在笔者看来，此次四部门联手规范数据资产入表，其核心要义在于以成本法为基石，通过四大关键举 措，重塑数据资产的估值逻辑与体系，实现数据资产价值的有效治理。 具体来看，一是严格成本计量，其运作逻辑在于无论数据是自主开发还是外购，其入账价值均以实际发 生的、可直接归属于该资产的支出为依据。这一规定彻底摒弃了对未来价值的虚幻预期，将数据资产价 值牢牢锚定在历史成本上，从源头上遏制了资产泡沫的滋生。 ■田鹏 近日，财政部、国务院国资委、国家金融监督管理总局、中国证监会等四部门联合发布的《关于严格执 行企业会计准则切实做好企业2025年年报工作的通知》提出，企业应当以成本计量内部形成或外购的数 据资源，并加强数据资源相关成本管理，夯实数据资源成本核算基础，不得将以评估等方式得出的金额 直接作为入账和调账的依据。这一监管重拳无疑为数据资产估值乱象戴上了"紧箍咒"。 自2024年《企业数据资源相关会计处理暂行规定》落地以来，A股数据资产入表热情持续高涨。2025年 三季报显示，101家A股上市公司披露的数据资产规模合计达29.71亿元，入表公司数量和规模同比增幅 均接近翻倍。 但热潮之下，数据资产估值缺乏统一的行业标准，进一 ...

在数字经济蓬勃发展的背景下，数据资产已成为制造业数字化转型的核心驱动力。《数据资产驱动苏州制造业数字化转型的机制研究报告》系统阐释了数据 资产的基本内涵、分类体系与关键特性，并构建了从"业务数据化"到"数据资源化"再到"数据资产化"的三阶段演进路径。报告指出，高质量、可治理、结构 化的数据资产不仅是企业优化生产、提升管理效率的基础，更是实现智能决策和商业模式创新的战略资源。尤其在苏州这一制造业重镇，推动数据资产价值 释放对实现产业高质量发展具有重要意义。 报告深入剖析了区块链、人工智能与虚拟现实等前沿技术如何赋能数据资产管理。其中，区块链确保数据确权与可信流通，AI提升数据分析与应用效能， VR则助力高价值数字知识资产的构建。研究还通过多个制造业典型场景——如预测性维护、柔性定制、供应链协同等——生动展示了数据资产如何切实转 化为生产力。例如，某服装企业依托工业互联网平台实现"一人一版"定制，订单响应周期缩短50%，产能提升50%，凸显数据驱动带来的显著效益。 然而，苏州制造业在数据资产管理中仍面临严峻挑战：设备协议不统一导致"数据孤岛"，标准缺失引发"一物多码"，专业人才匮乏制约体系建设，安全顾虑 阻碍数据 ...

Core Insights - The report from Shanghai Jiao Tong University's Shanghai Advanced Institute of Finance indicates a steady growth in the data asset reporting of listed companies, although the growth rate has slowed compared to 2024 [1] Group 1: Non-Listed Companies - As of September 30, 2025, 375 non-listed companies in China have disclosed their data asset reporting, securing a total financing amount of 1.899 billion yuan, with a noticeable slowdown in growth [2] - Local state-owned enterprises are the main contributors to data asset reporting among non-listed companies, with 310 local state-owned enterprises accounting for 82.67% of the total, raising 1.710 billion yuan [2] - The types of businesses and data categories for non-listed companies that have reported data assets are diverse, with the leading sectors being information transmission, software and IT services, and leasing and business services, which together account for 75.50% of the total [2] Group 2: Regional Distribution - The coverage of data asset reporting among non-listed companies has expanded to 27 provincial-level administrative regions, with Shandong and Jiangsu leading [3] - More than half of the companies have chosen to register their data assets on local platforms, indicating a localized trend in registration [3] - The proportion of technology companies among the reporting non-listed companies is significant, making up 33.60% of the total [3] Group 3: Listed Companies - As of August 31, 2025, 109 out of over 5,000 listed companies in A-shares have disclosed data asset reporting, involving a total amount of 2.640 billion yuan, with a steady growth in overall scale but a slowdown in growth rate compared to 2024 [4] - The "intangible assets" category remains the primary method for listed companies to disclose data resources, with 101 companies reporting amounts totaling 1.706 billion yuan [4] Group 4: Industry Trends - The number of financial industry companies reporting data assets has significantly increased by 33% compared to the end of 2024, involving an amount of 0.054 billion yuan, primarily from banks and securities firms [4] - The three major telecom operators have made a notable contribution, with a total reporting amount of 1.600 billion yuan, accounting for 60.7% of the market total [4] - The report introduces a new section on data asset valuation, detailing the concepts, processes, methods, and examples of data asset valuation, while discussing the current challenges and future outlook [4]

