Credit scoring with class imbalance data: An out-of-sample and out-of-time perspective.
Published: 14 February 2023| Version 1 | DOI: 10.17632/bzr2rxttvz.1
Data for predicting default risk in the next 12, 36, and 60 months. A training sample is provided for each outcome window, as well as out-of-sample (OOS) and out-of-time (OOT) testing samples. OOS is generated using the same timeline as the training sample, whereas OOT is created from a future timeline. The samples are all generated using the same characteristics/features.
University of KwaZulu-Natal - Westville Campus
Financial Risk, Machine Learning, Credit