Detect Frauds in Credit Card using Data Mining Techniques
Mehak Mahajan1, Sandeep Sharma2
1Mehak Mahajan*, Dept. of Computer Engineering and Technology, Guru Nanak Dev University, Amritsar, Punjab, India
2Dr. Sandeep Sharma, Dept. of Computer Engineering and Technology, Guru Nanak Dev University, Amritsar, Punjab, India.
Manuscript received on November 14, 2019. | Revised Manuscript received on 23 November, 2019. | Manuscript published on December 10, 2019. | PP: 4891-4895 | Volume-9 Issue-2, December 2019. | Retrieval Number: A5041119119/2019©BEIESP | DOI: 10.35940/ijitee.A5041.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In today era credit card are extensively used for day to day business as well as other transactions. Ascent within the variety of transactions through master card has junction rectifier to rise in the dishonest activities. In trendy day’s fraud is one in every of the most important concern within the monetary loses not solely to the merchants however additionally to the individual purchasers. Data processing had competed a commanding role within the detection of credit card in on-line group action. Our aim is to first of all establish the categories of the fraud secondly, the techniques like K-nearest neighbor, Hidden Markov model, SVM, logistic regression, decision tree and neural network. So fraud detection systems became essential for the banks to attenuate their loses. In this paper we have research about the various detecting techniques to identify and detect the fraud through varied techniques of data mining.
Keywords: Credit Card, Types of Frauds, Data Mining Techniques
Scope of the Article: Data Mining