Lost in a black‐box? Interpretable machine learning for assessing Italian SMEs default
Lisa Crosato,
Caterina Liberati,
Marco Repetto
Abstract:Academic research and the financial industry have recently shown great interest in Machine Learning algorithms capable of solving complex learning tasks, although in the field of firms' default prediction the lack of interpretability has prevented an extensive adoption of the black‐box type of models. In order to overcome this drawback and maintain the high performances of black‐boxes, this paper has chosen a model‐agnostic approach. Accumulated Local Effects and Shapley values are used to shape the predictors… Show more
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