Abstract
Over the years banking sector has suffered severe loss due to several fraudulent schemes and techniques. Development of a rapid behavioral modeling method in banking sectors is need of the hour. In this study we present the solution for such fraudulent by availing real time anomalistic behavioral modeling in banking scenario using the associative rule learning. The presented technique is tested for its validity on the publicly available datasets for performance review.
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