(1) The data sources are diversified. With the advent of the era of big data, Internet credit data is no longer limited to bank credit data. On the one hand, the core business of Internet companies provides rich Internet credit data, such as Sesame Credit relies on Ali e-commerce transaction data and customer evaluation credit data, and Tencent Credit relies on social network data of social platform QQ users and WeChat users. These data contain social, political, commercial, cultural, health and other information, which can be used as weak variables in the credit evaluation model to analyze the essential behavior of customers and predict their future trends. On the other hand, P2P enterprises build their own credit database. With the development of P2P, more and more credit data are collected by P2P enterprises. For example, companies such as auction loans, renren loans and trust wealth have established their own credit information systems.
(2) Wide coverage. At present, China's credit information system covers about 800 million people, but only about 37% of them have credit records, and the other 500 million people have no bank credit records. For the financial sector, these 500 million people are potential customers of banks and a favorable opportunity to expand their business. How to understand the credit situation of these 500 million people has become a challenge for all financial institutions. However, with the development of the Internet, more and more individuals and enterprises leave a lot of information on the Internet, which broadens the scope and sources of credit data. The application of big data and cloud computing facilitates the collection of credit data. Using the collected data to judge the credit of people without credit records can meet the needs of financial institutions for pre-loan review of borrowers' repayment willingness and repayment ability.
(3) Concealed data collection. Compared with traditional credit reporting, Internet credit reporting enterprises in the era of big data have their own rules for data collection, collation, processing, analysis and use. First, Internet companies usually use cloud computing and background encryption technology to process the collected data. Due to technical reasons and information asymmetry, the information subject is not clear about his own network information collection scope. Second, at present, many Internet companies stipulate in their privacy policies that they have the right to communicate and cooperate with other platforms that abide by the same privacy policy, so users often ignore this information.
(4) Rich application fields. First, the content of credit data is more comprehensive. For example, Sesame Credit provides an important basis for financial institutions to evaluate the credit of loan subjects and decide whether to issue credit by collecting information such as customers' credit records, behavior preferences, performance ability, identity and personal relationships. Second, the application of credit evaluation results tends to be more life-oriented and daily. In addition to lending, the application field has been extended to a wider range of uses such as accommodation and travel. The third is to provide an effective basis for regulatory decisions. After mastering these big data, the regulatory authorities can timely understand the credit changes of economic entities, make more sensitive choices, monitor the flow of funds and check the implementation of policies, and realize the accuracy of regulatory policies.