Workflow
智能金融创新
icon
Search documents
中国银行原行长李礼辉:智能金融治理应该刚柔并济,洞察、支持、引导创新
Xin Lang Cai Jing· 2025-12-19 02:01
Core Viewpoint - The 22nd China International Financial Forum emphasizes the construction of a secure and efficient intelligent financial ecosystem in the digital economy era, highlighting the need for reliability, interpretability, and economic viability in smart financial innovations [1][18]. Group 1: Financial Models - AI technology is evolving from unimodal to multimodal, enabling the processing of unstructured data and creating direct commercial value in finance [3][21]. - The DeepSeek OCR launched on October 20 can compress text token counts by 90% and accurately identify key information in financial documents, enhancing data processing precision [3][21]. - Financial models must ensure high reliability, interpretability, and economic efficiency, focusing on security against malicious attacks and minimizing errors in financial transactions [5][23]. Group 2: Financial Agents - The evolution of AI from assistants to agents allows for the development of financial agents capable of performing complex tasks in various financial sectors, potentially replacing human roles [7][26]. - AI agents are already being deployed in banks and financial institutions, significantly improving efficiency, such as reducing the time for due diligence report writing from one day to one hour with over 98% accuracy [8][26]. - The shift towards AI in finance necessitates a transformation in human resource management and educational structures to accommodate the new skill requirements [9][27]. Group 3: Data Sharing - The quality and quantity of data are critical for the effectiveness of intelligent finance, with current data sharing facing challenges such as administrative fragmentation and insufficient integration of private data [10][28]. - The "Data 20" initiative aims to establish a framework for data rights, circulation, and governance, promoting both the quantity and quality of data shared [10][28]. - Local regulations and platforms are being developed to facilitate public data sharing and improve the flow of non-public data among financial institutions and tech companies [11][29]. Group 4: AI Competition - AI is recognized as a core technology determining national strength, with competition primarily between the US and China, focusing on computational power [12][31]. - By the end of 2024, China's computing power is projected to account for approximately 26% of the global total, while the US is expected to hold about 37% [13][32]. - The development of AI technologies must navigate geopolitical challenges, with the US imposing restrictions on high-end technology exports to China, impacting the global AI landscape [14][33].