BibTeX:

@article{IJIRSTV1I8043,
     title={Review on Detection of Suspicious Transaction in Anti-Money Laundering Using Data Mining Framework },
     author={Kamlesh.D.Rohit and Dharmesh.B.Patel},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={1},
     number={8},
     pages={129--133},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV1I8043.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

Data mining, “the extraction of hidden predictive information from large databases”, is a powerful new technology with great potential to help for detecting the Anti-money Laundering. To detect suspicious money laundering transaction in the real world financial is a critical task. Database is take important role to store various kinds of useful and meaningful information. Data mining technique like Decision tree is easily extract the information from large dataset. For detection of Anti Money laundering, Data mining is used extensively, because of limited scalability, adaptability and validity. The main motivation for detecting money laundering used in real time application like classification, clustering, neural network, machine learning, prediction etc.In this review paper we study on various Data mining techniques and Anti Money laundering detection methods. And based on that we decide that the clustering techniques are the best techniques for detecting anti-money laundering.

Data mining, Anti Money laundering, Clustering, Suspicious Transaction.