Credit investigation method based on Internet behaviors

Abstract

The invention discloses a credit investigation method based on Internet behaviors. The credit investigation method comprises the following steps: 1, acquiring actor data information; 2, importing twoAHP models T1 and T2, endowing corresponding weights, and performing fuzzy evaluation to perform score interval grading; and 3, outputting the credit investigation interval level of the actor. The credit investigation method has the advantages that the influence of various indexes on the evaluated object is brought into consideration; uncertainty occurring in the evaluation process is effectivelyprocessed; a qualitative evaluation method and a quantitative evaluation method are combined; and a good scientific theoretical basis is provided. Compared with a traditional 5C model, the credit investigation model is more accurately positioned on the user network behavior, and the association between the internet surfing behavior of the network user and the personal credit investigation system is pointed out.

Description

technical field [0001] The invention relates to the field of information credit investigation, in particular to a credit investigation method based on Internet behavior. Background technique [0002] Credit investigation refers to the activities of collecting, arranging, saving and processing credit information of individuals or enterprises through specialized and independent third-party institutions, and providing them to information users. my country's credit reporting industry started relatively late, and it only began to explore in the late 1980s. So far, it has mainly formed a mixed operation pattern dominated by the credit reporting center of the People's Bank of China and supplemented by private credit reporting agencies. Among them, corporate credit investigation precedes personal credit investigation, and personal credit investigation only started in 2000. At present, it is more popular to use machine learning prediction models and integrated learning strategies fo...

AI Technical Summary

Problems solved by technology

When handling personal credit investigation business, the evaluation reference data used by credit institutions is relatively narrow, and the amount of information obtained is very small, which makes it easy for applicants to grasp the system standards adopted by the credit granting party to evaluate credit, and then a large number of speculative behavior

[0004] 2. The credit investigation results obtained by the previous credit investigation methods are not used in many occasions, so the evaluation results usually cannot change with the changes of people's behavior, which makes it possible for people to falsify information in each credit review

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