Web: http://arxiv.org/abs/2201.11486

Jan. 28, 2022, 2:11 a.m. | Prateek Kate, Vadlamani Ravi, Akhilesh Gangwar

cs.LG updates on arXiv.org arxiv.org

Churn prediction in credit cards, fraud detection in insurance, and loan
default prediction are important analytical customer relationship management
(ACRM) problems. Since frauds, churns and defaults happen less frequently, the
datasets for these problems turn out to be naturally highly unbalanced.
Consequently, all supervised machine learning classifiers tend to yield
substantial false-positive rates when trained on such unbalanced datasets. We
propose two ways of data balancing. In the first, we propose an oversampling
method to generate synthetic samples of minority …

arxiv banking generative adversarial network insurance management network relationship

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