Risk assessment method and device based on user relationship and computer equipment

Abstract

The invention relates to a risk assessment method and apparatus based on a user relationship, a computer readable storage medium and a computer device. The method comprises the steps of obtaining attribute feature data corresponding to a to-be-assessed user; obtaining inter-user relationship information corresponding to the to-be-evaluated user, determining an associated user corresponding to theto-be-evaluated user according to the inter-user relationship information, and obtaining a corresponding associated risk evaluation result according to the associated user; calculating each statistical result by using the associated risk assessment result, combining each statistical result to obtain associated feature data corresponding to the to-be-assessed user, and inputting the attribute feature data and the associated feature data corresponding to the to-be-assessed user into a risk assessment model for calculation to obtain a risk assessment result corresponding to the to-be-assessed user; wherein the risk assessment model is obtained by training according to the attribute feature data, the associated feature data and the credit feature data corresponding to the training user. According to the scheme provided by the invention, the obtained risk assessment result can be more accurate.

Description

technical field [0001] The present application relates to the field of computer technology, in particular to a risk assessment method, device, storage medium and computer equipment based on user relationships. Background technique [0002] With the development of artificial intelligence technology, Internet financial companies have begun to use artificial intelligence to conduct risk assessments for users. For example, using a machine learning model to assess the risk of users, the main process is to first collect a group of users with existing financial business performance, associate more dimensional user data, input the user data into the machine learning model, and train Risk Assessment Model. When performing a risk assessment on a new user, it is necessary to obtain user data of the new user, evaluate the user data through a risk assessment model, and obtain a risk assessment result. [0003] However, the current risk assessment model usually treats users as independe...

AI Technical Summary

Problems solved by technology

Only using more dimensional data of the user itself to train the risk assessment model will cause the risk assessment model to have the problem of low risk assessment accuracy

Images