Credit card fraud detection using machine learning: a study
P Tiwari, S Mehta, N Sakhuja, J Kumar… - arXiv preprint arXiv …, 2021 - arxiv.org
As the world is rapidly moving towards digitization and money transactions are becoming
cashless, the use of credit cards has rapidly increased. The fraud activities associated with it …
cashless, the use of credit cards has rapidly increased. The fraud activities associated with it …
Enhanced credit card fraud detection based on SVM-recursive feature elimination and hyper-parameters optimization
N Rtayli, N Enneya - Journal of Information Security and Applications, 2020 - Elsevier
With the growth of online shopping, Credit Card Fraud (CCF) comes out as a serious
menace. For this end, the automatic and real-time fraud detection field calls for several …
menace. For this end, the automatic and real-time fraud detection field calls for several …
Fraud detection in mobile payment systems using an XGBoost-based framework
P Hajek, MZ Abedin, U Sivarajah - Information Systems Frontiers, 2023 - Springer
Mobile payment systems are becoming more popular due to the increase in the number of
smartphones, which, in turn, attracts the interest of fraudsters. Extant research has therefore …
smartphones, which, in turn, attracts the interest of fraudsters. Extant research has therefore …
Computational approaches and data analytics in financial services: A literature review
D Andriosopoulos, M Doumpos… - Journal of the …, 2019 - Taylor & Francis
The level of modeling sophistication in financial services has increased considerably over
the years. Nowadays, the complexity of financial problems and the vast amount of data …
the years. Nowadays, the complexity of financial problems and the vast amount of data …
Meta-learning approaches for learning-to-learn in deep learning: A survey
Y Tian, X Zhao, W Huang - Neurocomputing, 2022 - Elsevier
Compared to traditional machine learning, deep learning can learn deeper abstract data
representation and understand scattered data properties. It has gained considerable …
representation and understand scattered data properties. It has gained considerable …
Auto loan fraud detection using dominance-based rough set approach versus machine learning methods
Financial fraud is escalating as financial services and operations grow. Despite preventive
actions and security measures deployed to mitigate financial fraud, fraudsters are learning …
actions and security measures deployed to mitigate financial fraud, fraudsters are learning …
[HTML][HTML] Machine learning algorithms for fraud prediction in property insurance: Empirical evidence using real-world microdata
MK Severino, Y Peng - Machine Learning with Applications, 2021 - Elsevier
This paper evaluated fraud prediction in property insurance claims using various machine
learning models based on real-world data from a major Brazilian insurance company. The …
learning models based on real-world data from a major Brazilian insurance company. The …
Champion-challenger analysis for credit card fraud detection: Hybrid ensemble and deep learning
Credit card fraud detection is an essential part of screening fraudulent transactions in
advance of their authorization by card issuers. Although credit card frauds occur extremely …
advance of their authorization by card issuers. Although credit card frauds occur extremely …
ESG score prediction through random forest algorithm
V D'Amato, R D'Ecclesia, S Levantesi - Computational Management …, 2022 - Springer
Environment-related risks affect assets in various sectors of the global economy, as well as
social and governance aspects, giving birth to what is known as ESG investments …
social and governance aspects, giving birth to what is known as ESG investments …
Deep representation learning with full center loss for credit card fraud detection
Z Li, G Liu, C Jiang - IEEE Transactions on Computational …, 2020 - ieeexplore.ieee.org
Credit card fraud detection is an important study in the current era of mobile payment.
Improving the performance of a fraud detection model and keeping its stability are very …
Improving the performance of a fraud detection model and keeping its stability are very …