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目前，广州数据交易所已按照数据资源化、产品化、资产化、资本化的完整链路构建起一套涵盖企业数据资产管理各阶段的实施路径。沈海介绍，首先要引导企业经由数据治理、资源盘点与质量管理，达成数据资源化；继而通过数据合规管理、产权登记及应用场景开发，实现数据产品化；随后借助数据交易与资产入表，完成数据资产化；最终以数据资产投融资等手段，推动数据资本化。他认为，通过产权登记明确数据权属关系，既可增强数据交易可信度，使金融机构在获取和使用数据时更加确信数据的来源和合法性，避免权属纠纷，降低法律风险，也可获得数据产权登记证书，作为企业融资增信的依据，拓宽企业融资渠道，促进数据要素市场的繁荣。
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在复用增效方面，促进金融机构之间数据的互联互通，促进数据的复用和共享，形成风险管理、客户服务等方面的协同效应，降低金融机构的信息获取成本，提高数据使用的效率和准确性，进而提升整体服务水平。
在完成数据产权登记试点的基础上，广州数据交易所依托自身专业服务能力，助力央国企、民营企业规范开展数据资源入表工作，先后参与了多项数据资产化相关研究项目，并通过培训、完善数据资产登记交易机制等措施，深化市场对数据资源入表的理解，助力企业实现数据资源从“无形资产”到“合规资产”的转化，为数据要素市场化配置提供了可复制、可推广的实践经验。
报告显示，数据产品交易市场的透明度有待提高，信息披露仍需要继续完善，尤其在价格方面，大部分产品没有公开具体的价格，也没有明确的计费标准；数据使用规范性仍需加强，市场活跃度有待提升。此外，各交易机构对数据产品的理解把握和引导作用显著，产品中“数据”的浓度普遍较高，但同时也存在部分数据产品存在过于追求上架产品数量、将完整产品拆分成多个子产品的情况。
在融合创新方面，通过整合来自不同渠道和不同维度的数据，帮助金融机构获得更全面、更深入的市场洞察，为金融机构提供市场情报和决策支持，推动金融产品的创新和服务模式的升级，设计出更加符合市场需求和客户需求的金融产品和服务。
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其次是稳健系数指标的整体得分也较低，得分差异的主要原因在于数据授权机制变化带来潜在合规风险，数据来源披露不充分，以及使用规范缺乏明确界定。从稳健系数指标细分来看，北京国际大数据交易所得分最高。
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目前，广州数据交易所已按照数据资源化、产品化、资产化、资本化的完整链路构建起一套涵盖企业数据资产管理各阶段的实施路径。沈海介绍，首先要引导企业经由数据治理、资源盘点与质量管理，达成数据资源化；继而通过数据合规管理、产权登记及应用场景开发，实现数据产品化；随后借助数据交易与资产入表，完成数据资产化；最终以数据资产投融资等手段，推动数据资本化。他认为，通过产权登记明确数据权属关系，既可增强数据交易可信度，使金融机构在获取和使用数据时更加确信数据的来源和合法性，避免权属纠纷，降低法律风险，也可获得数据产权登记证书，作为企业融资增信的依据，拓宽企业融资渠道，促进数据要素市场的繁荣。
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在完成数据产权登记试点的基础上，广州数据交易所依托自身专业服务能力，助力央国企、民营企业规范开展数据资源入表工作，先后参与了多项数据资产化相关研究项目，并通过培训、完善数据资产登记交易机制等措施，深化市场对数据资源入表的理解，助力企业实现数据资源从“无形资产”到“合规资产”的转化，为数据要素市场化配置提供了可复制、可推广的实践经验。
贵数所对上架产品的信息披露更为公开透明。据贵数所公开的产品类型信息，数据产品、算法模型、算力基础设施三类产品占比较多，也从侧面反映出贵数所将贵州本地的算力产业优势与数据交易市场进行了有效衔接。
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发展新兴数据产业，是发展新质生产力、塑造发展新动能新优势、促进数据要素价值释放的需要。在权属与安全的责任前提下，数据流通一般没有地域限制，数据价值的开发利用也是一种发散而连绵不绝的过程，价值链随着研发、运用的场景变化而不断延伸。数据产业的空间之所以大，也正是因为场景开发可以遍地开花，是一种想象力大爆发带来的数字生产力使然。而场景创新的主要目的，其实是把人、机器、产品、服务以及情感，进行跨领域、跨时空的聚集、融合，从而实现生产流程再造和产业形态重塑，推动资金、人才等传统要素和新兴数据要素价值跃升。
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分地区来看，各大数据交易机构的金融场景数据产品分别有哪些特征？《报告》统计分析发现，北数所注重数据来源的授权使用；上数所聚焦金融产品应用场景；广数所聚焦数据技术的应用；深数所致力于构建多元场景生态矩阵；贵数所聚焦提供多样化数据服务。
同时，广州数据交易所贯彻落实《行动计划》提出的“以推进数据要素协同优化、复用增效、融合创新作用发挥为重点”的指导思想，通过构建全链条服务体系，着力促进金融领域释放数据乘数效应。
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在完成数据产权登记试点的基础上，广州数据交易所依托自身专业服务能力，助力央国企、民营企业规范开展数据资源入表工作，先后参与了多项数据资产化相关研究项目，并通过培训、完善数据资产登记交易机制等措施，深化市场对数据资源入表的理解，助力企业实现数据资源从“无形资产”到“合规资产”的转化，为数据要素市场化配置提供了可复制、可推广的实践经验。
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