From Text to Bank Interrelation Maps

TL;DR

This paper introduces a novel method to analyze bank interrelations by constructing networks from financial discussion texts, revealing dynamic patterns and qualitative insights during financial crises.

Contribution

It presents a new approach using textual data to visualize and analyze bank interconnections, capturing temporal dynamics and qualitative context beyond numerical data.

Findings

Network structures reflect crisis periods and bank distress.

Connections between distressed banks and authorities fluctuate over time.

Textual analysis provides qualitative insights into interbank relations.

Abstract

In the wake of the ongoing global financial crisis, interdependencies among banks have come into focus in trying to assess 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 discussion. Co-mentions of bank names are turned into a network, which can be visualized and analyzed quantitatively, in order to illustrate characteristics of individual banks and the network as a whole. The approach allows for the study of temporal dynamics of the network, to highlight changing patterns of discussion that reflect real-world events, the current financial crisis in particular. For instance, it depicts how connections from distressed banks to other banks and supervisory authorities have emerged and faded over time, as well as how global shifts in network structure coincide with severe crisis episodes. The usage of textual data holds an additional advantage in the possibility of gaining a more qualitative understanding of an observed interrelation, through its context. We illustrate our approach using a case study on Finnish banks and financial institutions. The data set comprises 3.9M posts from online, financial and business-related discussion, during the years 2004 to 2012. Future research includes analyzing European news articles with a broader perspective, and a focus on improving semantic description of relations.