The banking industry is a data-driven industry. In the process of providing financial services, a large amount of user data, transaction data and external data have been accumulated. Data has become a critical asset in the banking industry. The banking industry makes static data flow through data mining, analysis and application. On the one hand, it can empower the development of existing businesses and better realize digital transformation; on the other hand, it can make accurate portraits of customer groups and fully understand customers. demand, and build truly "customer-centric" financial products and services.
For banks, data governance is critical. A few days ago, the 2021 annual reports of the six major state-owned banks have been released successively, all of which specifically mentioned "data governance". In addition to the Agricultural Bank of China, the annual reports of the other five major state-owned banks also involved data governance-related planning, organizational structure construction, etc. related information.
In order to further understand the status quo of data governance of the six major state-owned banks, Zero One Think Tank combined the definition of data governance and regulatory trends, and took stock of their progress and innovation in data governance from the aspects of data governance structure construction, data standard promulgation, and data platform construction. .
1. Definition of Data Governance and Regulatory Policies
In 2018, the China Banking and Insurance Regulatory Commission clarified the definition of data governance for the first time in the "Guidelines for Data Governance of Banking Financial Institutions". It is a dynamic process to formulate and implement systematic systems, processes and methods to ensure unified data management, efficient operation, and full play of value in business management.”
It can be seen from the definition that data governance has three elements: one is to build a unified governance structure; the other is to formulate systematic systems and standards; the third is to be able to play the value of data in the end.
With the release of the "Guidelines for Data Governance of Banking Financial Institutions", the supervision of data governance in the banking industry has been continuously upgraded. After that, the China Banking and Insurance Regulatory Commission and the central bank issued a number of relevant policies to promote data governance in the banking industry, involving data governance system evaluation, governance capability improvement, and governance system construction. <