  The policy objective of safeguarding financial stability has stimulated a
wave of research on systemic risk analytics, yet it still faces challenges in
measurability. This paper models systemic risk by tapping into expert knowledge
of financial supervisors. We decompose systemic risk into a number of
interconnected segments, for which the level of vulnerability is measured. The
system is modeled in the form of a Fuzzy Cognitive Map (FCM), in which nodes
represent vulnerability in segments and links their interconnectedness. A main
problem tackled in this paper is the aggregation of values in different
interrelated nodes of the network to obtain an estimate systemic risk. To this
end, the Choquet integral is employed for aggregating expert evaluations of
measures, as it allows for the integration of interrelations among factors in
the aggregation process. The approach is illustrated through two applications
in a European setting. First, we provide an estimation of systemic risk with a
of pan-European set-up. Second, we estimate country-level risks, allowing for a
more granular decomposition. This sets a starting point for the use of the
rich, oftentimes tacit, knowledge in policy organizations.
