The paper proposes an explainable AI model that can be used in credit risk management and, in particular, in measuring the risks that arise when credit is borrowed employing credit scoring platforms. The model applies similarity networks to Shapley values, so that AI predictions are grouped...

ICOs are a new way for blockchain startups to finance project development by issuing coins or tokens in exchange for fiat money or Bitcoin or other cryptocurrencies. In this article, we start from the current distinction between different types of tokens and argue that it can create confusion...

The proposals to limit auditor liability, principally aimed at protecting the Big-4 from the risk of a catastrophic exposure to damages, are grounded on the assumption that auditors are generally over-deterred. The 2008 EC Commission Recommendation on auditor liability relies heavily on this...

This is the first European study to conduct an extensive empirical research of startup charters. Our aim is to test whether the significant reforms of the law on the Italian società a responsabilità limitata (the GmbH-type limited liability company) were successful in making Italian corporate...

Investments in Small and Medium Enterprise (SME) are facilitated by the availability of advanced machine learning (ML) methods, with high computational power and accuracy. However, despite their high accuracy, complex ML models do not provide sufficient explanation and may not be adequate for...

We present a statistical model which can be employed to monitor the time evolution of the COVID-19 contagion curve, and of the associated reproduction rate R0. The model is a Poisson autoregression of the daily new observed cases and can, differently from classical exponential growth models,...

This paper describes a multidimensional machine learning model and its implementation in a financial technology (fintech) application. The aim of the model is to learn from both micro economic financial data and macro economic trends the credit rating of companies that ask for credit. We show...