来源：今日建行 近日，2025全球数商大会（以下简称"数商大会"）在上海国际会议中心举行。本届数商大会，以"数联 全球 商通未来 乘数无界"为主题，聚焦推进实体经济和数字经济深度融合。建设银行参加大会开幕式及 多个分论坛，全方位展示在区块链场景建设、数据要素流通、数商生态服务等数字经济领域的实践与探 索。 在开幕式上，数商大会发布"航运贸易数字化合作创新联盟区块链信用证应用场景"，建行上海市分行作 为首批合作金融机构，依托区块链实现信用证业务全流程上链，破解传统跨境结算瓶颈，为广大外贸企 业提供更安全、便捷的跨境金融服务，助力贸易金融生态建设，获得会议主办方高度关注。为期两天的 活动中，建行先后受邀参加区块链创新高峰论坛、"可信碳数 链通未来"等分论坛，集中展示区块链领 域多项创新实践成果，分享公共数据开发利用经验和建议。 数字经济时代，数据要素的融合应用，既是商业银行数字化转型的关键路径，更是践行金融"五篇大文 章"、赋能实体经济的关键抓手。近年来，建行积极聚焦数据要素流通，以数据服务数据、以创新服务 创新、以新质生产力服务新质生产力，全面构建数字经济时代的发展新模式，多措并举服务数商生态发 展，扩大"数商 ...

Core Insights - The article discusses the significant breakthrough in the financialization of data assets through the issuance of data asset ABS (Asset-Backed Securities), which has clarified the pathways for monetizing data in the capital market [1][2] Summary by Sections Data Asset ABS Overview - Data asset ABS refers to securities backed by stable and predictable cash flows generated from data assets, making data the primary source of revenue [2] - Data asset empowerment ABS involves using data as a credit enhancement tool embedded in traditional assets, enhancing cash flow stability and pricing efficiency [2] Market Activity - As of now, seven data asset ABS products have been successfully issued in 2023, with a total issuance scale of 2.49 billion yuan [1] - The products are categorized into two main types: four data asset ABS and three data asset empowerment ABS [1] Participation and Impact - State-owned enterprises have emerged as the primary initiators in the data asset ABS market, accounting for 71.4% of the projects, while private and public enterprises contributed to the remaining [2] - The average coupon rate for the seven projects is 2.04%, significantly lower than the average interest rate for traditional loans to small and medium-sized enterprises [2] Significance for Innovation and Financing - Data asset ABS provides a new financing channel for technology-driven and asset-light companies, facilitating better planning and operation of data and intellectual property assets [3] - The scale of data asset ABS enriches the asset allocation categories in the capital market, offering stable investment opportunities for conservative institutional investors [3] Challenges and Future Directions - Current challenges include the stability and predictability of revenue models, as some products have not yet established sustainable cash flow [4] - Recommendations for future development include balancing policy incentives with data privacy protection, leveraging technology for value discovery, and designing products that match investor risk preferences [4][5]

Core Viewpoint - The successful implementation of the first data asset pledge financing business in Zhejiang Province by Bank of Communications marks a significant breakthrough in the financialization of data elements, providing 10 million yuan credit support to Zhejiang Lianxin Technology Co., Ltd, a specialized and innovative enterprise in the AI industry [1][2]. Group 1 - The financing solution involves a comprehensive service system that includes data asset value assessment, pledge financing, and risk mitigation, addressing common financing challenges faced by technology enterprises [1][2]. - Zhejiang Lianxin Technology Co., Ltd specializes in psychological big data applications, utilizing vast data to train a psychological application model that provides critical decision-making support and practical application empowerment for governments, enterprises, and individuals [1]. - The innovative financing model combines data asset pledges with policy guarantees, creating a new financing pathway for light-asset, data-heavy technology enterprises [2]. Group 2 - The collaboration between Bank of Communications, Hangzhou Data Exchange, and third-party professional evaluation agencies has established a four-party cooperation mechanism that integrates finance, technology, policy, and expertise [2][3]. - The bank aims to deepen strategic cooperation with data exchange and guarantee institutions, focusing on key technical aspects such as asset valuation modeling and risk pricing to contribute to the construction of a "data element X financial service" ecosystem [3].