另一方面，建设可信数据交付管理平台，打造多形态、多密级的数据交付能力，提供一站式、全流程的数据交付服务，建立起覆盖交易前、交易中、交易后的全流程管理与监督体系，实现了数据交易的精细化管理。
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报告建议，数据产品交易市场需要构建市场驱动的透明生态，建立统一规范的基本信息披露标准。各指标之间的相关性表明，在公开交易平台上，越是回归数据要素价值本义的产品，对包括价格在内的信息披露态度会越开放，也更容易寻找到可落地的应用场景和市场空间。在数据交易机构的进场监管下，数据产品均已经过严格的合规审核，进一步规范信息披露机制，有助于与潜在需方达成有效沟通，推动形成“越透明越增值”的正向循环。
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具体而言，在协同优化方面，广州数据交易所通过数据分析，推动金融机构更精准地把握市场需求和资源供给的变化，实现资源的最优配置，从而提升整体运营效率。
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在数据价值挖掘方面，通过与金融机构合作，挖掘数据在金融领域的应用场景和价值，并运用数字技术将原始数据转化为有价值的产品和服务，提供风险评估、客户画像、市场预测等创新点，满足金融机构需求。
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一方面，依托广东数字政府建设的公共支撑能力，建设了多层次数据要素流通交易平台，为数据交易供需双方提供安全、可信、便利、高效的平台化服务，并深度融合行业平台交易体系，实现了场内场外数据交易的高效协同。
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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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激发数据潜力，桥接金融动力 按照“规范、透明、公开”以及“真实可信、合规可控、记录可溯、创新可拓”的原则，围绕打造登记、估值、挂牌、披露四项核心功能，探索数据资产交易市场建设，促进数据要素市场与金融要素市场联动发展。
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然而，基础制度建设的滞后性日益凸显——数据确权机制尚未贯通，导致机构数据“不愿供”；数据流通交易规则仍以各地分散探索为主，市场定价与安全互信机制仍待完善，数据产品“流不动”的困局持续存在。以上种种因素，严重削弱了金融机构在风险定价、精准营销和产品创新等方面发挥数据要素驱动作用，也阻碍了金融资源配置效率和数字化风控水平的提升。
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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。
以广州数据交易所为例，在合规保障方面，其建立了数据流通交易全生命周期安全管控制度体系，强化数据安全、产品安全、系统安全、生态安全管控措施，同时搭建起数据交易分级分类标准、数据质量管理、数据资产管理等数据全生命周期安全管理体系。
深化数据要素市场化配置改革、构建以数据为关键要素的数字经济，发展数据产业是重要举措。去年底，国家发展改革委等部门《关于促进数据产业高质量发展的指导意见》明确指出，数据产业是利用现代信息技术对数据资源进行产品或服务开发，并推动其流通应用所形成的新兴产业，包括数据采集汇聚、计算存储、流通交易、开发利用、安全治理和数据基础设施建设等。贵州做强做优数字经济，促进数据产业高质量发展是题中应有之义。
要素密集度描述了数据产品中数据包的“大小”及“纯度”，是最能体现“数据产品”本义的一项指标。各数据交易机构在该项的得分较为均衡且普遍较高。不过，仍然存在一些产品不含有数据或很少含有数据，以及大批同系列产品字段拆分过于分散的情况。从要素密集度指标细分来看，上海数据交易所得分最高。
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