在金融市场体系中，保险行业占据着重要地位，而地方国资控股的中小财险作为其中的组成部分，在区域金融 稳定与民生保障中发挥关键作用，但其公司治理长期存在行业监管与国资监管交叉、"三会一层"权责不清、党委前 置研究衔接不畅、治理运行低效、市场化程度不足等结构性问题。原银保监会曾指出，26 家地方国资财险公司中， 超 60% 存在 "三会一层" 运作不规范，导致风险防控失效、决策机制僵化。本文拟通过介绍国任财产保险股份有限 公司（以下简称"国任保险"）过去几年的探索实践，为地方国资中小财险构建中国特色现代金融企业治理体系提供 参考。 文/ 国任保险党委副书记、总裁 邓可 ， 国任保险董事会办公室资深专家 罗曦 1 地方国有中小 财险公司治理面临的 主要问题 从我国保险公司的治理实践来看， 地方控股中小财险公司面临以下几个主要问题： （一） 国资监管与行业监管边界的问题 国资监管主要目标是确保国有资本的保值增值，实现国有经济在关键领域的控制力和影响力。对于地方 中小险企，地方国资监管部门更关注企业的经济效益、资产回报率、国有股权权益、防止国有资产流失 等方面，强调企业在当地金融板块中的战略布局和产业引导作用。 编 者 ...

数字资产交易行业是区块链技术与金融创新深度融合的产物，近 年来伴随全球数字化进程加速，已成为重塑全球经济格局的重要 力量。《清华金融评论》编辑部特地展开征稿活动，就 前瞻 全 球数字资产展开征文。 《清华金融评论》 2025 年第 10 期专题 前瞻 全球 数字资产 数字资产交易行业是区块链技术与金融创新深度融合的产物，近年来伴随全球数字化进程加速，已成为 重塑全球经济格局的重要力量。《清华金融评论》编辑部特地展开征稿活动，就 前瞻 全球数字资产 展 开征文。 以"顶天、立地、学术、政策"为原则，以"分析研究经济金融形势、解读评论经济金融政策、建言献策 经济金融实践"为内容，旨在为政策制定者提供智囊服务，为经营决策者提供咨询服务，为教学研 究者 搭建交流平台，为广大投资者提供投资建议。围绕以下 12 个 选题展开论述， 您也可以根据自己擅长的 领域进行调整 。欢迎各位专家学者踊跃投稿，期待您的原创佳作。 约稿方向 4000～6000字（含图表） 3 查重 知网查重不超过8% 4 投稿格式 5 截止时间、投稿邮箱 2025年9月20日 thfrc@pbcsf.tsinghua.edu.cn 1 全球央行数字货币 ...

拥抱 人工智能 变革，共塑金融未来 文 /清华大学五道口金融学院 讲席 教授、副院长 张晓燕 2025年3月，政府工作报告提出持续推进"人工智能+"行动。这引发了人们对人工智能（AI）的更大关注。作为新一轮科技革命和产业变 革的重要驱动力量，人工智能正以前所未有的广度与深度， 重构各行业的业务形态与 服务模式。金融业因其数据密集型与技术驱动型特 征，正处于智能化变革的前沿，面临深刻的范式转型。如何把握历史性机遇，审慎应对伴生的复杂挑战，已成为金融生态体系亟待解决 的重要议题。这不仅是金融业自身转型升级的内在要求，更是响应国家战略部署、发展新质生产力、建设数字中国和金融强国的重要契 机。 人工智能对金融的战略意义，体现为三大引领性作用。其一， 人工智能 是驱动金融安全与效率提升的 "新基建"。它通过提升风险计量的 穿透性与市场监测的前瞻性，为维护金融体系稳定提供了关键技术支撑；同时以对核心业务流程的自动化决策与流程优化，带来了运营 效能的跃升。其二， 人工智能 是服务普惠金融等 "五篇大文章"的核心驱动力。它以技术力量，消解传统金融服务的边界与壁垒，推动金 融价值从服务少数群体走向赋能整个社会；同时通过对ESG ...

