Effective detection of sophisticated online banking fraud on extremely imbalanced data

By Wei Wei, Jinjiu Li, Longbing Cao, Yuming Ou, Jiahang Chen. World wide web (Bussum), 2012

343 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems

View Paper: https://www.semanticscholar.org/paper/4fbf863f8adfc21640f81fc4958c9d636371a8ba

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Information Systems

Citations in the corpus

Fraud detection system: A survey (2016, background): “But it has major limitation because it is not possible to detect all different kinds of frauds because it only looks for known patterns of misuse (Wei et al., 2012).”
Modelling Multi-Component Predictive Systems as Petri Nets (2017, background): “Some examples are astronomy (Berriman et al. 2007), biology (Shade and Teal 2015), clinical research (Teichmann et al. 2010), archive scanning (Messaoud et al. 2011), telecommunications (Maedche et al. 2000), banking (Wei et al. 2013) and process industry (Budka et al. 2014) to name a few.”
Learning from imbalanced data: open challenges and future directions (2016, background): “In real-life applications such as fraud detection [61] or cheminformatics [12] we may deal with problems with imbalance ratio ranging from1:1000 up to 1:5000.”
A survey on addressing high-class imbalance in big data (2018, methodology): “[64] presented a system called i-Alertor.”
Machine Learning with Oversampling and Undersampling Techniques: Overview Study and Experimental Results (2020, background): “However, this assumption is not correct in several applications, for example weather forecast [1], diagnosis of illnesses [2], ﬁnding fraud [3], as nearly most of the instances are labeled with one class, while few instances are labeled as the other class.”
Token-level Adaptive Training for Neural Machine Translation (2020, unknown): “This problem can be observed in various tasks (Wei et al., 2013; Johnson and Khoshgoftaar, 2019).”