In the last decade, the demand for sustainable and social investments has improved. The mutual funds industry has responded to market needs by offering a number of investment products focused on Environmental, Social and Governance (ESG) companies. The aim of this article is to understand if an ESG score can actually be considered a valid criterion that portfolio managers could adopt, along with traditional risk–return optimisation, in selecting asset portfolios. The paper analyses the link between the performance and the ESG score of different sectoral portfolios (one for each sector of the Global Industry Classification Standard), entirely composed of ESG assets, in the search for a clear and strong positive correlation that could suggest an overall advantage to focus on an ex ante choice of assets with high ESG scores.

In the last few years, financial managers, supervisors and policy makers have been collectively engaged on the role of the banking and financial sector in relation to environmental and sustainability issues. The efficiency level that characterizes the production process of banks and financial intermediaries is strictly interconnected with sustainability so that, from a long term perspective, cost and profit efficiency reveals to be one of the most important premises for sustainability. This work aimed to analyze the level of efficiency achieved by European banking groups to verify if some key drivers of efficiency deriving from strategic choices outlined by literature on single banks (i.e., size, number of branches, cost income ratio and geographical location) are the same when considering banking groups. The study is focused on the period 2011–2016 that is characterized by, at least, two critical events that occurred after the sub-prime crisis. The level of efficiency of each banking group was measured with the Stochastic Frontier Approach and then the units were clustered into three homogeneous sets. Observing these clusters, the results show that the groups belonging to some specific countries appear to be more efficient with respect to others. Moreover, the banking groups characterized by many branches and a high level of cost income ratio exhibit a medium level of efficiency. Eventually, the biggest banking groups are the least efficient.

Understanding the correlation between different customers’ loss of creditworthiness is crucial to credit risk analysis. This paper describes a novel method, based on a weighted network model, in which a set of firms, customers of the same bank, represent the nodes while their links and weights derive from the total transaction amounts. We explore the contagion mechanism deriving from the transmission of the difficulties of one customer to other clients of the same bank so highlighting areas where contagion risk is higher. We use a real proprietary data set provided by a bank to illustrate the proposed approach.