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Autor:
Valdrighi, Giovani, Ribeiro, Athyrson M., Pereira, Jansen S. B., Guardieiro, Vitoria, Hendricks, Arthur, Filho, Décio Miranda, Garcia, Juan David Nieto, Bocca, Felipe F., Veronese, Thalita B., Wanner, Lucas, Raimundo, Marcos Medeiros
The widespread use of machine learning in credit scoring has brought significant advancements in risk assessment and decision-making. However, it has also raised concerns about potential biases, discrimination, and lack of transparency in these autom
Externí odkaz:
http://arxiv.org/abs/2409.20536