curriculum reform industry-education integration student capability innovation capacity responsible AI governance

References

  1. Bank for International Settlements. Artificial Intelligence and the Economy: Implications for Central Banks. BIS Annual Economic Report. 2024. Available online: https://www.bis.org/publ/arpdf/ar2024e3.htm (accessed on 3 March 2026).
  2. International Organization of Securities Commissions. The Use of Artificial Intelligence and Machine Learning by Market Intermediaries and Asset Managers. IOSCO Final Report FR06/2021. 2021. Available online: https://www.iosco.org/library/pubdocs/pdf/IOSCOPD684.pdf(accessed on 10 March 2026).
  3. National Institute of Standards and Technology. Artificial Intelligence Risk Management Framework (AI RMF 1.0); National Institute of Standards and Technology: Gaithersburg, MD, USA, 2023. https://doi.org/10.6028/NIST.AI.100-1.
  4. Wu S, Irsoy O, Lu S, et al. BloombergGPT: A Large Language Model for Finance. arXiv 2023. https://doi.org/10.48550/arXiv.2303.17564.
  5. Yang H, Liu XY, Wang CD. FinGPT: Open-Source Financial Large Language Models. arXiv 2023. https://doi.org/10.48550/arXiv.2306.06031.
  6. Xie Q, Han W, Zhang X, et al. PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Finance. arXiv 2023. https://doi.org/10.48550/arXiv.2306.05443.
  7. Kurshan E, Shen H, Chen J. Towards Self-Regulating AI: Challenges and Opportunities of AI Model Governance in Financial Services. In Proceedings of the ICAIF ′20: ACM International Conference on AI in Finance, New York, NY, USA, 15–16 October 2020. https://doi.org/10.1145/3383455.3422564.
  8. Cao Z, Feinstein Z. Large Language Model in Financial Regulatory Interpretation. arXiv 2024. https://doi.org/10.48550/arXiv.2405.06808.
  9. National Institute of Standards and Technology. Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile; National Institute of Standards and Technology: Gaithersburg, MD, USA, 2024. https://doi.org/10.6028/NIST.AI.600-1.

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).