A Study on Credit Card Fraud Detection using Machine Learning
A. N. International Journal of Trend in Scientific Research and Development, 4 (3):
801-804(April 2020)
Abstract
Due to the high level of growth in each number of transactions done using credit card has led to high rise in fraudulent activities. Fraud is one of the major issues related to credit card business, since each individual do more of offline or online purchase of product via internet there is need to developed a secured approach of detecting if the credit card been used is a fraudulent transaction or not. Pattern involves in the fraud detection has to be re analyze to change from reactive approach to a proactive approach. In this paper, our objectives are to detect at least 95 of fraudulent activities using machine learning to deployed anomaly detection system such as logistic regression, k nearest neighbor and support vector machine algorithm. Ajayi Kemi Patience | Dr. Lakshmi J. V. N Ä Study on Credit Card Fraud Detection using Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30688.pdf
%0 Journal Article
%1 noauthororeditor
%A N, Ajayi Kemi Patience | Dr. Lakshmi J. V.
%D 2020
%J International Journal of Trend in Scientific Research and Development
%K Algorithm Card Credit-Movement. Detection Fraud K-Nearest Learning Logistic Machine Neighbor Regression Support Vector
%N 3
%P 801-804
%T A Study on Credit Card Fraud Detection using Machine Learning
%U https://www.ijtsrd.com/computer-science/other/30688/a-study-on-credit-card-fraud-detection-using-machine-learning/ajayi-kemi-patience
%V 4
%X Due to the high level of growth in each number of transactions done using credit card has led to high rise in fraudulent activities. Fraud is one of the major issues related to credit card business, since each individual do more of offline or online purchase of product via internet there is need to developed a secured approach of detecting if the credit card been used is a fraudulent transaction or not. Pattern involves in the fraud detection has to be re analyze to change from reactive approach to a proactive approach. In this paper, our objectives are to detect at least 95 of fraudulent activities using machine learning to deployed anomaly detection system such as logistic regression, k nearest neighbor and support vector machine algorithm. Ajayi Kemi Patience | Dr. Lakshmi J. V. N Ä Study on Credit Card Fraud Detection using Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30688.pdf
@article{noauthororeditor,
abstract = {Due to the high level of growth in each number of transactions done using credit card has led to high rise in fraudulent activities. Fraud is one of the major issues related to credit card business, since each individual do more of offline or online purchase of product via internet there is need to developed a secured approach of detecting if the credit card been used is a fraudulent transaction or not. Pattern involves in the fraud detection has to be re analyze to change from reactive approach to a proactive approach. In this paper, our objectives are to detect at least 95 of fraudulent activities using machine learning to deployed anomaly detection system such as logistic regression, k nearest neighbor and support vector machine algorithm. Ajayi Kemi Patience | Dr. Lakshmi J. V. N "A Study on Credit Card Fraud Detection using Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30688.pdf
},
added-at = {2020-06-10T08:21:44.000+0200},
author = {N, Ajayi Kemi Patience | Dr. Lakshmi J. V.},
biburl = {https://www.bibsonomy.org/bibtex/211ff227084a2b0170bd3a3d841e75698/ijtsrd},
interhash = {026a945faac0301dfa13afdcba3978ee},
intrahash = {11ff227084a2b0170bd3a3d841e75698},
issn = {2456-6470},
journal = {International Journal of Trend in Scientific Research and Development},
keywords = {Algorithm Card Credit-Movement. Detection Fraud K-Nearest Learning Logistic Machine Neighbor Regression Support Vector},
language = {English},
month = {April},
number = 3,
pages = {801-804},
timestamp = {2020-06-10T08:21:44.000+0200},
title = {A Study on Credit Card Fraud Detection using Machine Learning
},
url = {https://www.ijtsrd.com/computer-science/other/30688/a-study-on-credit-card-fraud-detection-using-machine-learning/ajayi-kemi-patience},
volume = 4,
year = 2020
}