What are the sources and methods of data for big data credit?

The source of data for big data credit collection is the mining of information and data collection.

The difference between big data and traditional credit collectionIn essence, big data credit collection is the application of big data technology to credit collection activities, big data credit collection, in short, is the use of these massive data collection, after mining and analysis for the purpose of proving a person's or enterprise's credit status.

1, in terms of data raw materials, more and more Internet online dynamic big data is added. For example, a false borrowing applicant information can be identified by analyzing online behavioral traces, a real Internet user will always leave traces on the network. The timeliness of the data that is useful for credit is also critical, and the dynamic data that is usually recognized as valid by the credit industry is usually 24 months back from now.

2. The traditional credit reporting company adopts a peer-to-peer information sharing model, in which customers need to first *** enjoy a corresponding piece of information to query a piece of information; whereas the Internet company utilizes its own massive data advantage and user information to judge from several latitudes, such as wealth, security, compliance, consumption, and socialization, and to establish a credit report for the user, forming a massive database based on big data.

3. After the formation of the database system, the collection of credit information of a single subject will be very easy, the marginal cost of credit services is low, fast, and the direct benefit is the reduction of the cost of credit services and a large amount of services. Moreover, after the formation of the database, the operating costs of credit bureaus are more from the input of intellectual property and hardware, compared with the large-scale personnel requirements, the low-cost advantage is obvious.