Bimonthly    Since 1986
ISSN 1004-9037
Publication Details
Edited by: Editorial Board of Journal of Data Acquisition and Processing
P.O. Box 2704, Beijing 100190, P.R. China
Sponsored by: Institute of Computing Technology, CAS & China Computer Federation
Undertaken by: Institute of Computing Technology, CAS
Published by: SCIENCE PRESS, BEIJING, CHINA
Distributed by:
China: All Local Post Offices
 
   
      07 April 2023, Volume 38 Issue 2   
    Article

    CREDIT CARD FRAUD DETECTION SYSTEM
    Raghav Sukhwal1, Shivam Sharma2, Dhruv Kumar3, Mr Amit Kumar4.
    Journal of Data Acquisition and Processing, 2023, 38 (2): 3759-3767 . 

    Abstract

    For clients to avoid being charged for items they did not buy, credit card companies must be able to identify fraudulent credit card transactions. To overcome such challenges, Data Science and Machine Learning might be applied. This study uses Credit Card Fraud Detection to show how machine learning can be used to model a data collection. The Credit Card Fraud Detection Issue includes modelling previous credit card transactions using information from transactions that turned out to be fraudulent. The model is then applied to assess the likelihood of fraud in a new transaction. Our objective is to eliminate erroneous fraud classifications while detecting all fraudulent transactions. Credit card fraud detection is an excellent illustration of classification. During this process, we focused on analysing and pre-processing large data sets as well as implementing multiple anomaly detection methods.

    Keyword

    #


    PDF Download (click here)

SCImago Journal & Country Rank

ISSN 1004-9037

         

Home
Editorial Board
Author Guidelines
Subscription
Journal of Data Acquisition and Processing
Institute of Computing Technology, Chinese Academy of Sciences
P.O. Box 2704, Beijing 100190 P.R. China
E-mail: info@sjcjycl.cn
 
  Copyright ©2015 JCST, All Rights Reserved