Reference : Transfer learning for credit card fraud detection : A journey from research to production.
Scientific congresses, symposiums and conference proceedings : Paper published in a journal
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/50240
Transfer learning for credit card fraud detection : A journey from research to production.
English
Siblini, Wissam mailto []
Coter, Guillaume mailto [Worldline]
Fabry, Remy mailto []
He-Guelton, Liyun mailto [Worldline]
Oble, Frederic mailto [Worldline]
Lebichot, Bertrand mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > TruX >]
Le Borgne, Yann-Aël mailto []
Bontempi, Gianluca mailto []
2021
The Proceedings of the Data Science and Advanced Analytics (DSAA 2021) IEEE conference
Yes
DSAA 2021
April 2021
[en] Transfer Learning ; Fraud detection
[en] The dark face of digital commerce generalization is the increase of fraud attempts. To prevent any type of attacks, state-of-the-art fraud detection systems are now embedding Machine Learning (ML) modules. The conception of such modules is only communicated at the level of research and papers mostly focus on results for isolated benchmark datasets and metrics. But research is only a part of the journey, preceded by the right formulation of the business problem and collection of data, and followed by a practical integration. In this paper, we give a wider vision of the process, on a case study of transfer learning for fraud detection, from business to research, and back to business.
Innoviris
http://hdl.handle.net/10993/50240

File(s) associated to this reference

Fulltext file(s):

FileCommentaryVersionSizeAccess
Open access
A Journey from Research to Production.pdfPublisher postprint277.42 kBView/Open

Bookmark and Share SFX Query

All documents in ORBilu are protected by a user license.