Corporate payments networks and credit risk rating

Understanding the structure of interactions between corporate firms is critical to identify risk concentration and the possible pathways of propagation of financial distress. In this paper we consider the interaction due to payments and, by investigating a large proprietary dataset of Italian firms, we characterize the topological properties of the payment network. We then focus on the relation between the network of payments and the risk of firms. We show the existence of an homophily of risk, i.e. the tendency of firms with similar risk profile to be statistically more connected among themselves. This effect is observed both when considering pairs of firms and when considering communities or hierarchies identified in the network. By applying machine learning techniques, we leverage this knowledge to show that network properties of a node can be used to predict the missing rating of a firm. Our results suggest that risk assessment should take quantitatively into account also the network of interactions among firms.