Financial Weekly 每周金融评论 | 目录 CONTENTS 热点聚焦 FOCUS ◎《关于加强商业银行互联网助贷业务管理提升金融服务质效的通知》 2025年9月8日 235 | 证监会 财政部、央行:加强协同,持续 推动我国债券市场平稳健康发展 FINAncial 每周金融评论 . . 10月1日即将实施，网贷监管更趋严格 MEETINGS ◎ 财政部、央行:加强协同，持续推动我国债券市场平稳健康发展 重大政策 POLICIES ◎ 证监会:合理调降公募基金认购费、申购费 EVENTS ◎ 美国8月非农就业数据远逊预期，9月降息几成定局 ◎ 财政部拟第二次续发行2025年超长期特别国债(三期) 車要数字 ◎ 中国8月末外汇储备较7月末上升299亿美元 深 刻 - 展 想 前 ଚଳ T 实 15 专注于经济金融政策解读与建言的智库型全媒体平台 5 元/篇 36 18 电子刊 纸质刊 元/期 432 元/ 180 元/年 010-62773231 载点 聚焦 l 《关于加强商业银行互联网助贷业务管理提升金融服务质效的通知》10月1日即将实施，网贷监管更趋严格 01 2025年4月初，国家金融监督管 ...

对中央银行货币供应管理职能构成潜在冲击。 周小川指出，稳定币发行机构凭借其发行行为实质上获得了货币创造能力，试图履行部分中央银行的职 能，这一趋势亟需引起高度重视。由于该类机构普遍缺乏对货币政策框架及央行运作机制的专业认知，其行为可能带来系统性风险。 此外，现实中准备金托管机制可能存在监管不足或执行不到位的情况。尽管存在准备金约束，稳定币的实际发行规模仍主要由发行机构自主决定。即便实 行100%准备金制度，稳定币仍可能通过存贷、抵押及多重交易渠道衍生出广义流动性，导致实际流通规模难以准确测算，从而干扰央行对货币供应量的 判断与政策制定。 应用场景渗透速度低于此前市场预期。 目前，稳定币的使用已不再局限于原生加密货币生态，正逐步扩展至跨境支付体系、电子商务清算、供应链金融 以及真实世界资产（RWA）代币化等多个领域。市场对稳定币规模的预估，普遍建立在上述应用实现大规模推广的前提之下。 文/《清华金融评论》 杨曦 中国人民银行原行长周小川在ICMA第57届法兰克福年会上发表了以"数 字货币的挑战与潜在风险"为主题的演讲，指出了数字货币尤其是稳定币 落地面临的挑战和潜在风险。他总结时强调，数字货币发展在提升效率、 ...

寿险新业务价值大幅增长 在寿险业务方面，各家险企的中报都突出强调了新业务价值的强劲增长，这显示了行业在转型期的显著成果。 新业务价值（NBV）高速增长。中国平安寿险及健康险业务新业务价值达成223.35亿元，同比大增39.8%。中国人保寿险半年新业务价值在可比口径下同 比增长71.7%。新华保险上半年新业务价值为61.82亿元，同比增长58.4%。中国太保寿险新业务价值同比增长32.3%。这些数据表明，险企正从过去单纯追 求保费规模，转向追求高质量、高价值的业务发展。 投资端表现抢眼 2025年中报显示，各家险企共同构成了行业稳健向好的发展局面。 中国人寿作为行业巨头，总保费达到5250.88亿元，同比增长7.3%，上半年总资产突破7.29万亿元，总投资收益达1275.06亿元，归属于母公司股东的净利 润为409.31亿元，同比增长6.9%，并宣布派发中期现金股利每股0.238元（含税），总计约67.27亿元，彰显其雄厚的资本实力和稳定的盈利能力。 中国平安上半年净利润为680.47亿元，同比下降8.8%，总保费达到5000.76亿元，同比增长1.0%，总资产达13.51万亿元，并宣布派发中期股息每股0.95 ...