Group 1 - As of Q3 2023, 375 non-listed companies in China have disclosed data resource inclusion, securing a total financing amount of 1.899 billion yuan [1] - The implementation of the Ministry of Finance's interim regulations on accounting treatment of enterprise data resources will officially start on January 1, 2024, which aims to standardize the accounting methods for data resources [1] - The growth rate of data asset inclusion is slowing down as companies face more challenges in promoting data assets from "single-point breakthroughs" to "overall promotion" [1] Group 2 - Local state-owned enterprises are the main contributors to data asset inclusion among non-listed companies, with 310 local state-owned enterprises accounting for 82.67% of the total, securing 1.71 billion yuan in financing [2] - The leading industries for data asset inclusion are information transmission, software and IT services, leasing and business services, and transportation, accounting for 75.50% of the total companies [2] - Data asset registration is predominantly localized, with over half of the companies choosing to register on local platforms within their province [2] Group 3 - Among listed companies, 109 out of over 5,000 A-share companies disclosed data resource inclusion, involving a total amount of 2.64 billion yuan, indicating steady growth but a slowdown compared to 2024 [3] - The majority of listed companies report data resources under the "intangible assets" category, with 101 companies accounting for 1.706 billion yuan, primarily using the straight-line method for amortization [3] - The financial sector has seen a significant increase in data asset inclusion, with a 33% rise in the number of companies compared to the end of 2024, mainly concentrated in banks and securities firms [3]

Core Insights - The implementation of data asset recognition for companies has shown steady growth, but the growth rate has slowed down since its initiation on January 1, 2024 [1][2] Summary by Category Listed Companies - The number of A-share listed companies recognizing data resources increased from 40 in mid-2024 to 109 by mid-2025, with total recognized amounts rising from 1.36 billion to 2.64 billion yuan [1] - The "intangible assets" category remains the primary disclosure method, with 101 companies reporting data resources as intangible assets totaling 1.71 billion yuan [1] - Most data resources in intangible assets are generated through self-development, with straight-line amortization over 3-5 years being the mainstream practice [1] Industry Distribution - The financial sector saw a significant increase in the number of listed companies recognizing data assets, up 33% from the end of 2024, with a total amount of 0.54 million yuan, primarily from banks and securities firms [2] - The three major telecom operators contributed significantly, with a total recognition amount of 1.6 billion yuan, accounting for 60.7% of the market total [2] - Data asset recognition has expanded to cover 25 provincial administrative regions, with an increasing number of high-market-cap companies participating [2] Non-Listed Companies - As of September 30, 2025, 375 non-listed companies have disclosed data asset recognition, with a total financing amount of 1.899 billion yuan [2][3] - Local state-owned enterprises are the main contributors, accounting for 82.67% of the total recognized companies, with a cumulative financing amount of 1.71 billion yuan [3] - The leading industries for non-listed companies recognizing data assets include information transmission, software and IT services, and transportation [3] Challenges and Considerations - There is a gap between top-level design and practical implementation, with many ambiguities in specific rights confirmation, valuation standards, and auditing criteria [4] - Companies face challenges in matching investments with expected returns, as the complexity of data asset recognition requires significant resources [5] - Balancing information disclosure with commercial confidentiality is crucial, as excessive disclosure may risk revealing core algorithms and user data [5]

