Credit Card Fraud Detection Using Bayesian Belief Network

Authors

  • M. Deekshith Kumar Student, Department of Information Science and Engineering, Srinivas Institute of Technology, Valachil, India
  • Sowmya Assistant Professor, Department of Information Science and Engineering, Srinivas Institute of Technology, Valachil, India
  • Abdul Mubarak Student, Department of Information Science and Engineering, Srinivas Institute of Technology, Valachil, India
  • M. S. Dhanush Student, Department of Information Science and Engineering, Srinivas Institute of Technology, Valachil, India

Keywords:

Bayesian Networks, Credit cards, Fraud detection, Naïve Bayes Classifier

Abstract

The number of Credit card fraud cases are increased by day by day in online payment system. Therefore, it’s essential to have a fraud detection in transaction system, which is implemented with the help of decision making algorithm. In the proposed system, we have applied two ML techniques suited for reasoning under indefiniteness: Artificial Neural Network(ANN) and Bayesian Belief Network. If the transaction is a fraudulent, it determined as examine the precious transaction and compare with a new current transaction. If its feature of the previous transaction and the current transaction vary considerably then the new current transaction may be a fraudulent or genuine transaction. These two machine-learning techniques approaches for the proper reason under indefiniteness. Bayesian network is also known as belief network and it is a types of artificial intelligence program that uses a variety of methods, and used for pattern identification and classification of data.

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Published

27-07-2020

How to Cite

[1]
M. D. . Kumar, Sowmya, A. . Mubarak, and M. S. . Dhanush, “Credit Card Fraud Detection Using Bayesian Belief Network”, IJRESM, vol. 3, no. 7, pp. 316–319, Jul. 2020.

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Section

Articles