摘要
本文研究商业银行数据资产估值的实践方法,基于要素贡献视角提出基于Shapley值评估模型的数据资产估值模型,并采用情景分析与模拟分析方法计算具体银行业务场景下的数据资产价值。本文发现,基于Shapley值的数据资产估值模型具有很好的灵活性和适应性,能够在评估过程中根据数据资产的特性进行实时调整,避免了单一评估方法的片面性,有助于更全面地评估数据资产的价值。在银行数据资产图谱基础上,基于合作博弈理论与数字技术手段评估不同数据对于各类决策模型的贡献度,有助于实现数据资产价值与数据要素收益的公平分配。
This paper examines practical methodologies for valuing data assets of commercial banks.The paper proposes a data asset valuation model based on the Shapley value evaluation framework from the perspective of factor contribution,and employs scenario analysis and simulation methods to calculate the value of data assets under specific banking business scenarios.The findings demonstrate that the Shapley value-based model exhibits remarkable flexibility and adaptability,enabling real-time adjustments based on data asset characteristics during valuation.This approach overcomes the limitations of singular evaluation methods and facilitates a more comprehensive assessment of data asset value.Building upon the data asset mapping of banks,the paper utilizes cooperative game theory and digital technologies to evaluate the contribution of different data to various decision-making models,and help achieve a fair distribution of data asset value and data factor return.
作者
欧阳日辉
李文杰
Ouyang Ri-hui;LI Wen-jie
出处
《现代金融研究》
北大核心
2025年第8期32-46,共15页
Journal of modern finance
基金
国家自然科学基金专项项目“数据市场化配置规律及其对数据价值释放的影响机理研究”(72442026)
国家社会科学基金重大招标项目“数据要素驱动经济增长的理论与政策研究”(23&ZD073)的资助。