Core Insights - The Xinjiang Free Trade Zone has achieved 72 provincial-level institutional innovation results in two years, enhancing the level of institutional openness [1][2] Group 1: Institutional Innovations - The innovations cover eight key areas: trade facilitation, investment facilitation, personnel flow facilitation, government management innovation, financial openness innovation, industrial development, business environment, and regulatory oversight [2] - The implementation of a comprehensive regulatory system for bonded aviation fuel has serviced over 9,400 flights, with a monthly supply capacity growth rate of 18% [2] - A new "QR code" rapid customs clearance model for self-driving export vehicles has improved clearance efficiency by 80% [2] Group 2: International Cooperation - The Xinjiang Free Trade Zone is deepening international cooperation with Central Asia, West Asia, and South Asia, exemplified by the collaboration between the Kashgar area and Kyrgyzstan's Naryn region to build an international industrial park [3] - The Urumqi area has pioneered a "business + technology" model to promote bonded aircraft maintenance services and has innovated a comprehensive service model for fruit and vegetable exports, reducing costs per container by 15% [3] - The Horgos area is testing new models for cross-border services in traditional Chinese medicine and tourism, expanding international cooperation in healthcare, culture, and digital sectors [3] Group 3: Business Environment Optimization - The Xinjiang Free Trade Zone focuses on transforming government functions to optimize the business environment, offering over 100 exclusive services for high-level talents through initiatives like the "Red Mountain Talent Card" [3] - Innovative financing tools such as data assets and "Hui Trade Loan" have effectively alleviated financing difficulties for small and micro enterprises [3] - A cross-border settlement platform has been established, supporting transactions in 18 currencies, including the ruble [3][4]

Core Insights - The strategic partnership between People's Data and the China Electronic Technology Standardization Institute aims to enhance the market-oriented allocation of data elements and improve the data ecosystem for high-quality agricultural development [1][3]. Group 1: Partnership Details - People's Data and the China Electronic Technology Standardization Institute will collaborate on various aspects including data infrastructure, standard development, data application, and governance [3]. - The China Electronic Technology Standardization Institute is a key research institution under the Ministry of Industry and Information Technology, focusing on standardization in the electronic information technology sector [3]. Group 2: Objectives and Future Plans - The partnership is a significant outcome of the "People's Roadshow" event, which is part of a broader initiative to facilitate communication between government and enterprises [4]. - People's Data plans to continue organizing events that promote the integration of resources across government, industry, academia, and research to support local industrial development and the digital economy [4].

Core Insights - The strategic value of data assets is increasingly recognized as a key component of corporate competitiveness, driven by the acceleration of the marketization process of data elements [1][3] - The transition of data from elements to assets requires overcoming three core barriers: legal, accounting, and market challenges, making data asset incorporation into financial statements a necessary prerequisite for unlocking data value [2] - The development and utilization of data assets by companies have significantly increased, extending beyond single business segments to include financing, industry integration, and business innovation [3] Company Developments - Beijing Sanwei Tiandi Technology Co., Ltd. recently won a procurement project from China-ASEAN Information Harbor Co., Ltd., indicating recognition of its technology and product strength [1] - Shenzhen Yushun Electronics Co., Ltd. plans to acquire shares in Zhong'en Cloud (Beijing) Data Technology Co., Ltd. to enter the promising data center market, enhancing future growth and profitability [4] Policy Support - Local governments are intensifying policy support to facilitate the incorporation of data assets into financial statements, with measures such as cash incentives and operational guidelines [4][6] - Dongguan City has implemented measures to support enterprises in the initial assessment and incorporation of data elements, while Jiangsu Province has provided clear operational paths for data resource standardization [4] Market Trends - The process of data asset securitization is accelerating, with four data asset-backed securities (ABS) issued since April, totaling 1.774 billion yuan, indicating a shift towards normalized issuance [3][6] - A total of 102 A-share listed companies disclosed data asset information in their 2025 semi-annual reports, with a combined data asset scale of 5.637 billion yuan, reflecting a year-on-year increase of 137.21% in the number of companies and 74.79% in scale [6] Challenges and Recommendations - Companies face challenges in data asset incorporation, including issues with data compliance, ownership definition, and valuation difficulties [2][6] - Experts suggest the establishment of a robust evaluation standard and methodology for data assets, considering factors such as data quality, scarcity, and potential commercial value [7][8] - Companies are encouraged to strengthen data governance capabilities and ensure compliance and security in data management processes [8]

