  We study the difference between the level of systemic risk that is
empirically measured on an interbank network and the risk that can be deduced
from the balance sheets composition of the participating banks. Using
generalised DebtRank dynamics, we measure observed systemic risk on e-MID
network data (augmented by BankFocus information) and compare it with the
expected systemic risk of a null model network, obtained through an appropriate
maximum-entropy approach constraining relevant balance sheet variables. We show
that the aggregate levels of observed and expected systemic risks are usually
compatible but differ significantly during turbulent times (in our case, after
the default of Lehman Brothers and the VLTRO implementation by the ECB). At the
individual level instead, banks are typically more or less risky than what
their balance sheet prescribes due to their position in the network. Our
results confirm on one hand that balance sheet information used within a proper
maximum-entropy network model provides good aggregate estimates of systemic
risk, and on the other hand the importance of knowing the empirical details of
the network for conducting precise stress tests on individual banks, especially
after systemic events.

Risk Management;Physics and Society