Romingxiong: Big Data Finance--how to go in the future?

At present, large data finance is in multifaceted state, Ali Group and other large electric dealers take the lead in the market, to accumulate the transaction data to the small and medium-sized micro-enterprises to carry out credit services; Other industries rely on their own industrial data chain, the industry to integrate the internal, closed-loop data financial services; Banks rely on their strong financial strength, the establishment of bank E-commerce platform, with a variety of preferential conditions to attract stores, upgrade the supply chain financial system, the development of intermediary business.

Large data finance as a comprehensive concept, in the future development, the enterprise sits in the data will no longer be limited to the single business, the third party payment, the Informationization financial institution as well as the Internet financial portal all will integrate into the Big Data financial service platform, the Big Data financial service will realize the multiplex business integration on the basis of the recount of each institution.

The author, through the summary of the current situation, has the following views on the future development of large data finance.

The realization of the integration of information flow and financial flow by the electronic business

The Electronic Business finance is the electronic commerce enterprise in the long-term development of the E-commerce platform, the data accumulates and the credit record application inevitable trend, is the commercial credit docking bank credit performance. The electricity merchant started by the net purchase, obtains the sale through the data, the flow, then through the sale accumulates the data, the flow, gathers the stickiness, the data structure and the stratification obvious, to the information flow's response is keen.

The development of the Electronic Business finance can be divided into two stages at present. The first stage is to complete the third party payment, the traditional bank has the payment and credit function of innovation and substitution; the second stage for the electric business wing is gradually abundant, starts to seek with the bank the credit cooperation, represents the example for Jingdong Mall's supply chain financial model. Today, the electronic business of finance can be said to have not developed into the next stage, but the direction of development differences. One side is the financial platform represented by Alibaba, before acquiring the banking licence, to raise funds by means of asset securitization, trust plan and so on, the other side is a financial platform represented by Suningyun, which is directed at the private banking licence, hoping to nationalize the information flow and capital flow after the establishment of the bank. In essence, the two converge are in the grasp of commodity flow, information flow, efficient, low-cost access to capital flow, so as to establish their own complete ecological circle, to the ecological circle to provide one-stop business services to enhance the stickiness of merchants, enhance competitors entry barriers, look forward to the fierce Internet financial competition in the era of a place.

Financial institutions actively build data platforms to enhance user experience

Under the shock wave of cross-border finance, the financial institutions represented by the banks did not sit idly by, and the banks via the electricity dealers and launched the counterattack. Banks to enter the field of electrical business and gene fusion is good for the moment, regardless of the amount of data, the large commercial banks in the data level, especially in the financial data have the advantages of the electricity quotient.

Since 2012, a number of banks, such as the construction Bank, the bank, ICBC and so on are actively deploying their own platform, look forward to retaining the old customers and expand the number of customer data at the same time, so that customer data three-dimensional, and use of stereo data for differentiated services, understand customer consumption habits, predict customer behavior, conduct management transactions, Risk control of credit risk and compliance.

On the other hand, data management and application become a more severe and urgent problem for banking industry than data collection. Commercial banks have taken action on this item. China Minsheng Bank plans to build data standards and large data base platform in 2013 years, 2014 years to build a real-time data integration platform, 2015 to establish a complete enterprise data services to support intelligent services; The Bank of communications uses the intelligent voice cloud product to analyze and process the massive voice data collected by the credit card center every day, Collect information on customer identity, preferences, service quality and market dynamics.

Large data finance realizes large data industry chain division

There is no doubt that big data will be more and more profound in our time. Both veteran IT companies such as IBM and Cisco, and it rookies focused on big data in the Hadoop ecosystem, have grabbed the big data industry chain in just a few years. In the future, who can lead the big data technology, can Chinese manufacturers grab a seat in the big data explosion? How can enterprises in various data links obtain financial inspiration from the operation of large data and establish a service platform that conforms to their own characteristics?

The large data can be divided into six parts, such as data collection, data cleaning, data storage and management, data analysis, data visualization and industrial application. And in every link, there are already different companies starting to occupy the place here.

In data acquisition, traditional IT companies such as Google and Cisco have already started to deploy data collection work. In China, Taobao, Tencent, Baidu and other companies have collected and stored a large number of user habits and user consumption behavior data. In the future, there will be more professional data collection companies for the specific needs of various industries, specialized design industry data collection system.

In the mathematical cleaning, when a large number of complex and disorderly data collection, how to filter out useful data to complete the data clean-up work and pass to the next link, this is with large data industry division of the continuous refinement of the need for increasingly high links. In addition to the old IT companies such as Intel, Informatica, Teradata and other professional data processing companies show greater vitality. In China, such as Chinese-pride data and other similar manufacturers are beginning to emerge.

From the data storage and management, the data storage and management are two subdivision steps. The relationship between these two subdivisions is very close. The way of data management determines the storage format of data, and how data is stored restricts the depth and breadth of data analysis. Because of the high correlation, it is usually more effective to design these two segments by a manufacturer. From the point of view of the manufacturer, IBM, Oracle and other established data storage providers have obvious advantages, they are in the original storage business on the corresponding in-depth expansion, easily occupy a larger market share.

In the data analysis, the traditional data processing company SAS and SPSS have obvious advantages in the analysis. However, data analysis companies based on the Open-source software infrastructure Hadoop have seen a burst of growth in recent years. For example, the Cloudera company, founded in 2008, helps businesses manage and analyze data based on open source Hadoop products. Thanks to its ability to help customers complete customized data analysis requirements, Cloudera has a large number of well-known corporate users, such as Expedia, JPMorgan Chase and other companies, in just five years, with an estimated market value of 700 million.

In the interpretation of data, the data level of large data analysis is reduced to specific industry problems. SAP, SAS and other data analysis companies in their existing business to join the industry knowledge to become the leader in this aspect of competition. At the same time, due to the development of large data wibidata and other professional data reduction companies have also begun to flourish.

In the process of data visualization, the big data really starts to help management practice. By analyzing and imaging the data, the conclusions of large data can be quantified and applied to the industry. This link needs the profession specialized personnel, through the big data to give the inference, unifies the profession the concrete practice to develop the real can change the industry present situation the plan.

In the process of sorting out the data, the enterprise is looking for the card bit of data link. Large data Service platform, as the name suggests, will be based on large data. Unable to squeeze into the data of the six links, it will be difficult to form suitable for their own enterprise path of the large data service platform. Taking the bank as an example, the reason why the bank is actively entering the circle of the electric quotient is the way of squeezing the data acquisition. In the continuous development of the large data service platform, it can be foreseen that there will be six links of data processing enterprises continue to join, competition will be intensified. After entering the enterprise must first find the enterprise in the data processing the focal point.

I think that in the future development of large data, the establishment of data trading platform, in the relevant laws and regulations, the data can be on a unified platform to search for parity and transactions, this is not only the enterprise in the main business outside the data value-added behavior, but also to solve the closed data, data fragmentation provides an effective solution, To achieve synergy between the agencies concerned, more in line with the "data is the asset" spirit.