A Probabilistic Model Using Graph Based Sequential Pattern Mining Algorithm For Money Laundering Identification

摘要: Money laundering an activity, which hides the source and origin of money in any banking or financial account a country.  The countries stability growth depends on overall amount banks finance organizations. holds country leads to changes value international market. In past decades criminals started hiding income from where transferred account, is illegal towards rule country. This causes threat country, because those amounts can be washed at point time some other Also terrorist makes this kind transactions their clients encourage terrorism. We focus identifying behavior holder managing accounts. There has been various methodologies proposed using data mining techniques, but suffers identify money. propose graph based sequential pattern technique probability model transaction originated. generate with many numbers nodes vertices for each transactional set, we patterns transition paths. Using paths compute amount.