Ontology-based anti-money laundering early-warning method

Abstract

The invention relates to an ontology-based anti-money laundering early-warning method, comprising the following steps: (1) building an anti-money laundering ontology composed of a client information ontology, a financial institution information ontology and a transaction information ontology, and linking the client information ontology, the financial institution information ontology and the transaction information ontology into the anti-money laundering ontology by constraint conditions; (2) building databases including a transaction flow database, a CBR case database, a law and regulation rule database and an auxiliary database; and (3) retrieving the ontology, discriminating the large-sum transactions and the suspicious transactions through operation, classifying the levels of risk by CBR and generating the report files. The method has the beneficial effect of providing convenience for anti-money laundering work, thus not only increasing the correct rate of anti-money laundering work but also greatly improving the working efficiency of the financial institutions.

Description

technical field [0001] The invention relates to ontology and CBR case reasoning technology, mainly an anti-money laundering early warning method based on ontology. Background technique [0002] How to effectively prevent and combat money laundering activities has become a hot issue in the current society. At present, my country's anti-money laundering means are mainly the identification of customer identities and the reporting of large-value transactions and suspicious transactions. Many difficulties will be faced in the actual anti-money laundering operation process. At present, the main problems are: the suspicious description of the suspicious transaction reporting system is not clear enough, how to establish a specific anti-money laundering work process under the framework of the anti-money laundering law, suspicious judgment standards and How to refine the anti-money laundering work; and although most financial institutions currently have automatic extraction software ...

AI Technical Summary

Problems solved by technology

Many difficulties will be faced in the actual anti-money laundering operation process. At present, the main problems are: the suspicious description of the suspicious transaction reporting system is not clear enough, how to establish a specific anti-money laundering work process under the framework of the anti-money laundering law, suspicious judgment standards and How to refine the anti-money laundering work; and although most financial institutions currently have automatic extraction software for large-value transactions, it is filtered through mechanical conditions and is easily used by criminals; suspicious transactions are still in the counter business The level of manual identification of employees will not only cause errors due to human factors, but more seriously affect the work efficiency of financial institutions

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