The use of data mining of to create of a fraud prevention and detection system in credit card

K. Sivakumar; G. Manoharan; A. S. Prakaash

doi:10.53730/ijhs.v6nS5.10371

Authors

K. Sivakumar Department of Mathematics, Saveetha School of Engineering,Saveetha Institute of Medical and Technical Sciences(SIMATS), Saveetha University, Chennai 602105, India
G. Manoharan Research Scholar, Department of Mathematics, Sathyabama Institute of Science and Technology, Chennai-600119, Tamilnadu, India
A. S. Prakaash Department of Mathematics, Panimalar Institute of Technology, Chennai- 600 123

Keywords:

Data Mining, Fraud, Prevention, System, Detection and Methodologies

Abstract

After defining the problem, we'll examine the various techniques (pre-and post-dynamic) for managing installment card fraud recognition, as well as collect all the data from various elements of card-based monetary fraud (regions, fraudulent activity, etc.). When all of the information has been gathered, it's time to put it into practice. It is best to avoid using data that has been gleaned from several sources because it has little practical use until it can be combined. For this collaboration, we're looking into novel data-combination approaches that can help us find the location of financial fraud. The Fraud Prevention and Detection systems were developed utilizing a variety of data mining techniques, including rule learning, rule generation, and rule selection.

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