  Since 2008, the network analysis of financial systems is one of the most
important subjects in economics. In this paper, we have used the complexity
approach and Random Matrix Theory (RMT) for analyzing the global banking
network. By applying this method on a cross border lending network, it is shown
that the network has been denser and the connectivity between peripheral nodes
and the central section has risen. Also, by considering the collective behavior
of the system and comparing it with the shuffled one, we can see that this
network obtains a specific structure. By using the inverse participation ratio
concept, we can see that after 2000, the participation of different modes to
the network has increased and tends to the market mode of the system. Although
no important change in the total market share of trading occurs, through the
passage of time, the contribution of some countries in the network structure
has increased. The technique proposed in the paper can be useful for analyzing
different types of interaction networks between countries.
