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论文编号：	14823
作者编号：	2320213811
上传时间：	2024/6/17 10:51:24
中文题目：	基于数据中台的M银行运营效率提升研究
英文题目：	Research on Enhancing Operational Efficiency of Bank M Based on Data Middle Platform
指导老师：	樊振佳
中文关键字：	大数据；数据中台；数字化转型；运营效率
英文关键字：	Big Data；Data Center；Digital Transformation；Operational Efficiency
中文摘要：	银行运营效率是银行可持续经营的基石。当前大数据和数字化转型已经广 泛改变全球各行各业的运作方式，我国银行业也在经历这种深刻的转变。数据中 台，作为一种新兴的数据组织和使用方式，在我国银行业中逐步展现其在提高运 营效率，降低成本，以及应对复杂市场环境中的关键作用。数据中台的作用是肯 定的，但其建设需要投入大量的人力物力，成本相对较高，因此数据中台建设目 标、建设过程，以及其会对运营效率产生什么影响是各家银行普遍关注的。 本研究首先通过梳理国内外相关文献的主要观点，界定了数据中台和银行 运营效率的概念，并提出了银行运营效率优化方式和运营效率测度方法。随后以 M 银行为例，使用 SWOT 工具对其运营效率现状进行分析，得出需要建设数据 中台的结论，并对其数据中台的建设过程进行阐述，对其建设成果进行了梳理， 结合消费贷的具体业务，分析数据中台对运营效率的影响方式。最后使用实证分 析法，构建 M 银行数据中台发展指数，使用数据包络分析模型测度运营效率， 使用回归模型分析数据中台发展指数对运营效率的影响程度。经过分析得出结 论：数据中台可以通过重建商业银行业务流程或数据整合与标准化的方式来提 升商业银行的运营效率；数据中台主要通过提升商业银行技术进步效率的方式， 来提升商业银行运营效率；数据中台对商业银行运营效率的提升，在数据中台建 设当年对运营效率就会有提升，且第二年提升效果更明显；数据中台的建设对商 业银行的纯技术效率和规模效率会产生负影响。 在数字化转型的潮流中，商业银行普遍关注建设数据中台对提升运营效率 的影响。M 银行作为一家具有代表性的全国性股份制商业银行，其分析结果在 本研究中得到了重点探讨。这些结果不仅对 M 银行本身具有参考意义，同时也 为其他面临相似挑战的商业银行提供了宝贵的借鉴和参考。
英文摘要：	The operational efficiency of banks is the cornerstone of sustainable banking operations. Currently, big data and digital transformation have widely changed the way industries operate globally, and the banking industry in our country is also undergoing this profound transformation. As an emerging way of organizing and utilizing data, the data center gradually demonstrates its crucial role in improving operational efficiency, reducing costs, and coping with complex market environments in the banking industry. The role of the data center is affirmative, but its construction requires a significant investment of manpower and resources, with relatively high costs. Therefore, the specific construction and impact on operational efficiency are widely concerned by banks. This thesis first defines the concepts of data middle platform and bank operational efficiency by reviewing the main viewpoints of relevant literature both domestically and internationally. It proposes optimization methods for bank operational efficiency and measurement techniques. Subsequently, using M Bank as a case study, the current operational efficiency is analyzed using the SWOT tool, concluding the necessity of establishing a data middle platform. The process of constructing the data middle platform is elaborated upon, along with a review of its accomplishments. Furthermore, in conjunction with specific consumer loan businesses, the impact of the data middle platform on operational efficiency is analyzed. Lastly, employing empirical analysis methods, the thesis constructs the M Bank data middle platform development index, measures operational efficiency using data envelopment analysis models, and analyzes the extent to which the data middle platform development index affects operational efficiency using regression models. Through analysis, it is concluded that the data middle platform can enhance the operational efficiency of commercial banks by reconstructing business processes or integrating and standardizing data. It primarily improves the efficiency of technological progress in commercial banks, thereby enhancing operational efficiency. The implementation of the data middle platform results in an immediate improvement in operational efficiency, with a more pronounced effect observed in the second year. However, the construction of the data middle platform adversely affects the pure technical efficiency and scale efficiency of commercial banks. In the trend of digital transformation, commercial banks generally focus on the impact of building data centers on improving operational efficiency. Bank M, as a representative national joint-stock commercial bank, is the focus of analysis in this thesis. These results are not only of reference significance to Bank M itself but also provide valuable reference for other commercial banks facing similar challenges.
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