How Artificial Intelligence and machine learning research impacts payment card fraud detection: A survey and industry benchmark

NF Ryman-Tubb, P Krause, W Garn - Engineering Applications of Artificial …, 2018 - Elsevier
The core goal of this paper is to identify guidance on how the research community can better
transition their research into payment card fraud detection towards a transformation away …

Inductive graph representation learning for fraud detection

R Van Belle, C Van Damme, H Tytgat… - Expert Systems with …, 2022 - Elsevier
Graphs can be seen as a universal language to describe and model a diverse set of
complex systems and data structures. However, efficiently extracting topological information …

Scalable machine learning techniques for highly imbalanced credit card fraud detection: a comparative study

RA Mohammed, KW Wong, MF Shiratuddin… - PRICAI 2018: Trends in …, 2018 - Springer
In the real world of credit card fraud detection, due to a minority of fraud related transactions,
has created a class imbalance problem. With the increase of transactions at massive scale …

Computer-based systems having computing devices programmed to execute fraud detection routines based on feature sets associated with input from physical cards …

A Walters, G Rafferty, J Goodsitt - US Patent 10,748,155, 2020 - Google Patents
Abstract Systems and methods for performing fraud detection at POS devices based on
analysis of feature sets are disclosed. In one embodiment, an exemplary method may …

Computer-based systems having computing devices programmed to execute fraud detection routines based on feature sets associated with input from physical cards …

A Walters, G Rafferty, J Goodsitt - US Patent 11,257,091, 2022 - Google Patents
Systems and methods for performing fraud detection at POA devices based on analysis of
feature sets are disclosed. In one embodiment, an exemplary method may comprise …

Classification of imbalanced data streams with an adaptive window re-balancing with retaining knowledge framework

RA Mohammed - 2020 - researchportal.murdoch.edu.au
Imbalanced data is ubiquitous in many real-world domains such as bioinformatics, call logs,
cancer detection, finance, heart rates, and weather prediction. If one of the classes in a …