Deceit Exposure of Monetary Withdrawal Transactions using Data Mining


Authors : Dr. Firoz Kayum Kajrekar, Dr. Chandrashekar Sonawane

Volume/Issue : Volume 3 - 2018, Issue 1 - January

Google Scholar : https://goo.gl/DF9R4u

Scribd : https://goo.gl/GUbPA9

Thomson Reuters ResearcherID : https://goo.gl/3bkzwv

Paper states a strategy for detecting doubtful transaction done using financial cards. Data Mining methods have been implemented to detect such doubtful transactions; existing methods produce incorrect results by categorizing the valid transaction as doubtful in some cases and creating misunderstanding and concern in customers faith. This effort is proposed to develop a fusion model using an existing technique Density-Based Spatial Clustering of Applications with Noise (DBSCAN) combined with a rule base algorithm to reinforce the accuracy of the existing technique. The DBSCAN algorithm combined with Rule base algorithm contribute a improved card fraud detection method with more precision over the existing DBSCAN algorithm when used alone.

Keywords : Data Mining, Card Fraud, Data Mining, DBSCAN.

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