Research On The Development Strategy Of Private Wealth Management Of Commercial Banks In The Era Of Big Data

As China’s new economic normal growth, development and the rise of the capital market of private enterprises, China’s high net worth population scale is expanded year by year. Development of financial institutions and private wealth growth driven by dual, diversity and differences in development trend is inevitable, how to conform to the wealth management business innovation trends, bank restructuring and development must be solved. The generation and application of big data, to help commercial banks to meet future customer demand for diversity may provide. And in 2015,China launch big data strategy from a strategic level- "Promoting the development of Big Data Platform for Action", the "Outline" for the first time to the big top-level design data determined to be the basis of national strategic resources, vigorously develop large data industry, prompting large data resources into an important driving force of economic development the new normal. Faced with the opportunities and challenges brought by the era of big data, it is necessary to commercial banks on the basis of the existing advantages for "big data" to develop a new strategy to cope with future Big Data era has brought a variety of changes.This article clear and definite big data content, this is commercial banks relying on its own data and external data, to expand the size of the data in an amount sufficient to meet the time, the value of the effect measure efficiency requirements, while meeting the "4V + 1O" data feature. Based on the analysis of the existing big data technology and data sources of large commercial banks, the commercial banks to explore large data flow processing five main components(data import, data storage and management, operation processing, data mining and data visualization), play to their strengths and technical support advantages, making capital data has become increasingly evident. In this paper, wealth, private wealth, wealth management, private wealth management expanded the definition of the content, private wealth will include credit, because the relationship between commodity currencies mainly as credit relations, credit as a separate intangible economic relations, will make individual economic activities convenience and benefit. Good credit record can make use of the credit system spread in the whole society, so that the credit is a resource and wealth. While combing private wealth management business development context, summed up the experience of foreign countries, providing theoretical and empirical support for the Big Data Bank Private Wealth Management and commercial integration. Based on the status of Big Data and Commercial Bank Private Wealth Management’s analysis, the trends in the era of Big Data is: more accurate marketing, better service, more efficient operations, more advanced risk control. On the basis of experience and analysis of the current situation, this paper explore Big Data technologies to private wealth management opportunities, challenges and risks, Which includes the opportunity to improve the efficiency of information collection and application, and expand business development space, promote the development of bank credit, to achieve comprehensive risk management; Challenges include management decision-making mechanism of the challenges facing the objectivity, the nature of the data management system faces challenges assets, data applications, multi-level application challenges faced by the way, high-speed and efficient data processing technology faces challenges faced by technicians to configure integrated to challenge; Risks include information management risk, strategy implementation risk, legal risk.Case by domestic and foreign commercial banks Private Wealth Management Applications Big Data technologies, including Minsheng Bank used big data product shelf management, China CITIC Bank established intelligent management system, China Everbright Bank build data platform, Morgan Stanley’s efficient operation, DBS Bank using a large data customized investment and Fiodor bank established the intelligence community. application of domestic and foreign commercial banks reveal: wealth management organizations digitize, wealth management services analysis, core business processes of industrialization and banking IT cost reduction, thereby providing a reference for the future of big data in the development of guidance to wealth management applications.Based on Experience of national commercial banks private wealth management development, domestic and foreign banks as well as large data applications in private wealth management, development of commercial banks private wealth management era of big data strategy should be developed as follows: formulating the strategic objectives of large data, "private, face to face, exclusive, targeted" traditional wealth management industry will combine "opening, virtual, at any time, information sharing" the Internet; building a big data management chain within the enterprise to establish a unified data management standards and process specifications to achieve, standardized processes ensure industrial customers massive traffic data for efficient excavation and analysis of customer management, in insight into aspects of market standardization processes to ensure that large intelligent data analysis of enterprise data and historical financial market data, in terms of business operations of large data management standards and process specifications to achieve transparency and efficiency of data processing increased while avoiding operational risk during operation and improve risk management and control efforts; building a scientific organizational structure, based on their gene organization, culture and overall objectives, establish the right organizational structure organized analysis, collaboration and avoid over-reliance on organizations fear the limitations of information; establishing Big Data thinking "customer-centric" customer segmentation service system, customer-centric business philosophy, to promote large customer data to build a panoramic view, thus completing the integration of data, providing customers with a hierarchical data base, our customers’ develop differentiated products and investment programs; implementation of the "fine", "personalized" and "customized" management, carry out a comprehensive customer value analysis, customer behavior analysis undertaken to carry out information analysis, customer relationship to maintain stability; implementation of "talent winning" competitive strategy, based on data-driven decisions to perform, require interdisciplinary knowledge and talent, to achieve the integration and implementation of business, technology, mathematics, behavioral economics and sociology and many other disciplines.