Review on Credit Card Fraud Detection using Machine Learning Algorithms
|© 2020 by IJCTT Journal|
|Year of Publication : 2020|
|Authors : Pooja, Dr. Ashlesha|
|DOI : 10.14445/22312803/IJCTT-V68I6P113|
How to Cite?
Pooja, Dr. Ashlesha, "Review on Credit Card Fraud Detection using Machine Learning Algorithms," International Journal of Computer Trends and Technology, vol. 68, no. 6, pp. 77-81, 2020. Crossref, https://doi.org/10.14445/22312803/IJCTT-V68I6P113
The advancement of new technologies and the fast growing of technological development have generated new possibilities as well as imposing new challenges. Fraud, the biggest challenges for business and organization, emerge with new technologies to take new and distinctive forms that are hidden and tougher to identify than the conventional forms of this crime. Credit card frauds also grow up along with growing in technology. It also noticed that financial fraud is extremely growing in the global communication improvement. It is being admitted every year that the loss because of this types of fraudulent activities is billions of dollars. These activities are performed so gracefully that it look similar to original transactions. Simply using of pattern matching technique and simple method really not useful for detecting these fraudulent activities. A well planned and systematic method has became need for all business and organization to minimizing chaos and carry out in place. Several technique has been evolved based on Artificial intelligence, Machine learning, Data mining, Genetic programming Fuzzy logic etc.. for detecting credit card fraudulent activities. Besides this technique, K-Nearest Neighbour algorithm and outlier detection methods are implemented to optimize the best solution for the fraud detection problem. These techniques proved to minimize the false alarm rates and increase the fraud detection rate.
Credit Card, Fraud Detection, Machine Learning, Logistic Regression, K-Nearest Neighbour..
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