Multi Model Approach for Money Laundering Identification Using Fund Transition Matrix

Suspicious money transfer has been increased due to the reason that the terrorist organizations and other communities funding peoples to perform many illegal threatening activities. The growing illegal funding shakes the financial stability of any country and has to be monitored in such a way to stop illegal flow of money. The money laundering is such activity where the origin of money has not be found and considered as threatening fund. There are many approaches has been discussed earlier but struggles with origin identification. To solve the problem of money laundering identification, we propose a multi model approach using fund transition matrix. Each transaction is considered as a state of state transition diagram and the transaction can have any number of states. The transaction will be considered as a complete one where the origin of money is identified. We compute a transaction completeness measure based on incoming and outgoing fund of any account and generate number of states from each state of the transition graph. From identified states and transactional completeness measure, we identify and declare set of suspicious accounts which has illegal money transfer. The proposed approach has produced efficient results and the accuracy of money laundering identification is improved.