Core Viewpoint - The integration of large language models (LLMs) into the banking sector is driving digital transformation, but the inherent opacity of these models presents significant challenges in explainability, necessitating the establishment of a transparent and trustworthy AI application framework to ensure safe and compliant operations [3][4]. Regulatory Constraints on Explainability - Financial regulatory bodies are increasingly emphasizing the need for transparency in AI models, requiring banks to disclose decision-making processes to meet compliance standards and protect consumer rights, which serves as a primary external constraint on LLM applications [6]. - In scenarios like credit approval that directly affect customer rights, algorithmic decisions must provide clear justifications to ensure fairness and accountability. Regulations such as the EU's General Data Protection Regulation (GDPR) mandate transparency in automated decision-making, and domestic regulators also require banks to explain reasons for credit application rejections [7]. - Global regulatory trends are converging towards the necessity for AI model explainability, with frameworks like Singapore's FEAT principles and China's guidelines emphasizing fairness, ethics, accountability, and transparency. The upcoming EU AI Act will impose strict transparency and explainability obligations on high-risk financial AI systems [8]. Technical Explainability Challenges of LLMs - The architecture and operational mechanisms of LLMs inherently limit their technical explainability, as their complex structures and vast parameter counts create a "black box" effect [10]. - The attention mechanism, once thought to provide insights into model behavior, has been shown to have weak correlations with the importance of features in model predictions, undermining its reliability as an explanation tool. The sheer scale of parameters complicates traditional explanation algorithms, making it difficult to analyze high-dimensional models effectively [11]. - The phenomenon of "hallucination," where LLMs generate plausible but factually incorrect content, exacerbates the challenge of explainability. This issue leads to outputs that cannot be traced back to reliable inputs or training data, creating significant risks in financial contexts [12].

Core Viewpoint - The article discusses the recent fluctuations in the RMB/USD exchange rate, highlighting the factors contributing to the RMB's appreciation and the underlying economic conditions that support this trend [2][4][14]. Group 1: Exchange Rate Dynamics - The RMB experienced a series of fluctuations in 2023, initially appreciating in a weak dollar environment, then depreciating due to tariff concerns, before regaining strength [2]. - The RMB's middle price, onshore price, and offshore price have all shown a tendency to converge towards the 7.0 level, indicating a unified market response [2][4]. Group 2: Core Pillars of RMB Valuation - The three core pillars influencing RMB valuation are the China-US interest rate differential, policy risk premium, and purchasing power parity (PPP) [4]. - The narrowing of the China-US interest rate differential has been a fundamental basis for the RMB's appreciation over the past three months, with the nominal interest rate spread decreasing by nearly 50 basis points [4][5]. - The actual interest rate differential has also narrowed, with China's low inflation levels contrasting with rising inflation in the US, enhancing the relative attractiveness of Chinese assets [5][7]. Group 3: Policy Risk and Market Sentiment - The policy risk premium for Chinese assets is decreasing, while it is rising for US assets, driven by concerns over the independence of the US Federal Reserve [7]. - The stability of RMB assets is becoming a rare value in a globally turbulent macroeconomic environment, as China's reforms and policy stability are expected to further reduce the sovereign risk premium [7][11]. Group 4: Purchasing Power Parity - The RMB is currently undervalued against the USD based on purchasing power parity, with the IMF indicating that 1 USD has the purchasing power equivalent to 3.4 RMB [9]. - Long-term undervaluation is attributed to capital account restrictions and international investor concerns regarding China's economic transition [11]. Group 5: Catalysts for RMB Appreciation - The recent strong performance of the RMB is attributed to both internal and external factors, including the central bank's strong midpoint guidance and geopolitical considerations [14][15]. - The influx of foreign capital into the A-share market, driven by a bullish sentiment, has created additional demand for RMB, contributing to its appreciation [19]. - Companies are accelerating their currency conversion from USD to RMB, as the cost of holding USD increases amid anticipated US interest rate cuts [22]. Group 6: Future Outlook - The weak dollar environment is expected to continue supporting RMB appreciation, although challenges such as declining export expectations and the need for domestic demand recovery remain [25].

