Tackling fraud detection with an enhanced Kepler optimization and ghost opposition-based learning. [PDF]
Egami RH +3 more
europepmc +1 more source
A synergistic enhancement of the Ivy algorithm for GAN-based imbalanced classification. [PDF]
Xu H, Xiong J, Wu J, Zhou X, Xu R, Wu H.
europepmc +1 more source
Consumer credit evaluation model for free trade ports by a sparse attention transformer and graph neural network. [PDF]
Wu M, Sabri MF, Meng C, Wang S.
europepmc +1 more source
Big data in financial risk management: evidence, advances, and open questions: a systematic review. [PDF]
Theodorakopoulos L +2 more
europepmc +1 more source
Cyber Risk Management of API-Enabled Financial Crime in Open Banking Services. [PDF]
Ojehomon OG, Cichorska J, Michnik J.
europepmc +1 more source
Synergistic review of automation impact of big data, AI, and ML in current data transformative era. [PDF]
Rath S, Pandey M, Rautaray SS.
europepmc +1 more source
A new fusion neural network model and credit card fraud identification. [PDF]
Jiang S +4 more
europepmc +1 more source
Related searches:
Sequence classification for credit-card fraud detection
Expert Systems With Applications, 2018Abstract Due to the growing volume of electronic payments, the monetary strain of credit-card fraud is turning into a substantial challenge for financial institutions and service providers, thus forcing them to continuously improve their fraud detection systems. However, modern data-driven and learning-based methods, despite their popularity in other
Michael Granitzer +2 more
exaly +3 more sources
Machine Learning for Credit Card Fraud Detection
Proceedings of the 2021 1st International Conference on Control and Intelligent Robotics, 2021With the development of E-bank, the use of credit cards gets an unprecedented improvement as well as the problem of credit card fraud. To overcome this problem, we need automatic systems to finish the fraud detection. The number of monitored account data is so large that our human resources are unable to detect the whole dataset. Also, since the number
Yuxin Gao, Shuoming Zhang, Jiapeng Lu
openaire +1 more source
Credit Card Fraud Detection with Resampling Techniques
2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT), 2021With the advancement of technology and consumer strength, the use of credit cards has rapidly increased. Credit Cards have shortened a transaction process making it simpler but has made the system prone to frauds. The information regarding one's credit card can easily be stolen and misused.
Prerak Parekh +3 more
openaire +1 more source

