An Artificial Intelligence approach to Shadow Rating

Angela Rita Provenzano, Daniele Trifir\`o, Nicola Jean, Giacomo Le Pera, Maurizio Spadaccino, Luca Massaron and Claudio Nordio

Papers from arXiv.org

Abstract: We analyse the effectiveness of modern deep learning techniques in predicting credit ratings over a universe of thousands of global corporate entities obligations when compared to most popular, traditional machine-learning approaches such as linear models and tree-based classifiers. Our results show a adequate accuracy over different rating classes when applying categorical embeddings to artificial neural networks (ANN) architectures.

Date: 2019-12
New Economics Papers: this item is included in nep-big, nep-cmp and nep-rmg
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