Alliance-based modeling of interbank lending networks: insights into risk contagion dynamics - Ziwen Jiang; Xu Jiang; Huanlan Yan; Yu Xie; Jiamin Yao (PLoS ONE, 2025)
The financial market, a highly intricate and dynamic system, relies heavily on banks as its central pillars. The interactions among these banks are pivotal in shaping the stability and efficiency of the overall financial system. A comprehensive understanding of the interbank relationships and network structures is essential to uncover the underlying mechanisms that drive financial markets. This paper presents a novel approach to modeling interbank lending as a dynamic network, aiming to explore the influence of banking alliances on risk contagion dynamics. While extensive research has been dedicated to interbank lending strategies, the role of long-term cooperative alliances and their structural effects on lending behavior has remained largely underexplored. In this study, we propose an innovative interbank lending strategy that integrates alliance relationships, facilitating the construction of networks that more accurately represent the characteristics of real-world banking alliances. Through a series of simulation experiments, we investigate the risk contagion dynamics within these alliance-based networks under different external shock scenarios. Our findings provide valuable insights into the resilience and contagion mechanisms of banking alliance networks, offering practical recommendations for both financial institutions and regulators in designing more effective risk mitigation strategies.