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南方财经全媒体记者马嘉璐 卓皙雯 研究员时紫萱 仇雯 吴晓燕 广州报道
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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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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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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。
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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。
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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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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广州数据交易所副总经理沈海认为，数据交易所承担着包括数据合规交易保障者、数据资源整合者、数据流通与开发利用促进者、数据流通基础设施建设者、数据产业市场认知培育者在内的多重责任，要通过提供安全、高效、合规的数据交易平台，促进数据要素的流通和价值释放。
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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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