Suspicious transaction report generation method and device, computer device and storage medium

Abstract

The invention relates to a suspicious transaction report generation method and device, a computer device and a storage medium in the field of big data. The method comprises the steps of acquiring thetransaction data, and identifying whether the transaction data are suspicious transactions or not; when the transaction data is a suspicious transaction, identifying a risk type corresponding to the suspicious transaction, wherein the risk type corresponds to a plurality of risk characteristics; calculating a vector matrix corresponding to the plurality of risk characteristics; and inputting the plurality of vector matrixes into a neural network model, and outputting a suspicious transaction report corresponding to the risk type through the neural network model. By adopting the method, the working efficiency of finishing the suspicious transaction report can be effectively improved.

Description

technical field [0001] The present application relates to the field of computer technology, in particular to a suspicious transaction report generation method, device, computer equipment and storage medium. Background technique [0002] Money laundering is an act of legalizing illegal gains, which is an economic crime and poses a threat to the security and stability of the financial system. Therefore, financial institutions are required to actively carry out anti-money laundering work. Financial institutions monitor transactions related to money laundering, and report any suspicious transactions in a timely manner. When reporting, financial institutions need to describe suspicious transactions in the form of reports. In the traditional way, suspicious transaction reporting is done manually. If a large number of suspicious transactions are faced with manual preparation of corresponding reports, it will lead to low work efficiency. Contents of the invention [0003] Base...

AI Technical Summary

Problems solved by technology

If faced with a large number of suspicious transactions, the corresponding reports are written manually, which will lead to low work efficiency

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