System, method and device for realizing suspicious transaction scene model identification processing based on combination construction, processor and storage medium thereof

Abstract

The invention relates to a system for realizing identification processing of an anti-money laundering suspicious transaction scene model in the securities industry based on combination construction, and the system comprises: a data feature collection module, which is used for collecting various data needed by the suspicious transaction scene model for behavior identification processing; a monitoring scene construction module, which is used for constructing a monitoring scene model according to a system preset rule by using the collected data; and a suspicious transaction behavior identification module, which is used for carrying out identification processing on suspicious transaction behaviors according to the combined triggering result of the monitoring scene model. The invention further relates to a corresponding method and device, a processor and a storage medium thereof. By adopting the system, the method, the device, the processor and the storage medium of the invention, the diversity of monitoring data is broadened comprehensively, new monitoring rules are continuously added, threshold values constructed by combination are continuously optimized and corrected, anti-money laundering suspicious transaction clients are screened in a multi-view manner, and the system, the method, the device, the processor and the storage medium have important significance for the identification work of an actual anti-money laundering suspicious model.

Description

technical field [0001] The present invention relates to the technical field of financial data supervision, in particular to the technical field of suspicious transaction scene identification, and specifically refers to a system, method, device, processor and computer-based computer-based system for identifying and processing anti-money laundering suspicious transaction scene models in the securities industry. Read storage media. Background technique [0002] As the carrier of capital transactions, financial institutions are a key link and main place for money laundering. Banks are an important channel for fund transfer, and criminals often launder money through banks. Financial institutions and regulatory authorities at home and abroad are very concerned about this phenomenon. In recent years, criminals have frequently updated their means of money laundering, and have begun to use securities industry channels to launder money. [0003] As people's enthusiasm for securities...

AI Technical Summary

Problems solved by technology

In the securities industry, the traditional empirical rule model cannot better match and screen money laundering behaviors from massive data, and cannot exclude a lot of interference data

Second, it is not enough to support new money laundering methods under the new situation

[0005] However, this will lead to less analysis content, which is not comprehensive enough, and manual collection of information is likely to cause greater operational risks, excessive labor costs, and low identification efficiency

[0006] Secondly, because the monitoring behavior that conforms to a single model is hit, the number of early warnings will be too large, but not many customers report to the regulatory agency in the end, which will also lead to the low accuracy of the current system for suspicious identification of model monitoring

[0007] Finally, due to the limitation of a single model, if the rules and parameters of this model are improved, if the model is not adjusted in time, it may cause the model to fail to give early warning in the short term

Many potential money laundering customers may also be missed, and the risk is greater

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