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An anti-fraud and credit risk prediction method based on complex social network

A risk prediction and network technology, applied in prediction, data processing applications, instruments, etc., can solve the problems of inaccurate prediction and insufficient relationship mining, and achieve the effect of improving the accuracy.

Active Publication Date: 2020-01-21
SICHUAN XW BANK CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is: for the above-mentioned simple social network, each individual is divided into a single group, the relationship between people is not extensive and complete, and the prediction made according to the simple social network is not accurate enough. Problem, the present invention proposes a kind of anti-fraud and credit risk prediction method based on complex social network

Method used

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  • An anti-fraud and credit risk prediction method based on complex social network
  • An anti-fraud and credit risk prediction method based on complex social network
  • An anti-fraud and credit risk prediction method based on complex social network

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Embodiment Construction

[0056] All the features disclosed in this specification, except mutually exclusive features and / or steps, can be combined in any way. Such as figure 1 as shown,

[0057] An anti-fraud and credit risk prediction method based on a complex social network, including:

[0058] Step 1. Obtain personal user information. Each personal user is regarded as an individual, and a total of N individuals are included in the social network relationship;

[0059] Step 2, integrating relational data: using graph theory, abstract each of the N individuals in step 1 as a vertex, and abstract each relationship between every two individuals among the N individuals as an edge ;

[0060] Step 3, establish a relational model: establish a relational model adjacency matrix D based on the integrated relational data ij , the vertices of the adjacency matrix are N, and the dimension of the adjacency matrix is ​​N*N;

[0061] Step 4, determine whether there is a known fraudster, if no fraudster is foun...

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Abstract

The invention discloses an anti-fraud and credit risk prediction method based on complex social networks; aiming at complex social relations between people, the method can integrate the relative relations, friend relations and colleague relations so as to build a mathematics model, thus identifying and predicting client fraud risks and credit risks according to the complex social networks; the method can improve the fraud recognition rate and credit risk prediction accuracy, and can display the complex social networks in visualization, thus helping people to deeply understand and parse complex networks.

Description

technical field [0001] The invention relates to data mining technology, in particular to an anti-fraud and credit risk prediction method based on a complex social relationship network. Background technique [0002] With the development of society, the social relationship between people is becoming more and more complex. Many people seem to have no connection, but in fact they have some social relationships, such as relatives, friends, colleagues, classmates, and business partnerships. How to integrate complex social network relationships and establish mathematical models, and how to realize the visualization method of complex social networks has become difficult. [0003] Existing social network applications are often based on social networks based on simple relationships. In the process of using such social networks, they often aim at certain characteristics of individuals in the social network, first find the similarities of some groups, and then Sex divides groups. In a...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q50/00
CPCG06Q10/04G06Q50/01
Inventor 卫浩刘嵩
Owner SICHUAN XW BANK CO LTD