[HTML][HTML] Credit card fraud detection in the era of disruptive technologies: A systematic review
Credit card fraud is becoming a serious and growing problem as a result of the emergence
of innovative technologies and communication methods, such as contactless payment. In …
of innovative technologies and communication methods, such as contactless payment. In …
[PDF][PDF] Comparative Review of Credit Card Fraud Detection using Machine Learning and Concept Drift Techniques
OS Adebayo, TA Favour-Bethy, O Otasowie… - Int. J. Comput. Sci …, 2023 - academia.edu
Credit card fraud is a significant concern for financial institutions and cardholders alike. As
fraudulent activities become more sophisticated, traditional rule-based approaches struggle …
fraudulent activities become more sophisticated, traditional rule-based approaches struggle …
Intuitionistic fuzzy time series forecasting method for non-stationary time series data with suitable number of clusters and different window size for fuzzy rule generation
The strict non-stationary time series (NS-TS) forecasting is one of the challenging tasks as
the series does not follow any defined pattern. Previous studies had mainly focused on …
the series does not follow any defined pattern. Previous studies had mainly focused on …
Evaluation of deep neural networks for reduction of credit card fraud alerts
RSM Carrasco, MA Sicilia-Urban - IEEE Access, 2020 - ieeexplore.ieee.org
Fraud detection systems support advanced detection techniques based on complex rules,
statistical modelling and machine learning. However, alerts triggered by these systems still …
statistical modelling and machine learning. However, alerts triggered by these systems still …
A unified framework for dataset shift diagnostics
Supervised learning techniques typically assume training data originates from the target
population. Yet, in reality, dataset shift frequently arises, which, if not adequately taken into …
population. Yet, in reality, dataset shift frequently arises, which, if not adequately taken into …
[HTML][HTML] NAG: neural feature aggregation framework for credit card fraud detection
K Ghosh Dastidar, J Jurgovsky, W Siblini… - … and Information Systems, 2022 - Springer
The state-of-the-art feature-engineering method for fraud classification of electronic
payments uses manually engineered feature aggregates, ie, descriptive statistics of the …
payments uses manually engineered feature aggregates, ie, descriptive statistics of the …
Out-of-time cross-validation strategies for classification in the presence of dataset shift
S Maldonado, J López, A Iturriaga - Applied Intelligence, 2022 - Springer
Abstract Model selection is a highly important step in the process of extracting knowledge
from datasets. This is usually done via partitioning strategies such as cross-validation in …
from datasets. This is usually done via partitioning strategies such as cross-validation in …
Detection of credit card fraud using isolation forest algorithm
H Rajeev, U Devi - … Computing and Social Networking: Proceedings of …, 2022 - Springer
Credit card payment is increasing day by day. This leads to expanding digitization of
banking administrations and versatile financial applications. A large number of transactions …
banking administrations and versatile financial applications. A large number of transactions …
Contemporary approaches to analyze non-stationary time-series: Some solutions and challenges
Enhancement of technology yields more complex time-dependent outcomes for better
understanding and analysis. These outcomes generate more complex, unstable, and …
understanding and analysis. These outcomes generate more complex, unstable, and …
Machine Learning based Data Mining for Detection of Credit Card Frauds
This research study analyzes the different data mining techniques used for the detection of
credit card frauds. Additionally, different data mining techniques are properly described in …
credit card frauds. Additionally, different data mining techniques are properly described in …