第二十二届中国金融学年会

Nanjing in autumn is a place of outstanding natural beauty and cultural brilliance. At this critical juncture marking the conclusion of China’s 14th Five-Year Plan and the launch of the 15th Five-Year Plan, the 22nd Chinese Finance Annual Meeting aims to further strengthen academic exchange among Chinese finance scholars and promote transformative development in financial theory research and education. In accordance with the resolution of the 21st Council of the Chinese Finance Annual Meeting, this year’s meeting is jointly organized by the Council of the Chinese Finance Annual Meeting and Nanjing University, and co-hosted by the School of Engineering and Management at Nanjing University, Jiangsu Capital Market Research Association, and Jiangsu Key Laboratory of Digital Finance. The conference will be held from October 31 to November 2, 2025, at Nanjing University’s Xianlin Campus. Themed “Paradigm Shift: AI Reshaping Finance”, the meeting will thoroughly implement the spirit of the Third Plenary Session of the 20th CPC Central Committee and align with the strategic deployment outlined in the “CPC Central Committee Decision on Further Deepening Reform Comprehensively and Advancing Chinese Modernization” — particularly regarding high-quality financial development and technological self-reliance. It will focus on paradigm shifts in financial research and restructuring of the financial industry driven by artificial intelligence, exploring practical pathways toward building a strong financial nation. In recent years, breakthroughs in generative AI and large language models — represented by OpenAI and DeepSeek — have profoundly reshaped the foundational logic of financial research. This is not merely an incremental tool upgrade but a far-reaching paradigm shift. The application frontier of AI in finance continues to expand beyond traditional data analysis and rule-based judgment. Today, through multimodal data fusion and machine learning algorithms, AI actively extracts, refines, and reasons over financial knowledge — enabling higher-dimensional insights into the internal logic of complex financial systems and deeper revelations of emergent features and patterns such as risk contagion and behavioral evolution. Yet, a host of new challenges arise: How should academia understand and evaluate this AI-driven new paradigm in financial research? How can we resolve the “black-box” dilemma and insufficient explainability of AI models in finance? How should financial education and talent cultivation respond to the challenges and opportunities brought by the AI revolution? Practitioners in financial institutions face similar issues: How to better integrate AI technologies into existing business processes to enhance service and management efficiency? How to mitigate algorithmic bias and safeguard fairness in financial services? How to assess “unknown risks” posed by AI models and incorporate them into financial risk governance frameworks? Amid this wave of technological revolution, resolving these fundamental questions urgently requires joint exploration by experts and scholars across the financial domain.