A credit evaluation method and system

Abstract

The invention discloses a credit evaluation method and system, which includes obtaining the initial confidence value of each user according to the user's personalized credit control information; analyzing the user's detailed list data to obtain the user's social circle information; using the obtained social circle The circle information calculates the confidence value correction factor, and corrects the initial confidence value to obtain the user's credit value. Through the method of the present invention, the credit parameters of the user's social circle are introduced into the user's credit evaluation system, and the big data platform is used to mine and calculate the information of the social circle, and the confidence correction factor of the social circle in which the user is located is introduced on the basis of the user's own initial confidence value , which realizes the objective evaluation of the user's credit, which is beneficial to the operator to comprehensively evaluate the user's credit reliability from multiple dimensions, thereby improving the user experience, reducing the operator's business risk, that is, reducing the probability of events such as arrears.

Description

technical field [0001] The invention relates to post-pay service technology, in particular to a credit evaluation method and system for post-pay users. Background technique [0002] At present, the post-paid service has become an increasingly familiar service for mobile phone users and network users. The post-paid service is the method that users use first and then pay. On the one hand, it facilitates the use of services by users and expands the payment channels of operators. On the one hand, it also reduces the real-time demand for IT operation and maintenance systems, thereby reducing billing costs. However, at the same time, postpaid services also introduce risks. For example, the phenomenon of user arrears and unpaid parking still exists, which affects the revenue of operators to a certain extent. [0003] In order to solve the problem of arrears, my country's mobile communication companies have also begun to gradually establish user credit management. At present, the a...

AI Technical Summary

Problems solved by technology

Once the user exceeds the arrears amount or the arrears time threshold, it will enter the blacklist, so that it will be partially or completely restricted in business use and handling

[0004] The blacklist system can effectively control the occurrence of malicious arrears of some users, but at the same time, it also makes another part of friendly users, especially those who are new to the network, because there is no historical record, and the initial credit value of the network is low. Due to non-subjective and accidental factors such as conditional restrictions, they will be blacklisted, which will inevitably bring inconvenience to business use and affect the brand loyalty of operators.

Therefore, the existing evaluation of user credit is not accurate enough

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