D. Delpini

S. Battiston

M. Riccaboni

G. Gabbi

F. Pammolli

G. Caldarelli

Complex networks detect the driver institutions of an interbank market and ascertain that intervention policies should be time-scale dependent.

The Statistical Physics of Complex Networks has recently provided new theoretical tools for policy makers.
Here we extend the notion of network controllability to detect the financial institutions, i.e. the drivers, that
are most crucial to the functioning of an interbank market. The system we investigate is a paradigmatic case
study for complex networks since it undergoes dramatic structural changes over time and links among nodes
can be observed at several time scales. We find a scale-free decay of the fraction of drivers with increasing
time resolution, implying that policies have to be adjusted to the time scales in order to be effective.
Moreover, drivers are often not the most highly connected ‘‘hub’’ institutions, nor the largest lenders,
contrary to the results of other studies. Our findings contribute quantitative indicators which can support
regulators in developing more effective supervision and intervention policies.

Evolution of controllability in interbank networks