Deceit Exposure of Monetary Withdrawal Transactions using Data Mining

Dr. Firoz Kayum Kajrekar, Dr. Chandrashekar Sonawane1

1

Publication Date: 2019/01/27

Abstract: 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.

DOI: No DOI Available

PDF: https://ijirst.demo4.arinfotech.co/http://ijisrt.com/wp-content/uploads/2018/01/1Deceit-Exposure-of-Monetary-Withdrawal-Transactions-using-Data-Mining.pdf

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