Identifying Money Laundering Groups in Multi Mode Network Using Data Mining

The growth of internet technology opens the gate for money laundering where the internet user can easily transfer enormous amount to any suspicious account in the world. The user need no confirmation or approval from the destination account holder and can transfer the amounts instantly which can travel through set of account and become untraceable at the end. There exist many approaches but suffers with the accuracy of money laundering identification. We propose a new technique which identifies the group of accounts which involved in money laundering and identify the source account also. The proposed method uses multi mode network, where each account is considered as a node and the attributes, beneficiary becomes the mode of network. We cluster the accounts with more similar properties and links to form a group, from which we identify the set of accounts involved in money laundering. Earlier the money laundering approaches involved in identifying only the source or destination account but the proposed method identifies the money laundering groups. Key Terms: Multi mode networks, Money Laundering, Clustering, Data Mining.