Abstract

There are many types of fraud in our daily life. One of the frauds occurring these days is credit card fraud. When people around the globe make credit card transactions, there will also be fraudulent transactions. To avoid credit card fraud, we must know the patterns and how the fraud values differ. This paper proposed credit card fraud detection using machine learning based on the labeled data and differentiating the fraudulent and legitimate transactions. The experiment was conducted using supervised machine-learning techniques.

Keywords:
Credit card fraud Credit card Computer science Globe Card security code Computer security ATM card Machine learning Artificial intelligence World Wide Web Payment

Metrics

14
Cited By
3.32
FWCI (Field Weighted Citation Impact)
10
Refs
0.91
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Imbalanced Data Classification Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Electricity Theft Detection Techniques
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Financial Distress and Bankruptcy Prediction
Social Sciences →  Business, Management and Accounting →  Accounting
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