Paper: arXiv 2511.05691

Authors: Tamara Broderick, Ali Jadbabaie, Vanessa Lin, Manuel Quintero, Arnab Sarker, Sean R. Sinclair

Abstract

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.

Complexity vs Empirical Score

  • Math Complexity: 7.5/10
  • Empirical Rigor: 8.0/10
  • Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: This paper uniquely applies network theory and a stochastic Friedkin-Johnsen opinion dynamics model to surety bond risk analysis, filling a significant gap in insurance literature. It combines rigorous proof of convergence dynamics and risk amplification with strong empirical validation using a proprietary dataset of ~30,000 nodes, estimating a 2% baseline underestimation in risk exposure.

Research Flowchart

  flowchart TD
    A[Research Goal: Assess Network-Based Risk & Propagation in Surety Bonds] --> B[Data Inputs: Insurance Records & Directed Graph Construction]
    B --> C[Methodology: Extended Friedkin-Johnsen Model & Stochastic Simulation]
    C --> D[Theoretical Analysis: Monotonicity Conditions & Propagation Proof]
    C --> E[Empirical Validation: Real-World Insurance Dataset Analysis]
    D & E --> F[Key Outcome: Accounting for Network Effects Reveals ~2% Higher Risk Exposure]

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0 of 62 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.