Bank supervision using the Threshold-Minimum Dominating Set

• We introduce a novel methodology, the T-MDS, for efficient and swift bank supervision.
• The T-MDS is more efficient than the MDS and the MST in economics (and other) networks.
• We identify the most representative subset of banks (T-MDS) yielding an overview of the whole banking network behavior.
• We support that these banks can act as “sensors” of an imminent bank crisis.
• The identified neighborhoods can be used as pathways of possible bank contagion.

An optimized, healthy and stable banking system resilient to financial crises is a prerequisite for sustainable growth. Minimization of (a) the associated systemic risk and (b) the propagation of contagion in the case of a banking crisis are necessary conditions to achieve this goal. Central Banks are in charge of this significant undertaking via a close and detailed monitoring of the banking network. In this paper, we propose the use of an auxiliary supervision/monitoring system that is both efficient with respect to the required resources and can promptly identify a set of banks that are in distress so that immediate and appropriate action can be taken by the supervising authority. We use the network defined by the interrelations between banking institutions employing tools from Complex Networks theory for an efficient management of the entire banking network. In doing so, we introduce the Threshold Minimum Dominating Set (T-MDS). The T-MDS is used to identify the smallest and most efficient subset of banks that can be used as (a) sensors of distress of a manifesting banking crisis and (b) provide a path of possible contagion. We propose the use of this method as a supplementary monitoring tool in the arsenal of a Central Bank. Our dataset includes the 122 largest American banks in terms of their interbank loans. The empirical results show that when the T-MDS methodology is applied, we can have an efficient supervision of the whole banking network, by monitoring just a subset of 47 banks.