Core Viewpoint - The August 2025 non-farm payroll data in the U.S. significantly underperformed expectations, reinforcing the anticipation of a Federal Reserve interest rate cut in September, with some institutions predicting a potential cut of 50 basis points [2][3]. Summary by Sections Non-Farm Employment Data - The U.S. Labor Department reported that non-farm employment increased by only 22,000 in August, a substantial decline from the revised 79,000 in July and far below the market expectation of 75,000 [3]. - The unemployment rate rose by 0.1 percentage points to 4.3%, marking a four-year high [3]. Market Reactions - Following the release of the employment data, the U.S. dollar index dropped nearly 0.8%, while spot gold prices surged over 1%, reaching a new historical high of $3,594.76 per ounce [3]. - The weak employment data is attributed to several factors, including job losses in manufacturing due to tariffs, federal government layoffs, and a crisis of trust in data following the dismissal of the former Labor Statistics Bureau chief [3]. Federal Reserve's Policy Implications - The disappointing non-farm data has led to a strong signal for the Federal Reserve to consider rate cuts, with market expectations for a September cut rising to 99% and some predicting a 50 basis point reduction if subsequent inflation data supports it [3]. - The Fed's dual mandate is shifting focus towards employment, as current wage growth is slowing (with hourly wages increasing by 3.7% year-on-year) and labor participation rates are recovering, but demand remains weak, reducing the necessity for rate hikes [3]. Asset Market Impact - The weakening dollar is expected to see the dollar index fall below the critical support level of 98, potentially testing the 96.5-97 range [4]. - U.S. Treasury yields are declining, with the 2-year yield dropping by 11 basis points in a single day, leading to a flight to safe-haven assets [4]. - The stock market is experiencing divergence, with technology stocks benefiting from rate cut expectations, while manufacturing and energy sectors are under pressure [4]. - Emerging markets may find opportunities, with the Chinese yuan appreciating (breaking the 7.15 level) and Hong Kong stocks (Hang Seng Index) potentially benefiting from foreign capital inflows [4]. Economic Concerns - The weak non-farm employment data not only indicates cyclical slowdown but also points to structural risks, with manufacturing and construction sectors continuing to shrink under high interest rates and tariffs [4]. - Government layoffs and a decrease in immigrant labor are further impacting supply, particularly in the construction industry [4]. Upcoming Key Events - On September 9, the annual benchmark revision of non-farm payrolls is expected to be downwardly adjusted by 600,000 to 900,000 jobs, which may further strengthen the case for rate cuts [6]. - The August CPI data will be released on September 11; a decline in inflation would solidify the rationale for rate cuts, while a rebound could lead to market volatility [6]. - The Federal Reserve's meeting on September 16-17 will determine whether the rate cut will be 25 or 50 basis points, depending on the aforementioned data [6]. Conclusion - The recent non-farm data serves as a critical catalyst for the Federal Reserve's policy shift, with a September rate cut now almost certain. However, attention must be paid to the potential discrepancies between policy pace and market expectations, particularly regarding interest-sensitive assets and currency fluctuations [8].

Core Viewpoint - Under the low interest rate environment, brokerage asset management must find its strategic positioning and enhance its ability to serve the real economy while improving active management capabilities to stand out in a competitive market [3][4]. Group 1: Strengthening Service to the Real Economy - Serving the real economy is fundamental for financial institutions and is essential for brokerage asset management to thrive in a low interest rate environment. This can be achieved by accurately identifying positioning, aligning with policy directions, and enhancing connections between resident wealth and the real economy [6]. - Accurate positioning involves focusing on core responsibilities and establishing a long-term strategic direction that prioritizes financial functionality and addresses the financing needs of the real economy [6]. - Emphasizing policy alignment allows brokerage asset management to channel resources into areas that align with national strategies, such as technology finance, green finance, inclusive finance, pension finance, and digital finance [6][7]. - Enhancing connections between resident wealth and the real economy requires a focus on product innovation, resource allocation, and risk management to meet the growing demand for wealth preservation and appreciation among residents [7]. Group 2: Enhancing Research and Investment Capabilities - Research and investment capabilities are the core competitiveness of brokerage asset management and are crucial for active management, product creation, and client service [9]. - Strengthening the research and investment system involves strategic planning, organizational structure optimization, and talent management to balance various factors such as long-term and short-term goals, risk and return, and research and application [9][10]. - Quality assurance in research and investment can be achieved through methodological upgrades, process improvements, and a comprehensive evaluation system that includes accuracy, consistency, and impact [10][11]. - Technological support for research and investment should focus on integrating distributed computing, artificial intelligence, and data science to enhance the efficiency and effectiveness of research processes [11]. Group 3: Improving Asset Allocation Capabilities - Asset allocation is a key strategy for brokerage asset management to navigate the low interest rate environment and the shrinking returns of traditional fixed-income assets [13]. - Optimizing the asset allocation framework involves deepening the research on strategic and tactical asset allocation methods and enhancing the application of quantitative models [13][14]. - Diversifying asset allocation strategies is essential in a competitive market, necessitating a broader range of investment strategies and the establishment of a comprehensive management model for strategy verification and performance evaluation [14].