Bank Networks from Text: Interrelations, Centrality and Determinants

TL;DR

This paper introduces a novel text-based network analysis method to study bank interrelations and systemic risk by analyzing financial discourse, providing new insights beyond traditional numerical data analysis.

Contribution

It presents a text-to-network process and an information centrality measure to analyze bank importance from news articles, with visualization tools for qualitative assessment.

Findings

Identified key bank interrelations during the financial crisis

Quantified bank centrality trends over time

Provided a visual interactive interface for network analysis

Abstract

In the wake of the still ongoing global financial crisis, bank interdependencies have come into focus in trying to assess linkages among banks and systemic risk. To date, such analysis has largely been based on numerical data. By contrast, this study attempts to gain further insight into bank interconnections by tapping into financial discourse. We present a text-to-network process, which has its basis in co-occurrences of bank names and can be analyzed quantitatively and visualized. To quantify bank importance, we propose an information centrality measure to rank and assess trends of bank centrality in discussion. For qualitative assessment of bank networks, we put forward a visual, interactive interface for better illustrating network structures. We illustrate the text-based approach on European Large and Complex Banking Groups (LCBGs) during the ongoing financial crisis by quantifying bank interrelations and centrality from discussion in 3M news articles, spanning 2007Q1 to 2014Q3.