Network and Risk Analysis of Surety Bonds
This addresses risk propagation in large-scale projects for surety organizations, offering an incremental improvement over independent failure models.
The paper tackled the problem of risk assessment in surety bonds by modeling contractor networks as directed graphs and introducing a stochastic process based on the Friedkin-Johnsen model to simulate failures, finding that network effects increase average risk by approximately 2% in real-world data.
Surety bonds are financial agreements between a contractor (principal) and obligee (project owner) to complete a project. However, most large-scale projects involve multiple contractors, creating a network and introducing the possibility of incomplete obligations to propagate and result in project failures. Typical models for risk assessment assume independent failure probabilities within each contractor. However, we take a network approach, modeling the contractor network as a directed graph where nodes represent contractors and project owners and edges represent contractual obligations with associated financial records. To understand risk propagation throughout the contractor network, we extend the celebrated Friedkin-Johnsen model and introduce a stochastic process to simulate principal failures across the network. From a theoretical perspective, we show that under natural monotonicity conditions on the contractor network, incorporating network effects leads to increases in the average risk for the surety organization. We further use data from a partnering insurance company to validate our findings, estimating an approximately 2% higher exposure when accounting for network effects.