具体来看，GFTCI以"价值创造力、资源禀赋力、环境支撑力"三大维度视角刻画整体格局，在金融科技 发展水平方面重点关注企业、技术、投资、价值创造等维度；在金融科技发展潜力方面重点关注城市整 体经济发展水平、相关产业配套发展情况、人才资源禀赋及科技产业发展带来的影响；在金融科技发展 环境方面重点关注金融科技产业的外部环境、发展制度及城市在全球金融市场中的资源集聚和配置能 力。 作为本期指数的新亮点，GAIFC子指数以"硅基经济学"为理论起点，立足"投入—转化—产出"双循环， 将城市的"AI—金融"关系拆解为两条相互交织的价值链，一条关注"金融如何支持AI产业发展"，另一条 关注"AI如何反向提升金融体系效率与韧性"，探索"AI—金融"在制度环境、产业生态中的嵌入方式，以 及由此形成的持续的价值创造能力。(完) （文章来源：中国新闻网） 中新网上海11月29日电 (高志苗)"全球金融科技中心发展指数(2025)"29日在第七届上海金融科技国际论 坛上发布，指数从产业、技术、人才、制度及环境等评价维度，对全球22个核心城市的金融科技综合水 平，以及金融与AI双向赋能潜力进行剖析。该指数由上海金融科技产业联盟(简称" ...

Core Viewpoint - The article discusses the concept of "Silicon Economics" proposed by Shao Yilei, which signifies a paradigm shift in the global economic system from carbon-based to silicon-based structures driven by artificial intelligence, large models, computing power, data, and chips [1][3][10]. Group 1: Concept of Silicon Economics - Silicon Economics is characterized by the reconstruction of production materials, where intelligence replaces energy as the primary production resource, necessitating the acceleration of silicon-based infrastructure development [3][10]. - Labor dynamics will also change, with a decrease in human labor's share and an increase in the use of labor robots or AI agents [3][10]. - Trade patterns will be redefined, focusing on which countries will be exporters or importers of intelligence, the pricing of these exports, and the currencies used for transactions [3][10]. Group 2: Implications of Silicon Economics - The mission of Silicon Economics is to provide a systematic cognitive map and policy framework for new productive forces and the global intelligent economy [10][11]. - The "Power Triangle" of the silicon world includes the rights to extract intelligence, determine pricing, and settle transactions, with only China and the U.S. currently capable of providing stable supplies of computing power, data, and algorithms [11][14]. - The article highlights a critical transitional phase from "pure carbon-based" to "silicon-carbon hybrid," presenting both opportunities and challenges [11][14]. Group 3: Future Predictions - In the next 500 days, AI is expected to significantly transform the world, with algorithms dominating global productivity, potentially increasing GDP growth from 3% to 10% driven by AI [13][14]. - Stablecoins are anticipated to be linked with intelligence, with the Chinese yuan stablecoin possibly leading a new order anchored in algorithms [13][14]. - Silicon Economics is projected to become the global standard for AI economic capabilities, promoting algorithm governance and competition for intelligent sovereignty [13][14]. Group 4: Development of Intelligent Financial Systems - The Shanghai Artificial Intelligence Finance Institute (SAIFS) has developed a comprehensive "Intelligent Financial New Prototype System" to address the real demands of the financial industry [16][24]. - The system includes the SmithRM financial reasoning model and the Silicon Fin financial intelligence engine, which integrates data, models, intelligent agents, and application scenarios [16][24]. - The financial intelligence engine is designed to enhance data perception, algorithm evolution, computing power metabolism, and internal control immunity, aiming for a collaborative growth with the market [24].

Core Insights - Embracing AI is not optional for the financial industry, as it is becoming a key lever for transformation and growth in the sector [1][5] - The market for AI applications in finance is rapidly expanding, with significant discussions around its impact on financial institutions and ecosystems [1][5] Group 1: AI Integration in Finance - The integration of AI in finance is seen as essential for enhancing the capabilities of the financial system [5] - The 2025 WAIC highlighted the importance of AI in financial applications, showcasing various forums and exhibitions focused on AI and finance [1][2] - Ant Group's CEO emphasized the need for practical AI solutions that address real-world problems rather than theoretical concepts [2] Group 2: Development of Financial AI Models - Ant Group has launched the Finova model evaluation benchmark to assess AI capabilities in finance, promoting industry-wide improvements [2][3] - The introduction of the Agentar-Fin-R1 model aims to create a reliable and controllable AI core for financial applications [2][3] - A comprehensive financial task classification system has been developed, covering various financial sectors and enhancing model performance [3] Group 3: Real-World Applications and Collaborations - The collaboration between major banks and Alibaba marks a significant shift in the adoption of AI technologies in core banking projects [5][6] - Alibaba's AI technologies have shown substantial improvements in operational efficiency, such as a 30% adoption rate for intelligent code generation [5][6] - The focus on AI in financial risk management, particularly in merchant approval processes, highlights the deepening integration of AI in banking operations [6]

Core Insights - Artificial intelligence (AI) is recognized as a key driver for the new productive forces in the financial industry, marking a significant technological revolution [1][2][3] - The "Silicon Fin: SAIFS Financial Intelligence Engine" was launched, representing a breakthrough in AI-driven cognitive modeling and institutional embedding in finance [1][3] - The forum emphasized the importance of global cooperation and interdisciplinary collaboration to ensure that AI promotes sustainable and equitable economic growth [1][2] Group 1: AI and Financial Integration - Shanghai is positioning itself as a hub for AI and financial integration, aiming to create a high-level open and innovative environment [2] - The forum focused on the theme "Activating New Quality in Finance" and discussed how AI can reshape financial genetics and reconstruct economic landscapes [2][3] - The development of AI in finance is linked to broader societal issues such as social equity, economic resilience, and the reformation of global governance models [2][3] Group 2: Silicon Economics - The concept of "Silicon Economics" was introduced, which redefines production factors as computing power, algorithms, and data, moving away from traditional labor-capital paradigms [3] - The mission of Silicon Economics is to provide a systematic cognitive map and policy framework for new productive forces and the global intelligent economy [3] - AI is expected to transform the foundational logic of finance, leading to smarter, more trustworthy, and higher-quality industry development [3] Group 3: Events and Exhibitions - The forum featured a digital dialogue with the late Nobel laureate Herbert Simon, highlighting the ongoing relevance of his theories in the context of AI and economics [4] - The "FinAI Exhibition" showcased the latest AI applications and innovative solutions in finance, providing immersive experiences and interactive digital engagements [5]