Core Insights - Data, as the fifth production factor, has unique characteristics such as non-competitiveness, replicability, and infinite growth potential, making its value extraction process more complex than traditional production factors [1] - The development of a market for data elements relies heavily on a clear policy framework and implementation pathways, with local data trading institutions and data merchants becoming key drivers [1][2] - The domestic data element market is expected to grow at a compound annual growth rate (CAGR) of approximately 20.26%, surpassing 300 billion yuan by 2028 [6] Current Situation Analysis - The data element market system is gradually improving, driven by policy guidance and industrial construction, focusing on data, technology, and infrastructure [2] - The digital economy's core industries are becoming significant drivers of the overall economic system, with the digital economy scale increasing from 27.2 trillion yuan in 2017 to 53.9 trillion yuan in 2023, doubling in six years [6] Policy Analysis - The improvement of the policy framework for the data industry value chain and the establishment of local data systems are crucial for the circulation of data element value [4] Market Scale Assessment - The data element industry is projected to reach approximately 200 billion yuan by 2025 and exceed 300 billion yuan by 2028, with data processing and analysis being the largest segment [6] Data Value Chain Construction - The establishment of a data value circulation system is supported by advanced technology and regulatory compliance [8] - The construction of a data ownership system based on the "Data Twenty Articles" is essential for efficient data value circulation [11] Data Registration - Data registration is critical for asset ownership delineation and promoting data value release, with a "1+3" policy framework guiding public data resource management [13] Data Value Assessment - The data valuation policy framework is becoming more refined, with public data resource quantification standards emerging as important benchmarks [16] Data Asset Capitalization - The capitalization of data assets is a core practice for realizing data value, with the implementation of regulations marking a new era for data asset inclusion in financial statements starting January 1, 2024 [19] Data Asset Trading - The data market exhibits a distribution pattern of "internal cold, external hot," with off-market transactions dominating due to their flexibility and customization [21] Industry Practices - The financial sector is expected to see a CAGR of approximately 19.06%, reaching over 100 billion yuan by 2028, driven by data element integration [31] - The industrial manufacturing sector is projected to grow at a CAGR of about 24.22%, with a focus on high-quality data sets and trusted data spaces [34] - The healthcare industry is anticipated to grow at a CAGR of around 23.69%, emphasizing the compliance of personal health data applications [36] Trends - High-quality data set construction is becoming a key factor in advancing the artificial intelligence industry, transitioning from "point breakthroughs" to "holistic development" [39] - The establishment of trusted data spaces will be crucial for ensuring the circulation and high-value application of data elements [42]

Core Points - The State Council of China has approved a comprehensive reform pilot plan for market-oriented allocation of factors in ten regions, including Beijing's urban sub-center and the Guangdong-Hong Kong-Macao Greater Bay Area, to enhance the efficiency of resource allocation and promote a high-level socialist market economy [1][2]. Group 1: Technology Factor Allocation - The plan emphasizes the need to break down barriers in the technology transfer chain and promote the transformation of scientific and technological achievements into productive forces [4]. - It encourages the integration of technology and capital, supporting financial institutions to provide more financial products for technology transfer and transformation [4]. Group 2: Land Factor Allocation - The reform aims to explore land management system reforms, including optimizing land use and promoting mixed-use land development [5][6]. - It encourages the revitalization of idle and inefficient land through market-oriented approaches and supports the establishment of a unified urban-rural construction land market [6]. Group 3: Human Resource Allocation - The plan seeks to facilitate the social mobility of labor and talent by broadening the recognition of foreign professional qualifications and enhancing the recruitment of high-level professionals [7][8]. - It aims to stimulate innovation and entrepreneurship among talents by allowing flexible compensation structures and improving cross-border financial services [8]. Group 4: Data Factor Allocation - The initiative includes establishing rules for data circulation, enhancing public data sharing mechanisms, and promoting the development of new data-driven industries [9][10]. - It supports the creation of standardized contracts for data transactions and the implementation of a "ten-hundred-thousand project" to advance data application scenarios [10]. Group 5: Capital Factor Allocation - The plan emphasizes increasing effective financial service supply to support the real economy, including the establishment of merger funds and promoting direct and indirect financing [12][13]. - It encourages higher levels of financial openness and cooperation, facilitating cross-border financial services and supporting the development of a global wealth management center [13]. Group 6: Environmental Resource Allocation - The reform aims to construct a green factor trading mechanism and explore the realization of ecological product value [13][14]. - It emphasizes the importance of integrating environmental goals with resource allocation to promote sustainable development [14]. Group 7: Overall Efficiency Improvement - The plan focuses on enhancing the collaborative allocation efficiency of various factors, particularly in emerging industries such as artificial intelligence and life sciences [25][26]. - It aims to optimize resource allocation efficiency and effectiveness through market mechanisms and prevent undue government intervention in price formation [25].