Prediction of bank transaction fraud using TabNet—an adaptive deep learning architecture

The development of online banking has brought about an increase in fraudulent operations, which is a major problem for banks. This study delves into the urgent requirement for interpretable, scalable, and top-notch fraud detection systems by using TabNet, an adaptable deep learning framework, on a K...

Descripció completa

Dades bibliogràfiques

Autors principals:	B.S. Prashanth, Manoj Kumar, Ariful Hoque, Nasser Al Muraqab, Immanuel Azaad Moonesar, Udo Christian Braendle, Ananth Rao
Format:	Artigo
Idioma:	Inglês
Publicat:	Elsevier 2026-03-01
Col·lecció:	International Review of Economics & Finance
Matèries:	FinTech Digital banking fraud Decision support systems Explainable artificial intelligence (XAI) Alternative deep neural networks (DNNs) TabNet
Accés en línia:	http://www.sciencedirect.com/science/article/pii/S1059056026000298
Etiquetes:	Afegir etiqueta Sense etiquetes, Sigues el primer a etiquetar aquest registre!