Overdue risk warning method and device and electronic equipment

Abstract

The invention relates to an overdue risk warning method and device, electronic equipment and a computer readable medium. The method comprises the following steps: acquiring user information of a user in a predetermined state, the user information comprising basic information and behavior information; generating duration characteristic data, behavior characteristic data, frequency characteristic data and attribute characteristic data based on the user information; inputting the duration characteristic data, the behavior characteristic data, the frequency characteristic data and the attribute characteristic data into an overdue risk model, generating the overdue probability, and the overdue risk model being generated by training a machine learning model based on a focus loss function and gradually adjusting and optimizing the machine learning model; and when the overdue probability is greater than a threshold value, generating overdue risk warning information. According to the overdue risk warning method and device, the electronic equipment and the computer readable medium, the user with the preset feature can be accurately recognized, and early warning is performed when the overdue risk exists, so that an appropriate user strategy is adopted as early as possible, resource risks are prevented, resource safety is improved, and the calculation pressure of a server is reduced.

Description

technical field [0001] The present disclosure relates to the field of computer information processing, in particular, to an overdue risk warning method, device, electronic equipment and computer readable medium. Background technique [0002] Resource risk prevention refers to the behavior of resource market entities to use certain methods to prevent or avoid risks in compliance with regulations on the basis of relevant analysis in order to achieve expected goals. In the current environment, with the increase of personal and corporate resource credit demand, more and more companies providing resource services have emerged. For these resource service companies, it is a hot topic to prevent users' resource risks in advance. technology field. The main ways that Internet resource service agencies respond to resource fraud risk detection can be divided into two categories, namely, rule-based response methods and machine learning algorithm-based response methods. [0003] Among t...

AI Technical Summary

Problems solved by technology

However, since there are fewer bad samples corresponding to fraudulent users in normal sample data, it makes it more difficult for machine learning models trained with such samples to identify bad samples.

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