Group fraud recognition method and device of internet finance small/micro loans

Abstract

The invention discloses a group fraud recognition method and device of internet finance small / micro loans. The method includes the following steps: acquiring feature information of loan application users; defining relationships among the users through comparison of similarity among the feature information of the users; building a relationship network of the users on the basis of the defined relationships among the users, wherein one user represents one node, and users with a relationship are connected through a line; using an unsupervised learning algorithm to find all connected branches in the relationship network; distinguishing a group as an abnormal suspicious group if the number of users in the group exceeds a set threshold value; and detecting the abnormal suspicious group to furtheranalyze entity features of the abnormal suspicious group, and carrying out further investigation thereon if it is analyzed that fraud suspicion of the abnormal suspicious group is higher. The invention aims to build the relationship network of the users on the basis of features of the users of the internet finance small / micro loans, and effectively identify a group with the fraud suspicion according to the relationship network.

Description

technical field [0001] The present invention relates to the field of computer technology, in particular to a method and device for identifying gang fraud in Internet finance small and micro loans. Background technique [0002] At present, the traditional anti-fraud methods of Internet finance small and micro loans mainly include: 1. Risk control rules: by establishing a rule engine to describe the characteristics of fraudulent behavior, so as to distinguish fraudulent behavior from normal operations; 2. Anti-fraud machine Learning model: It uses data mining methods to build a classification model based on historical data (that is, known fraudulent applications and normal application data) using supervised learning algorithms. [0003] Existing technical means are to discover the repeated individual behavior patterns when financial frauds are discovered from historical cases, but the patterns of financial frauds evolve and develop over time, not only the individual behavior p...

AI Technical Summary

Problems solved by technology

[0003] Existing technical means are to discover the repeated individual behavior patterns when financial frauds are discovered from historical cases, but the patterns of financial frauds evolve and develop over time, not only the individual behavior patterns that repeatedly appear in historical cases, but also the current More and more financial frauds are organized through gangs, and the fraudulent characteristics of individuals in gangs are sometimes not significant, which leads to unsatisfactory results in identifying users based on individual characteristics in some cases

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