中经记者 郑瑜 北京报道 在数据要素市场化配置与价值转化进程加快背景下，数据从供给到应用再到收益的良性闭环得到有效实 践，正在为构建可持续、高质量的数据市场提供路径参考。 近期，全国首单获批的数据资产证券化产品（以下简称"数据资产ABS"）"华鑫—鑫欣—数据资产1—5 期资产支持专项计划"首期于深圳证券交易所正式发行，完成了数据资产ABS从获批发行走向落地， 从"纸面"走向市场的重要实践。 该项目由南京鑫欣商业保理有限公司（以下简称"鑫欣保理"）作为原始权益人、华鑫证券有限责任公司 （以下简称"华鑫证券"）作为管理人和独家销售机构，首期发行规模1.337亿元，优先级票面利率 2.0%，其中89%现金流均来源于数据资产质押贷款。 多位业内人士告诉《中国经营报》记者，首单数据资产ABS的落地发行，进一步验证了数据这一要素从 场景牵引，到创新激励，最后到成果转化的价值释放机制。数据从"资源"到"资产"，进而走向"资本"的 价值转化链条不仅可以提升各个产业的附加值，还可以使社会各方都充分感受到制度的巨大红利与数据 的无限潜力。 多元企业多维数据入池 华鑫证券透露，本次针对9家不同行业、区域和股权性质的入池企业，采取了 ...

在圆桌论坛环节，专家学者、金融机构代表与数商企业就数据资产评估、法律合规、产品创新等议题展开了热烈讨论。嘉宾一致认为，数据资产证券化需 构建"政、产、学、研、金"协同生态，打通数据确认、估值、流转与融资全链条。 本次交流会通过多元视角的深度分享和实践案例的精彩解析，为数据资产证券化提供了丰富的思想启迪和实践参考。江苏省数据交易所表示，将以更加开 放的姿态与各方携手，重点推进数据交易规则体系完善、数据产权登记、数据流通基础设施建设、数据资产化创新等，构建生态体系，加强跨区域跨领域 合作。 通讯员焦柳方扬子晚报/紫牛新闻记者万承源 在国家数据要素市场化改革持续深化的背景下，数据资产证券化正成为激活数据价值、赋能实体经济的重要金融创新工具。9月24日，由江苏省数据交易 所主办的"苏数引领数资融通——数据资产证券化创新业务交流会"在南京举办。本次会议汇聚了政府代表、学术专家、金融机构、数商企业及数据资产化 实践先锋，共同探讨数据资产证券化的政策框架、实践路径与未来机遇。 交流会围绕数据资产证券化这一前沿议题，通过政策解读、案例分享、圆桌对话等环节，为与会者提供了理论与实践深度融合的交流平台。会议旨在响应 中央金融工作 ...

□ 本报记者 胡春春 9月5日，伴随着一声响亮的"钟声"，全国首单获批的数据资产证券化项目"华鑫—鑫欣—数据资产1期资 产支持专项计划"正式挂牌。 "数据资产证券化，为中小企业提供低成本、高效率的融资解决方案，对增强企业的数据资产管理、数 据价值挖掘、数字化转型等具有重要意义。"南京大学江苏数字经济研究院研究员巫强表示。 数据资产证券化产品的发展，离不开日益完善的数据要素生态土壤。值得一提的是，在数据资产入表 （正式纳入会计处理范畴）从自选动作转变为规定动作后，数据显示，目前，江苏约100家A股上市公 司涉及数据资产入表。2024年报披露，A股江苏上市公司数据资产入表，涉及金额约21.64亿元。其中， 88家公司将数据资源计入无形资产科目，占披露数据资产入表公司总数的88%。同时，2024年全国数据 市场交易规模突破1600亿元，同比增长超30%。整体看，数据资产证券化展现出巨大的发展需求和潜 力。 这两只产品的成功发行，进一步明确了当前资本市场对数据要素作为新型资产类别的认可。市场普遍认 为，这为数据资产证券化提供了可复制、可推广的实践经验，深交所的"数字金融"产品将逐步进入常态 化发行阶段。 数据资产证券 ...

