Suspicious money laundering user transaction relation determination method and device

Abstract

The invention provides a suspicious money laundering user transaction relation determination method and device, and the method comprises the steps: constructing a suspicious money laundering user transaction network according to a total customer transaction relation network and a suspicious money laundering user set, and enabling network nodes in the suspicious money laundering user transaction network to be suspicious money laundering users; calculating transaction weights among the suspicious money laundering users in the suspicious money laundering user transaction network, and marking the suspicious money laundering user transaction network according to the transaction weights to obtain a suspicious money laundering user transaction relation network; and deleting the transaction relationship among the suspicious money laundering users of which the transaction weights are lower than a predetermined threshold in the suspicious money laundering user transaction relationship network to obtain a plurality of suspicious money laundering user transaction relationship groups, thereby determining the transaction relationship among the suspicious money laundering users. The problems that the group scale obtained by a money laundering gang mining mode in the related technology is too large and the money laundering transaction path is easily damaged are solved.

Description

technical field [0001] The embodiments of the present invention relate to the communication field, and in particular, relate to a method and device for determining a transaction relationship of a suspected money laundering user. Background technique [0002] In anti-money laundering upstream crime scenarios, most of the scenarios such as underground banks, gambling, and illegal fund-raising are crimes committed by gangs. Therefore, how to associate customers and accurately classify gangs is very important, and it is also necessary for further gang mining and manual verification. key steps. The transaction network between customers in the anti-money laundering scenario has two characteristics: [0003] 1. The transactions between customers are intricate, the transaction volume is relatively large, and normal transactions are far more than money laundering transactions; [0004] 2. The most essential feature of money laundering is to convert illegal gains into legal income o...

AI Technical Summary

Problems solved by technology

[0008] The embodiment of the present invention provides a method and device for determining the transaction relationship of suspicious money laundering users, so as to at least solve the problems in the related art that the group size obtained by the money laundering gang mining method is too large and the money laundering transaction path is easily destroyed

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