arXiv:2605. 18147v2 Announce Type: replace Abstract: Predictive models play a pivotal role in credit risk management, guiding critical decisions through accurate estimation of default probabilities and losses.
By Bart Baesens, Andreas Goethals, Stefan Lessmann, Simon De Vos, Cristi\'an Bravo, David Martens, Victor Medina-Olivares, Christophe Mues, Maria Oskarsd\'ottir, Seppe vanden Broucke, Tony Van Gestel, Tim Verdonck, Wouter Verbeke
arXiv:2601. 20533v2 Announce Type: replace-cross Abstract: Survival analysis has become a standard approach for modelling time to default by time-varying covariates in credit risk.
By Jianwei Peng (Humboldt-Universit\"at zu Berlin), Stefan Lessmann (Humboldt-Universit\"at zu Berlin, Bucharest University of Economic Studies)
arXiv:2402. 01811v2 Announce Type: replace Abstract: Credit scoring has been catalogued by the European Commission and the Executive Office of the US President as a high-risk classification task, in light of the potential harms of making loan approval decisions based on models that would be biased against certain groups.
By Pablo Casas, Huan Yu, Christophe Mues
arXiv:2606. 18479v1 Announce Type: new Abstract: Reject inference methods are widely used to mitigate survival bias in credit scoring, yet their effectiveness remains poorly understood.
By Bruno Scarone, Ricardo Baeza-Yates
arXiv:2606. 06776v1 Announce Type: new Abstract: Customer churn prediction is a central task in customer analytics, particularly in non-contractual, pay-per-use service environments where disengagement is not explicitly observed and must be inferred from behavioral inactivity.
By Muhammad Jawad Mufti, Omar Hammad, Haitham Saleh, Muqaddas Gull
arXiv:2606. 10333v1 Announce Type: new Abstract: Credit risk prediction is a critical problem in the consumer credit industry.
By Hongzhe Zhang, Jiarong Xu, Jing He, Xiao Fang