基于“课程—方法—评价”三维重构的人工智能赋能金融学专业交叉学科融合教学改革研究

The deep application of generative artificial intelligence and big data is reshaping the financial industry and imposing new interdisciplinary requirements on the knowledge and competence structure of finance graduates, while the traditional single-discipline training model faces a pronounced mismatch between supply and demand. Taking interdisciplinary integration as its analytical perspective, this paper combines literature review, policy text analysis, and reflection on teaching practice to review the research progress and policy requirements of integrating artificial intelligence into finance education, to identify the structural obstacles in the curriculum, pedagogy, and assessment of finance majors, and on this basis to propose a reform path centred on the three-dimensional restructuring of “curriculum–method–assessment.” The proposed path includes a modular “Finance + AI + X” course cluster, real-scenario-driven project-based and human–AI collaborative teaching, and a process-based, diversified and competency-oriented assessment system, so as to provide an actionable reference for interdisciplinary education in finance.