Authors :
T. Hemanth; K. Nikhil; K. Dheeraj; Srikanthyadav. M
Volume/Issue :
Volume 7 - 2022, Issue 5 - May
Google Scholar :
https://bit.ly/3IIfn9N
Scribd :
https://bit.ly/3P1glBf
DOI :
https://doi.org/10.5281/zenodo.6944900
Abstract :
With the help of technologies like artificial
intelligence (AI), machine learning, big data, blockchain,
cloud computing, and IoT the technological revolution is
speeding (IoT). There has been a dramatic increase in the
number of cyber-attacks and criminal activities as a result
of the widespread use of ever-improving internet
technologies. Fraudulent use of credit cards is a major
concern for the banking sector across the world. Credit
card fraud is growing at an alarming rate and has become
a major concern, especially as the amount of financial
transactions utilising credit cards grows. Here, we've
looked at some credit card fraud detection methods that
can help protect against a variety of scams. The research
problems were also discussed and analysed. For the
purpose of detecting credit card fraud, we've deployed six
widely-accepted machine learning approaches. A
confusion matrix is created for each machine learning
approach so that the algorithm's performance may be
evaluated. Accuracy, precision, recall, specificity,
misclassification and F1 score are used to evaluate its
efficacy. Machine learning approaches can be useful in
detecting credit card fraud, according to the results. For
fraud detection, we propose utilising different machine
learning algorithms, even though the findings
demonstrate that each algorithm has a high degree of
precision and recall.
Keywords :
Credit Card Fraud, Fraud Detection by Machine Learning, Machine Learning Techniques
With the help of technologies like artificial
intelligence (AI), machine learning, big data, blockchain,
cloud computing, and IoT the technological revolution is
speeding (IoT). There has been a dramatic increase in the
number of cyber-attacks and criminal activities as a result
of the widespread use of ever-improving internet
technologies. Fraudulent use of credit cards is a major
concern for the banking sector across the world. Credit
card fraud is growing at an alarming rate and has become
a major concern, especially as the amount of financial
transactions utilising credit cards grows. Here, we've
looked at some credit card fraud detection methods that
can help protect against a variety of scams. The research
problems were also discussed and analysed. For the
purpose of detecting credit card fraud, we've deployed six
widely-accepted machine learning approaches. A
confusion matrix is created for each machine learning
approach so that the algorithm's performance may be
evaluated. Accuracy, precision, recall, specificity,
misclassification and F1 score are used to evaluate its
efficacy. Machine learning approaches can be useful in
detecting credit card fraud, according to the results. For
fraud detection, we propose utilising different machine
learning algorithms, even though the findings
demonstrate that each algorithm has a high degree of
precision and recall.
Keywords :
Credit Card Fraud, Fraud Detection by Machine Learning, Machine Learning Techniques
