The traditional credit evaluation model judges the credit status of this person through logistic regression based on a person's loan history and repayment performance. The data sources of big data credits are very extensive, including e-commerce, social networks and search behaviors, which generate a lot of data. The big data quotation of Zhongtou Ruike (Beijing) Technology Co., Ltd. is to integrate a large number of variables with only minor influences through nonlinear algorithms, so that the overall performance of the model is better. The credit model is the core support of credit reporting. The CIC Risk Model is more from the theoretical analysis of the advanced credit model in the United States. The platform has been used and recognized by all parties.

The essence of credit is to collect and record credit information and provide it to decision makers after finishing processing. Today, CIC Ruike (Beijing) Technology Co., Ltd. uses big data, cloud computing, face recognition, depth algorithms and other technologies to make the credit has a broader meaning and use.

Any information can be credit data that, after analysis, is used to prove the credit status of a person or business. Because of the wide coverage of data and many dimensions, it has formed a broad-based credit information, that is, big data credit. To be valuable big data, there are three essential elements: First, the coverage is wide enough and the users need to be large enough. For example, the data of UnionPay and Telecom; secondly, the dimension should be effective and can be effectively converted into structured data. For example, the data of e-commerce; third, the information should be stable.

For the fast-growing Internet finance industry, using big data to help determine risk and developing business is an inevitable choice. At present, big data credit has spread from financial services to life services. Among them, the two core values ​​are: prevention of fraud risks and credit risks.

In a sense, many companies say they are doing big data, but in fact they can only say that it is & lsquo;multiple data & rsquo;. For example, banks and e-commerce, the bank's data is mainly in deposits and loans, intermediary business, exchanges, etc.; e-commerce is mainly trading, payment. Their data volume is super large, but there are few data types. If you just know how much a person consumes each month and how much you earn, you can't accurately describe a person. Similarly, if you only know the search record of this ID, map positioning, you can't accurately judge & lsquo; he is his & rsquo;. The data of Sino Rico's credit is not only large, but also a wide range of types. It combines multiple technologies and accurately judges “he is his”.

Credit needs to be understood by the public, credit needs to be accepted by the public, and the fierce competition and growth of consumer finance is pushing the entire financial market to change, making personal credit reporting business a demand that will break out in the next decade. This is not just commercial activity. More importantly, it brings about a change in social concepts. When data becomes the basis of all credit, everything that can be digitized can be credit, data is credit, credit is money, and money is wealth. With the help of the team of Zhongke Ruike experts, taking the big data ship makes the credit information easier.

Zhongtou Ruike (Beijing) Technology Co., Ltd.

Address: K417, Kempinski Office Building, 50 Liangmaqiao Road, Chaoyang District, Beijing

Phone: 010-64683308

Fax: 010-64683358

Email: contact@sinoricogroup.com

URL: http://www.sinoricogroup.com/