High-risk user dynamic identification method and device in financial field

Abstract

The invention can be applied to the financial field or other fields, and provides a high-risk user dynamic identification method and device in the financial field, and the method comprises the steps of generating a feature set of a user according to the grading of debt items of the user; classifying the users according to the feature set by using a clustering algorithm to generate a classification result; and dynamically identifying the high-risk user according to the classification result. Dynamic identification of high-risk large households under different time points and different overall risk degrees is realized, and the current situation of low efficiency and low precision of current offline manual evaluation of high-risk large households can be changed.

Description

Technical field [0001] The present invention belongs to the field of large data technology, and more particularly to distributed system service calls, specific to high-risk user dynamic identification methods and apparatus for financial areas. Background technique [0002] In the current financial field, the regulatory agencies and interior systems require specific matters to high-risk larger, which can be understood that high-risk owners are relatively conceptual concepts, referring to all major industries in the line, relatively high risk Big household. That is, the overall risk of point different points is different, and it is necessary to find a relatively high large number of risks in different overall risk. [0003] What standards are made to make large-scale risk assessments for dynamic changes (ie, difficult to point 1: How to quantify the risk of large-scale households), and how to accurately detect from nearly 10,000 largest households according to the overall risk of t...

AI Technical Summary

Problems solved by technology

This method is hardly satisfactory in terms of efficiency or accuracy.

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