Comparative Analysis of algorithms for Credit Card Fraud Detection using Data Mining: A Review

Authors

  • Neha .
  • Sunita Dhingra

DOI:

https://doi.org/10.37591/joadms.v6i2.2096

Abstract

Abstract

Data mining is a technique to extract new useful information from existing dataset. It is used to predict various patterns from present dataset. It has a great application in the field of bank and finance. In today’s world, everything is being online, means online shopping, online banking and online payment. The problem faced by them is credit card fraud. In this, we use the data mining techniques such as classification, clustering, association, and prediction and decision tree for detecting the credit card fraud. The algorithms are used to compare the results to find the optimal algorithm for detection of credit card fraud.

Keywords: Data mining, data mining techniques, WEKA tool, credit card fraud detection

Cite this Article

Neha, Sunita Dhingra. Comparative Analysis of Algorithms for Credit Card Fraud Detection using Data Mining: A Review. Journal of Advanced Database Management & Systems. 2019; 6(2):
12–17p.


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Published

2019-06-10

Issue

Vol. 6 No. 2 (2019)

Section

Review Articles

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