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arXiv · 1912.09764

An Artificial Intelligence approach to Shadow Rating

Angela Rita Provenzano·Daniele Trifirò·Nicola Jean·Giacomo Le Pera·Maurizio Spadaccino·Luca Massaron·Claudio Nordio
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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.

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Angela Rita Provenzano, Daniele Trifirò, Nicola Jean, Giacomo Le Pera, Maurizio Spadaccino, Luca Massaron, Claudio Nordio. 2019-12-20. An Artificial Intelligence approach to Shadow Rating. https://arxiv.org/abs/1912.09764

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