Credit Card Fraud Detection Using State-of-the-Art Machine Learning and Deep Learning Algorithms
Imam Mohammad ibn Saud Islamic University · Information Technology University · +2 more institutions
Abstract
People can use credit cards for online transactions as it provides an efficient and easy-to-use facility. With the increase in usage of credit cards, the capacity of credit card misuse has also enhanced. Credit card frauds cause significant financial losses for both credit card holders and financial companies. In this research study, the main aim is to detect such frauds, including the accessibility of public data, high-class imbalance data, the changes in fraud nature, and high rates of false alarm. The relevant literature presents many machines learning based approaches for credit card detection, such as Extreme Learning Method, Decision Tree, Random Forest, Support Vector Machine, Logistic Regression and XG…
Citation impact
- FWCI
- 46.75
- Percentile
- 100%
- References
- 48
Authors
6- FKFawaz Khaled AlarfajCorresponding
Imam Mohammad ibn Saud Islamic University
- IMIqra Malik
Information Technology University, University of Sargodha
- HUHikmat Ullah Khan
COMSATS University Islamabad
- NANaif Almusallam
Imam Mohammad ibn Saud Islamic University
- MRMuhammad Ramzan
Information Technology University, University of Sargodha
Topics & keywords
- Computer science
- Machine learning
- Credit card
- Artificial intelligence
- Credit card fraud
- Benchmark (surveying)
- Decision tree
- Random forest
- Peace, Justice and strong institutions