A Case Study Of C Bank Value Creation Based On Large Data

Under continuous development and progress of today's society,people's demands for finance are richer.The financial scenes are more and more widely applied and the degree and means of competition between the financial field have become increasingly fierce,and constantly intelligent.As an indispensable participant in the market,major commercial banks will focus on optimizing the daily business management activities and improving the key links of the value chain in order to cultivate the core competitiveness of banks.In this paper,we use C bank as the case study object to analyze the value increment of strategic point in value chain of C bank based on large data.Firstly,Bank C is facing a change in the macroeconomic situation of slowing economic growth and economic restructuring,then be influenced by financial disintermediation acceleration and interest rate liberalization falling to the ground,so raising some internal problems existing in the management mode and organization structure.Also the rapid rise of online finance,represented by "yu e bao",has hit traditional commercial Banks.The second part is analysis of the operation status and value chain of C bank.Then the value increment of big data in customer,risk management and innovation is analyzed in third part.Finally,some suggestions are given for the shortcomings of C bank's large data application.The final conclusions are three points: First,massive data through refining,mining,analyzing and summarizing can form information and knowledge,become the unique special assets of C bank.Second,data assets can help C Bank to improve customer value,strengthen risk and innovation management,enhance the quality of value chain's other basic activities and ancillary activities,to further consolidate and promote the C bank market position,and then for the C bank to bring greater Economic Value.Third,there are shortcomings in the application of large data of C bank,we need to strengthen the construction of data culture,speed up the training of data analysis personnel,increase the field of data applications,while learning and mastering data management experience,so as to achieve the goal of more accurate decision-making and more efficient operation.