In the credit risk domain, lenders frequently face situations where there is no, or limited historical lending outcome data. This generally results in limited or unaffordable credit for some individuals and small businesses. Transfer learning can potentially reduce this limitation, by leveraging knowledge from related domains, with sufficient outcome data. We investigated the potential for applying transfer learning across various credit domains, for example, from the credit card lending and debt consolidation domain into the small business lending domain.
CITATION STYLE
Suryanto, H., Guan, C., Voumard, A., & Beydoun, G. (2020). Transfer Learning in Credit Risk. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11908 LNAI, pp. 483–498). Springer. https://doi.org/10.1007/978-3-030-46133-1_29
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