Core Insights - The article emphasizes the importance of data as a core production factor in business operations, highlighting the need for effective integration and measurement of data resources to maximize their value [1][20] - The introduction of the "Data Twenty Articles" and the "Interim Regulations on Accounting Treatment of Enterprise Data Resources" provides clear policy guidance and operational frameworks for data asset management [1][20] Policy Framework - The "Data Twenty Articles" establishes the institutional foundation for the data factor market, clarifying data ownership, circulation rules, and security requirements, which are essential for the legal and compliant use of data resources [1] - The "Interim Regulations" further detail accounting treatment methods, ensuring that enterprises can scientifically and reasonably recognize, measure, and report data assets while adhering to accounting standards [1] Data Inventory and Assessment - Conducting a comprehensive data inventory is crucial for enterprises to identify the types of data they possess, where it is stored, and which teams manage it, allowing for precise delineation of data suitable for financial reporting [3] - The process of selecting valuable data for inclusion in financial statements is likened to gold mining, emphasizing the need for careful selection to ensure that only valuable data is reported [3] Ownership and Valuation Challenges - Data ownership remains a significant challenge due to historical reasons and cross-border complexities, necessitating industry guidelines to clarify rights and responsibilities [5] - Choosing appropriate valuation methods for data assets is critical, with cost, income, and market approaches each having specific applicability depending on the data's maturity and revenue generation potential [5] Measurement and Reporting - Once data is included in the balance sheet, ongoing measurement is essential, with inventory-type data requiring regular impairment testing and intangible data needing differentiated treatment based on its useful life [7] - Maintaining consistency in measurement methods is fundamental to ensuring the rigor of financial information [7] Risk Management in Data Asset Financing - When considering data assets for collateralized loans, risk management is paramount, with banks typically setting a collateral ratio not exceeding 50% of the assessed value and requiring compliance with registration procedures [9] - Selecting data with strong resilience to depreciation as collateral can effectively mitigate credit risk associated with rapid asset value decline [9] Asset Securitization Challenges - Asset securitization is a viable method for activating existing assets, but it faces challenges such as complex legal relationships, difficulties in cash flow forecasting, and a lack of historical default data [10] - Overcoming these challenges requires learning from successful domestic and international cases and continuous improvement of relevant laws and regulations [10] Strategic Importance of Data Asset Management - Successful inclusion of data assets in financial statements optimizes corporate financial structures, reduces debt ratios, and enhances asset turnover efficiency, particularly for asset-light technology companies [20] - Strengthening talent development through cross-training between IT and finance teams is essential for improving data asset management capabilities [20] - The process of data asset inclusion is a systematic project involving policy interpretation, resource organization, rights definition, value assessment, accounting treatment, and risk control [20]

Core Viewpoint - The company, Daily Interaction, reported a revenue of 218 million yuan for the first half of 2025, highlighting its commitment to embracing artificial intelligence technologies and the steady development of its data intelligence business, with expectations for scalable revenue in the coming year [1] Group 1: Business Performance - The company has maintained steady progress in its core business despite external market pressures, showcasing strong business resilience [2] - Developer services generated a revenue of 24.17 million yuan, reinforcing the company's leading position in the industry [2] - Commercial services achieved a revenue of 40.97 million yuan, while brand services contributed 8.46 million yuan, indicating positive growth potential [2] - Public services generated a revenue of 139 million yuan, focusing on mature products and actively exploring new intelligent products [2] Group 2: Investment in Artificial Intelligence - To capitalize on the opportunities presented by the AI wave, the company has increased its investment in artificial intelligence, establishing an AI division and appointing a Chief AI Officer [3] - Approximately 50 key personnel have been allocated to focus on AI product and project development [3] - The company has developed a series of AI products, including GAI OS, GAI Office, and GAI Store, and launched a high-end AI workstation [3] Group 3: Data Value Enhancement - The company is focusing on its "Data Station" strategy to facilitate the safe and efficient circulation of data among various stakeholders [4] - A nationwide "Hundred Cities, Hundred Scenarios" co-creation plan has been initiated, with successful implementations in multiple cities [4] - The company is actively exploring data asset securitization, having participated in the first approved data asset ABS product in July [4] - The company is committed to the "data + intelligence" development direction and plans to continue exploring AI, despite uncertainties in new product development [4]

Core Viewpoint - The National Development and Reform Commission plans to introduce over ten systems, including data property rights, to accelerate the release of data factor value, which is becoming a new engine for high-quality economic development, particularly in the financial sector [1][2]. Group 1: Data Factor Value in Financial Sector - Data factors are being recognized as valuable assets, with policies facilitating their entry into capital markets through instruments like Asset-Backed Securities (ABS) and Real Estate Investment Trusts (REITs) [2]. - The first closed-end infrastructure securities investment fund based on data centers was launched, with significant market recognition reflected in the buying amounts of 233 million and 388 million yuan for two specific funds [2]. - Data factors are enhancing credit assessment by integrating various data sources, which helps financial institutions with risk pricing and enables small and medium enterprises to convert hidden credit into financing capabilities [2][3]. Group 2: Challenges in Data Factor Financial Applications - Despite initial successes, the integration of data factors into financial services faces challenges such as data ownership confirmation, compliance, and security issues [4][5]. - The complexity of data as an asset, including its non-standard nature and valuation difficulties, complicates its integration into standardized financial products [5][6]. - Policies are being developed to address these challenges, including the establishment of data factor comprehensive experimental zones in various regions to explore data asset circulation models [6].

