The Accounting Network: How Financial Institutions React to Systemic Crisis

PLoS One. 2016 Oct 13;11(10):e0162855. doi: 10.1371/journal.pone.0162855. eCollection 2016.

Abstract

The role of Network Theory in the study of the financial crisis has been widely spotted in the latest years. It has been shown how the network topology and the dynamics running on top of it can trigger the outbreak of large systemic crisis. Following this methodological perspective we introduce here the Accounting Network, i.e. the network we can extract through vector similarities techniques from companies' financial statements. We build the Accounting Network on a large database of worldwide banks in the period 2001-2013, covering the onset of the global financial crisis of mid-2007. After a careful data cleaning, we apply a quality check in the construction of the network, introducing a parameter (the Quality Ratio) capable of trading off the size of the sample (coverage) and the representativeness of the financial statements (accuracy). We compute several basic network statistics and check, with the Louvain community detection algorithm, for emerging communities of banks. Remarkably enough sensible regional aggregations show up with the Japanese and the US clusters dominating the community structure, although the presence of a geographically mixed community points to a gradual convergence of banks into similar supranational practices. Finally, a Principal Component Analysis procedure reveals the main economic components that influence communities' heterogeneity. Even using the most basic vector similarity hypotheses on the composition of the financial statements, the signature of the financial crisis clearly arises across the years around 2008. We finally discuss how the Accounting Networks can be improved to reflect the best practices in the financial statement analysis.

MeSH terms

  • Accounting / methods*
  • Algorithms*
  • Banking, Personal / methods
  • Databases, Factual
  • Humans
  • Principal Component Analysis

Grants and funding

The authors acknowledge support from the "Progetto di Interesse CNR CRISISLAB". Michelangelo Puliga and Alessandro Chessa are employed by Linkalab. Linkalab provided support in the form of salaries for authors MP and AC, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.