Measuring systemic risk for bank credit networks: A multilayer approach

Abstract

Systemic risk analysis has become a very important undertaking in most central banks after the Global Financial Crisis (GFC). This paper describes the Colombian credit system of banks and firms as a bipartite network of lenders and borrowers. To such network, we apply a spectral method to identify the most central actors, and a variant of the DebtRank algorithm to identify the banks and firms that would be the most vulnerable to shocks in the system, and the most impactful in propagating them. We perform our analysis with a multi-layer approach, analysing networks of loans in the Commercial, Housing, and Microcredit domain. Our analyses reveal a rich and heterogeneous systemic risk profile across the Colombian credit system, and highlight the presence of considerable network effects that would contribute to shape the propagation of shocks from the real economy to the banking system.