  This paper introduces a novel framework to study default dependence and
systemic risk in a financial network that evolves over time. We analyse several
indicators of risk, and develop a new latent space model to assess the health
of key European banks before, during, and after the recent financial crises.
First, we adopt the measure of CoRisk to determine the impact of such crises on
the financial network. Then, we use minimum spanning trees to analyse the
correlation structure and the centrality of the various banks. Finally, we
propose a new statistical model that permits a latent space visualisation of
the financial system. This provides a clear and interpretable model-based
summary of the interaction data, and it gives a new perspective on the topology
structure of the network. Crucially, the methodology provides a new approach to
assess and understand the systemic risk associated with a financial system, and
to study how debt may spread between institutions. Our dynamic framework
provides an interpretable map that illustrates the default dependencies between
institutions, highlighting the possible patterns of contagion and the
institutions that may pose systemic threats.
