A Novel Banking Supervision Method using a Threshold-Minimum Dominating Set

A healthy and stable banking system resilient to financial crises is a prerequisite for sustainable growth. Minimization of a) the associated systemic risk and b) of the contagion effect in a banking crisis is a necessary condition to achieve this goal. The Central Bank is in charge of this significant undertaking via a close and detailed monitoring of the banking network that can significantly limit the outbreak of a crisis and a subsequent contagion. In this paper, we propose the use of an auxiliary monitoring system that is both efficient on 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 interrelations between banking institutions for efficient monitoring of the entire banking network employing tools from Complex Networks theory. In doing so, we introduce the Threshold Minimum Dominating Set (T-MDS). The T-MDS is used to identify the smallest most efficient subset of banks able to act as a) sensors of distress of a manifested banking crisis and b) provide a path of possible contagion. Moreover, at the discretion of the regulator, the methodology is versatile in providing multiple layers of supervision and monitoring by setting the appropriate threshold levels. 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 total assets. 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 small subset of banks. We will show that, the proposed methodology is able to achieve an efficient overview of the 122 banks by only monitoring 47 T-MDS nodes.