scholarly journals AN INTELLIGENT CREDIT CARD FRAUD DETECTION SYSTEM

2021 ◽  
Vol 9 (2) ◽  
Author(s):  
Ekwealor Oluchukwu Uzoamaka ◽  
Anusiuba Overcomer Ifeanyi Alex ◽  
Ezuruka Evelyn Ogochukwu ◽  
Uchefuna Charles Ikenna
Keyword(s):  
Credit Card ◽  
Detection System ◽  
Fraud Detection ◽  
Credit Card Fraud

scholarly journals Credit Card Fraud Detection System

2020 ◽  
Vol 6 (12) ◽  
pp. 24-27
Author(s):  
Shashank Singh and Meenu Garg
Keyword(s):  
Machine Learning ◽  
Credit Card ◽  
Data Science ◽  
Detection System ◽  
Fraud Detection ◽  
Detection Problem ◽  
Credit Card Fraud ◽  
Local Outlier Factor ◽  
Local Outlier ◽  
Isolation Forest

It is essential that Visa organizations can distinguish false Mastercard exchanges so clients are not charged for things that they didn't buy. Such issues can be handled with Data Science and its significance, alongside Machine Learning, couldn't be more important. This undertaking expects to outline the demonstrating of an informational collection utilizing AI with Credit Card Fraud Detection. The Credit Card Fraud Detection Problem incorporates demonstrating past Visa exchanges with the information of the ones that ended up being extortion. This model is then used to perceive if another exchange is fake. Our target here is to identify 100% of the fake exchanges while limiting the off base misrepresentation arrangements. Charge card Fraud Detection is an average example of arrangement. In this cycle, we have zeroed in on examining and pre- preparing informational indexes just as the sending of numerous irregularity discovery calculations, for example, Local Outlier Factor and Isolation Forest calculation on the PCA changed Credit Card Transaction

scholarly journals A Comparative Study on Credit Card Fraud Detection

2021 ◽  
Author(s):  
KOUSHIK DEB
Keyword(s):  
Credit Card ◽  
Financial Institution ◽  
Detection System ◽  
Dimensional Space ◽  
Fraud Detection ◽  
Modern Technology ◽  
Two Dimensional ◽  
Rating Score ◽  
Credit Card Fraud ◽  
Dependent Variables

Credit Card Fraud is increasing rapidly with the development of modern technology. This fraud detection system has been proven essential for banks and financial institution, to minimize their losses. This paper pr- oposes Credit Card Fraud Detection using clustering based on several uns- upervised Machine learning and deep learning algorithms. The method we follow to solve our problem is that we are going to plot the points into two dimensional space and some points turns out to be an outliers and some p- oints forms a valid clusters. These outliers are possible number of cheaters which is nothing but the fraudulent transactions and the bank may reject t- heir credit card application. And valid clusters are not cheaters therefore we are going to allocate them the credit card. So as a result we get the explicit list of customers i.e. the potential cheaters who have cheated. Thus, the clu- stering approach which will give better rating score can be chosen to be one of the best methods to detect fraud. In this paper, we worked with Statlog Australian Credit Card Approval Dataset in which the dependent variables have been removed to maintain the privacy of the customers.

Credit Card Fraud Detection System

2016 ◽  
Author(s):  
Suchita Anant Padvekar ◽  
◽  
Pragati Madan Kangane ◽  
Komal Vikas Jadhav
Keyword(s):  
Credit Card ◽  
Detection System ◽  
Fraud Detection ◽  
Credit Card Fraud
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