Enhancing Credit Card Default Prediction: Prioritizing Recall Over Accuracy
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-3817-5_32
Reference16 articles.
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4. Danovi A, Olgiati S (2015) ZETATM methodology and variation in the systemic risk of default: accounting for the effects of type II (false negative) errors variation on lending. Korporativnye Finansy 1:71–81. https://doi.org/10.17323/j.jcfr.2073-0438.9.1.2015.71-81
5. Xiao Y (2023) The predictive power of credit scores: examining default probability in Taiwanese credit card clients. Adv Econ Manage Political Sci 42:139–147. https://doi.org/10.54254/2754-1169/42/20232097
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