Abstract
With the development of the times, the financial system is getting bigger and bigger, and the links between the various industries are getting closer, so we need to cluster the financial industry. But how to deal with is a problem, after thinking about comparison we found that we can make some treatment between them. So the purpose of this article is to analyze the spatial distribution characteristics of financial services industry clusters based on big data. Based on the experimental principle of data security, this paper processes some data that is known on the market and unknown within the enterprise, and simulates the experimental process by using the 4-model based V+ on big data evaluation, and then the experimental results are drawn. The experimental results show that our model can analyze the spatial distribution characteristics of industrial clusters by analyzing some characteristics of financial services enterprises.
Highlights
Because of the demand for information in the current era, our whole life has undergone earth shaking changes
Because the significance of financial services is that the whole financial industry plays its multiple functions to promote economic and social development, which plays an important role in the circulation of financial and monetary system in the current era
Due to the national natural regional conditions, natural resource endowment characteristics, historical development track and other reasons, the eastern region has formed its own financial service industry [2]. This systematic comparison of cluster models will help to explore the development of financial industry
Summary
Because of the demand for information in the current era, our whole life has undergone earth shaking changes. Financial globalization relies on financial institutions (banking, insurance, securities and financial information management) and these financial conglomerates form the effective allocation of space-time resources, and through this way of distribution, it becomes a medium for transferring transnational investment or avoiding risks [8]. These financial activities are combined with the flow of international trade, and their root causes are accompanied by commerce, and services and Global trade turn into international trade activities [9]. We analyze the spatial distribution characteristics of financial services industry clusters based on big data [10]
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