Adaptive Machine Learning for Credit Card Fraud Detection

This project list resources on the topic of Machine Learning for Credit Card Fraud Detection.

Publications

Credit Card Fraud Detection: a Realistic Modeling and a Novel Learning Strategy A. Dal Pozzolo, G. Boracchi, O. Caelen, C. Alippi and G. Bontempi, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2017. pdf
GOTCHA! Network-based fraud detection for social security fraud Van Vlasselaer, V., Eliassi-Rad, T., Akoglu, L., Snoeck, M., Baesens, B., Management Science, accepted 2017.
A graph-based, semi-supervised, credit card fraud detection system B. Lebichot, F. Braun, and O. Caelen and M. Saerens, International Workshop on Complex Networks and their Applications, 721--733, 2016. Springer
Feature engineering strategies for credit card fraud detection AC Bahnsen, D Aouada, A Stojanovic, B Ottersten, Expert Systems with Applications 51, 134-142, 2016
Ensemble of Example-Dependent Cost-Sensitive Decision Trees AC Bahnsen, D Aouada, B Ottersten, arXiv preprint arXiv:1505.04637, 2015

Example-dependent cost-sensitive decision trees AC Bahnsen, D Aouada, B Ottersten, Expert Systems with Applications 42 (19), 6609-6619, 2015
APATE: A novel approach for automated credit card transaction fraud detection using network-based extensions. Van Vlasselaer V., Bravo C., Caelen O., Eliassi-Rad T., Akoglu L., Snoeck M., Baesens B., Decision Support Systems. 2015. Elsevier
Detecting Credit Card Fraud using Periodic Features AC Bahnsen, D Aouada, A Stojanovic, 2015 IEEE 14th International Conference on Machine Learning and Applications.

Credit Card Fraud Detection and Concept-Drift Adaptation with Delayed Supervised Information A. Dal Pozzolo, G. Boracchi, O. Caelen, C. Alippi and G. Bontempi, International Joint Conference on Neural Networks (IJCNN), Killarney, Ireland, 2015. pdf
Learned lessons in credit card fraud detection from a practitioner perspective A. Dal Pozzolo, O. Caelen, Y. Le Borgne, S. Waterschoot, and G. Bontempi, Expert Systems with Applications, vol. 41, no. 10, pp. 4915–4928, 2014. pdf
Using HDDT to avoid instances propagation in unbalanced and evolving data streams A. Dal Pozzolo, R. A Johnson, O. Caelen, S. Waterschoot, N. V Chawla, and G. Bontempi, International Joint Conference on Neural Networks (IJCNN), Beijing, China, 2014. pdf
Cost sensitive credit card fraud detection using Bayes minimum risk AC Bahnsen, A Stojanovic, D Aouada, B Ottersten, Machine Learning and Applications (ICMLA), 2013

Fraud Analytics: Using Supervised, Unsupervised and Social Network Learning Techniques Bart Baesens, Véronique Van Vlasselaer, Wouter Verbeke, Amazon

Adaptive Machine Learning for Credit Card Fraud Detection A. Dal Pozzolo, Universite Libre de Bruxelles, 2015. pdf
Example-Dependent Cost-Sensitive Classification AC Bahnsen, University of Luxembourg, 2015.
FAIR: Forecasting and network analytics for collection risk management V. Van Vlasselaer, Katholieke Universiteit Leuven, 2015.