In this study, we characterize systemic risk by the way in which financial institutions are interconnected. We construct time varying tail dependency networks to study the complex interdependencies in the financial system. Time varying lower dependency networks spanning 2008-2017 are constructed for 48 Chinese financial institutions based on Clayton’s time varying copula model and minimum spanning tree algorithm. We find that the extreme dependence between financial institutions increases during crises, with clear spikes during the global financial crisis as well as the Chinese interbank market “money shortage” in 2013 and the Chinese stock market crash in 2015. dependency networks tail, we see a high concentration, both within and between sectors. Securities companies play an important role in the cross-industry transfer of tail risks. We also identify seven financial institutions of systemic importance to the Chinese financial system using topological properties.