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@article{144430,
        author = {SHWETA},
        title = {Fraud detection method: A review},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {3},
        number = {11},
        pages = {187-190},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=144430},
        abstract = {With the rising demand of credit card transactions in recent years, credit card fraud has increasing excessively. With the development of modern technology, financial fraud is increasing significantly which results in the loss of billions of dollars worldwide. In order to detect fraud, several modern techniques are involved continuously for monitoring the suspected and undesirable behavior of users. This paper presents a review of current techniques used in credit card fraud detection. Many techniques are based on artificial intelligence, Data mining, neural network, K-nearest neighbor algorithm, artificial immune system, machine learning etc. The goal of this paper is to a comprehensive review of different techniques to detect frauds.},
        keywords = {credit card, Fraud detection, data mining, knowledge discovery},
        month = {},
        }