Transfer Learning for Credit Card Fraud Detection: A Journey from Research to Production

• URL: http://arxiv.org/abs/2107.09323v1
• Date: Tue, 20 Jul 2021 08:29:04 GMT
• Title: Transfer Learning for Credit Card Fraud Detection: A Journey from Research to Production
• Authors: Wissam Siblini, Guillaume Coter, R\'emy Fabry, Liyun He-Guelton, Fr\'ed\'eric Obl\'e, Bertrand Lebichot, Yann-A\"el Le Borgne, Gianluca Bontempi
• Abstract summary: State of the art fraud detection systems are now embedding Machine Learning (ML) modules. 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.
• Score: 29.50963185641885
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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