Stabilizing machine learning models with Age-Period-Cohort inputs for scoring and stress testing
Machine learning models have been used extensively for credit scoring, but the architectures employed suffer from a significant loss in accuracy out-of-sample and out-of-time. Further, the most common architectures do not effectively integrate economic scenarios to enable stress testing, cash flow,...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2023-06-01
|
| Series: | Frontiers in Applied Mathematics and Statistics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fams.2023.1195810/full |