  Risks threatening modern societies form an intricately interconnected network
that often underlies crisis situations. Yet, little is known about how risk
materializations in distinct domains influence each other. Here we present an
approach in which expert assessments of risks likelihoods and influence
underlie a quantitative model of the global risk network dynamics. The modeled
risks range from environmental to economic and technological and include
difficult to quantify risks, such as geo-political or social. Using the maximum
likelihood estimation, we find the optimal model parameters and demonstrate
that the model including network effects significantly outperforms the others,
uncovering full value of the expert collected data. We analyze the model
dynamics and study its resilience and stability. Our findings include such risk
properties as contagion potential, persistence, roles in cascades of failures
and the identity of risks most detrimental to system stability. The model
provides quantitative means for measuring the adverse effects of risk
interdependence and the materialization of risks in the network.