Group 1: Urban Development and Revitalization - Nanjing has revitalized urban spaces through the activation of 539 land and asset projects, with 212 already revitalized, covering approximately 1.26 million square meters of property and 0.52 million acres of land [1] - The Nanjing Health Grand City, a large-scale commercial project, has opened after a decade of stagnation, featuring a multi-modal transport hub that connects various public transport options, enhancing consumer accessibility [2][3] - The RE-PARK project on Ruijin Road has transformed an old garment factory into a trendy urban space, integrating commercial, cultural, and recreational functions, with an expected annual revenue exceeding 600 million yuan [5] Group 2: Transportation-Oriented Development (TOD) - The newly completed Sojie Complex is Nanjing's first public transport-oriented development (TOD), designed to optimize land use while maintaining its primary function as a bus station, featuring a mix of public transport facilities and commercial spaces [3] - The TOD model aims to enhance land productivity, with projected economic output exceeding 10 million yuan per hectare [3] Group 3: Data Asset Utilization - Nanjing is actively promoting the monetization of data assets, exemplified by the Jiangsu Future Urban Travel Technology Group's participation in a data asset securitization project, raising 5 million yuan [7] - The Nanjing Big Data Group has initiated the market-oriented operation of public data resources, successfully launching multiple public data products and enhancing the efficiency of data asset allocation [8][9]

Core Insights - The first approved data asset securitization project in China, "Huaxin-Xinxin-Data Asset 1-5 Phase Asset Support Special Plan," was officially issued on July 31, marking a significant step in recognizing data as a new asset class in the capital market [1][2] - The project demonstrates the feasibility of using data assets as collateral for financing, breaking the traditional reliance on physical assets and providing a new financing pathway for asset-light data companies [2][3] - The penetration rate of data asset recognition in financial statements is increasing, with a notable rise in the number of listed companies recognizing data assets, indicating a growing acknowledgment of data value [3][5] Data Asset Securitization - The launch of data asset securitization projects this year reflects the capital market's high recognition of data as a new asset class and serves as a breakthrough in facilitating the conversion of data from resources to assets to capital [2][3] - The first data asset-enabled securitization product was issued on July 17, further enriching the asset securitization product matrix and providing new financing options for technology-driven enterprises [1][2] Data Asset Recognition - Data asset recognition in financial statements is essential for the capitalization and marketization of data assets, with the implementation of new accounting regulations set to normalize this practice starting January 1, 2024 [2][3] - The number of listed companies recognizing data assets has significantly increased, from 12 companies with a total of 0.54 million yuan in Q1 2024 to 82 companies with a total of 33.43 million yuan in Q1 2025 [3][5] Market Ecosystem Optimization - Companies are encouraged to strategically plan their data asset management and establish comprehensive internal management systems to optimize the market ecosystem for data assets [5] - The establishment of data asset companies in China has surged, with 3,553 companies currently operating in this sector, indicating a growing market for data asset services [4]

Core Insights - The first approved data asset ABS in China, "Huaxin-Xinxin-Data Asset 1-5 Phase Asset Support Special Plan," was officially issued with a scale of 133.7 million yuan and a priority ticket interest rate of 2.0% [1] - The project involves nine participating enterprises from various regions and sectors, showcasing a diverse range of data asset applications [2] - The issuance aligns with the ongoing policy reforms for market-oriented allocation of data elements, indicating a significant potential for future growth in the data asset market [2][3] Group 1 - The project is managed by Nanjing Xinxin Commercial Factoring Co., Ltd. and Huaxin Securities Co., Ltd., with a focus on selecting quality data assets for collateral [1] - The participating enterprises include listed companies, private "little giant" firms, and state-owned enterprises, reflecting a broad representation of ownership structures [1][2] - The financing amounts for participating enterprises range from 10 million to 25 million yuan, demonstrating the model's versatility and replicability [2] Group 2 - The data assets cover a wide array of application scenarios, including autonomous driving data, smart agriculture data, and intelligent data for construction bidding [2] - The project serves as a valuable operational template for the industry, validating the feasibility of using data assets as collateral for financing [3] - The introduction of data property registration institutions enhances compliance and supports the authoritative establishment of property rights [3]

Core Viewpoint - The successful issuance of the first data asset securitization project in China marks a significant milestone in recognizing data as a new asset class and facilitates the transformation of data resources into capital [1][2]. Group 1: Project Details - The first phase of the "Huaxin-Xinxin-Data Asset 1-5 Phase Asset-Backed Special Plan" was officially issued on July 31, with a scale of 133.7 million yuan and a priority ticket interest rate of 2.0% [1]. - The project involves nine participating enterprises from Jiangsu, Zhejiang, Shaanxi, and Jiangxi provinces, including listed companies and private enterprises, showcasing a diverse range of ownership structures [1]. Group 2: Innovation Mechanism - The project employs an innovative mechanism that allows multiple data assets to be pledged for loans, demonstrating the feasibility of using data assets as collateral for financing [2]. - This model breaks the traditional reliance on physical assets for financing, providing new funding pathways for asset-light data companies [2]. Group 3: Market Impact - Following the approval of this project, there has been an acceleration in financial innovation related to data assets, with other similar projects successfully launched within three months [3]. - The impact of data asset securitization is expected to extend across multiple sectors, promoting the establishment of a unified national data market [3].