A Phase Transition Phenomenon for Ruin Probabilities in a Network of Agents and Objects

TL;DR

This paper investigates a phase transition phenomenon in ruin probabilities within a bipartite network model of agents and objects, revealing conditions under which joint ruin can be avoided despite individual risks.

Contribution

It introduces a novel phase transition analysis for ruin probabilities in networked risk models, extending classical risk theory to complex interconnected systems.

Findings

Identification of a phase transition threshold for joint ruin probabilities

Demonstration that network structure influences ruin risk

Extension of classical ruin theory to bipartite networks

Abstract

The classical Cram\'er-Lundberg risk process models the ruin probability of an insurance company experiencing an incoming cash flow - the premium income, and an outgoing cash flow - the claims. From a system's viewpoint, the web of insurance agents and risk objects can be represented by a bipartite network. In such a bipartite network setting, it has been shown that joint ruin of a group of agents may be avoided even if individual agents would experience ruin in the classical Cram\'er-Lundberg model. This paper describes and examines a phase transition phenomenon for these ruin probabilities.