How big data will change the field of credit

In the 21st century, the Internet, mobile Internet, 3D printing, artificial intelligence ...... As Moore's Law says, human scientific and technological innovations are developing rapidly, among which the development potential of big data is most favored. The concept of big data is very hot, but few people really understand the core content of big data, a common and serious misunderstanding is: big data = big data, i.e., big data is a large amount of data. But in fact, the core of big data lies in the intersection and flow of data.

Amazon's former chief scientist Andreas Weigend likened data to the new oil. In the information society, with the acceleration of new technologies such as big data, cloud computing, the Internet of Things, the mobile Internet and other related innovative applications, huge amounts of data are being generated, accumulated, changed, and developed in many fields, such as governmental affairs management, financial industry risk control, industrial development, urban governance, and people's livelihood services. and development. As the international consulting firm McKinsey said, "Data, which has permeated every industry and business function area today, has become an important production factor." China's data application resources are also becoming as essential as factors of production such as land, labor, and capital to promote China's stable economic growth.

Currently, China's Internet and mobile Internet user scale ranks first in the world, with rich data resources and application market advantages, big data part of the key technology research and development breakthroughs, emerging a number of Internet innovative enterprises and innovative applications. However, there is very little cross-fertilization between data, and the fragmentation of credit data sources is the main obstacle that currently affects the application and expansion of big data in China.

For the P2P industry, big data plays a significant role in the field of credit, and it is a big test for the core competitiveness of P2P platforms, and there are a number of enterprises at home and abroad that are engaged in the research and development, experimentation, and even practice of big data credit. It is worth paying attention to the fact that at present, only a few enterprises in the domestic financial industry that successfully use big data to do risk control, such as Ali Microfinance. They mainly use the massive transaction information and capital flow accumulated by sellers to complete the credit of merchants within a few seconds. There are still many problems in the field of data credit, the use of big data for risk control is a long way to go.

Relying on big data risk control relies mainly on timely updated data and the binding of customers to achieve its effectiveness, these two factors are also known as "closed-loop data". Although the central bank agreed at the beginning of the year to eight personal credit agencies to collect data, but because the database is often related to the core competitiveness of the platform, in the absence of a corresponding incentive mechanism, most of them are reluctant to **** enjoy.

On the other hand, the P2P industry's access to credit data is extremely limited, and personal credit data relies partly on the borrowing user's self-submission and partly on the platform's door-to-door collection, and the collection of credit data on the borrowing subject occupies a large amount of manpower and material resources of the P2P lending platforms, resulting in a certain amount of pressure on operating costs and management pressure.

The development history of the United States in utilizing data for credit collection and the logic behind it has certain reference significance for the development of credit collection industry in China. The U.S. Credit Bureau Association (CDIA) has developed a unified standard data reporting format and a standard data collection format for personal credit business, and is extending the U.S. credit data standards to other countries to promote the globalization of the credit system. In addition to financial-related data, data from the e-commerce, telecommunications and retail industries are also being incorporated into the credit collection system.

The characteristics of the U.S. credit collection market can be summarized in 12 words: professional division of labor, clear boundaries, and respective roles. The entire credit system is divided into institutional credit and personal credit, of which institutional credit is further divided into capital market credit and general business credit. In terms of personal credit, it is firstly processed by the three major credit bureaus in the United States, Experian, Equifax and TransUnion, and then credit rating is done by FICO Score and Vantage Score, and finally applied to the actual financial environment, which has formed a mature core industry chain. industry chain.

In addition, the United States, through legislation and industry **** knowledge, its data credit system has also formed a relatively unified standard. Take "personal credit" as an example, its connotation is defined by "5C1S": Character, Capability, Capital, Condition, Collatera, Collateral. Collatera), stability (Stability). At the same time, the boundaries of credit have been clearly delineated, i.e., a *** knowledge has been developed about the data base used to quantify credit.

From the perspective of the historical development path, the United States of America's big data credit is also the first to experience a savage growth, and then sensible integration. In this process, the expansion of application scenarios, technological advances and the improvement of laws and regulations have played a key role in promoting. As China's use of big data for credit collection is still in its infancy, the central bank authorized to carry out personal credit business of the eight credit agencies have not formed a mature industry closed loop, how to coordinate the relevant credit agencies and data source institutions, so that the basic credit information can be **** to enjoy, which requires the two types of institutions to cooperate with each other and the game, but also need to be able to make the appropriate government level to guide, in order to break the stalemate as soon as possible.

It is gratifying to see that accelerating the deployment of big data and deepening its application has become an intrinsic need and inevitable choice for stabilizing China's economic growth. The State Council recently issued the Outline of Action for Promoting the Development of Big Data, which is most notable for opening up government data and promoting industrial innovation. This is the first time that the development of big data in China has been elevated to a national strategy, which is of great significance in promoting the implementation of the national strategies of "Made in China 2025" and "Internet Plus", promoting mass entrepreneurship and innovation, and boosting the development of the economy and society.

The new service model and resource analysis and processing capacity brought by big data will drive the innovation of industrial technology research and development system, promote cross-field and cross-industry integration and collaborative innovation, promote the rapid development of emerging industries while driving the synergistic development of traditional industries, and provide strong support for the construction of a domestic credit society, industry innovation, and reshape the country's competitive advantage

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