6. Conclusion
In the AML field, especially detection system of suspicious transaction report (STR), we recognized that the data-mining theory such as multivariate date analysis (liner regression, logistic regression, luster analysis) and artificial intelligence technique (inductive algorithms, neural networks, fuzzy logic and Generic algorithms) is in practice and well developed. However, the information and knowledge gained are not necessarily used for or shared with the related shareholders, because data mining is considered one of the most important frontiers in database systems and one of the most promising interdisciplinary developments in the information industry26, we cannot help taking advantage of this concept. A lot of AML professionals realize the importance of cooperation at the national / international and private /public sector levels. Peter Reuter (2004) insists that the global AML regime clearly needs further development and promulgation of anti-money laundering strategies at the international as well as national levels. Cooperation with the private sector also should be enhanced, more technical and financial assistance should be provided, and more technical and financial assistance should be made available to poor jurisdictions.
But, is it sufficient to take preventive measures against money laundering? My answer is no. In addition to establishing such a regime, creating and co-evolving the network of ‘knowledge professionals’ is the impending assignment in this industry. The first and most important task is knowledge management in the global Anti-Money Laundering Field.