We investigate the resilience of financial networks to exogenous shocks, which can trigger primary and secondary defaults that propagate through the network in a cascading manner. Building on previous studies that have developed tools for numerically assessing the resilience of financial networks to such shocks, we conduct a series of numerical experiments to analyze how the structure of financial networks affects their resilience. Specifically, we evaluate the worst-case loss scenarios of the financial system in relation to fluctuations in banks’ cash inflows across different network structures. Our analysis explores the effects of network sparsity versus connectivity, as well as the impact of clustering and heterogeneity in liability patterns among financial institutions.