Account classification method and device involving non-legal legalization behavior, computer equipment and storage medium

Abstract

The embodiment of the invention discloses an account classification method and device related to non-legal legalization behaviors, computer equipment and a storage medium. The method comprises the steps of identifying historical transaction details of a plurality of transaction accounts according to a preset rule to determine corresponding money laundering suspicion gangs; determining transactioncharacteristics of each transaction account in the money laundering suspicion gangs, wherein the transaction characteristics at least comprise a transaction total amount and a transaction frequency; and performing clustering division on the money laundering suspicion gangs according to the determined transaction characteristics and a condensation hierarchical clustering algorithm to obtain a preset number of category sets, each category set comprising a plurality of transaction accounts. The money laundering accounts can be accurately and automatically classified through data analysis, the working efficiency of account classification is improved, and repeated work is reduced.

Description

technical field [0001] The invention relates to the field of data processing, in particular to an account classification method, device, computer equipment and storage medium related to legalization of illegal gains. Background technique [0002] Usually, people refer to the legalization of illegal gains as money laundering, and consider the accounts involved in the legalization of illegal gains as money laundering accounts. Money laundering not only seriously endangers the security of the national financial system and the stability of the social and economic order, but also provides financing for terrorism, endangering the safety of people's lives and properties. At present, the division and identification of anti-money laundering accounts mainly rely on the professional knowledge and processing experience of analysts, and manually construct the transaction characteristics of suspects one by one for analysis. This kind of analysis is very labor-intensive and time-consuming...

AI Technical Summary

Problems solved by technology

This kind of analysis is very labor-intensive and time-consuming. It is not only inefficient, but also ignores some important features; it lacks indicators that can specifically quantify the similarity of suspects’ transaction behaviors, resulting in a lack of precision in the analysis; In the process, it cannot be automated, which will generate a lot of inefficient and repetitive work

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