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With the digital transformation of commercial banks and the online transfer of credit transactions, the relationship between credit subjects tends to be complex, and personal credit risk management is facing challenges. The contagiousness of personal credit risk and the relationship among credit subjects are poorly understood in the field of credit risk management. This study used an SEIR infectious disease model to reveal the mode and structure of associated credit risk based on the theory and method of complex networks, and it explored the status and influencing factors of associated credit risk in a scale-free network using simulation experiments. The research findings indicate that the coefficient of latency, the coefficient of risk contagion, the coefficient of direct recovery, the coefficient of latent transformation, the coefficient of immune recovery, and the structure of the association network have a significant influence on the scale and threshold of associated credit risk. This study reveals comprehensive reasons for the outbreak of credit risk clusters and provides a new perspective for financial institutions, such as commercial banks, to help them manage credit risk. |
