Assessing Systemic Risk in the Insurance Sector via Network Theory

TL;DR

This paper introduces a network-based framework to identify key insurance companies contributing to systemic risk, using a novel centrality measure to evaluate their influence on network stability.

Contribution

It develops a complex network model with a new centrality measure, Weighted Effective Resistance Centrality, to assess insurers' systemic importance.

Findings

Identifies influential insurers in systemic risk propagation

Proposes a new network indicator for robustness analysis

Provides a method to quantify individual insurer impact

Abstract

We provide a framework for detecting relevant insurance companies in a systemic risk perspective. Among the alternative methodologies for measuring systemic risk, we propose a complex network approach where insurers are linked to form a global interconnected system. We model the reciprocal influence between insurers calibrating edge weights on the basis of specific risk measures. Therefore, we provide a suitable network indicator, the Weighted Effective Resistance Centrality, able to catch which is the effect of a specific vertex on the network robustness. By means of this indicator, we assess the prominence of a company in spreading and receiving risk from the others.