A Study On The Mechanisms Of Systemic Risk Contagion In The Insurance Industry

With the strengthening of the financial attributes of the insurance industry,the risk contagion of the insurance industry is also increasing.This paper analyses the contagion mechanism of systemic risk in the insurance industry through the lens of immunology and finds that the contagion mechanism of systemic risk in the insurance industry is similar to that of an infectious disease,starting with the "disease" of the failure and collapse of one or a few insurance companies,which then spreads to the entire system through contagion.Infectious diseases are characterized by the presence of pathogens and the body’s immune system’s ability to react rapidly to invading pathogens,as the immune system identifies and eliminates ’foreign’ substances,just as humans do in the process of removing pathogens.In the case of insurance companies,adverse external shocks may force them to react.If an insurer’s ’immune system’ is deficient,adverse shocks can enter and dominate,causing crises such as illiquidity and insolvency,and the insurer will become a new source of contagion,spreading to other insurers with which it is associated.An insurer’s defense against risk can also be classified according to the body’s immune system,which can be divided into intrinsic immunity(non-specific immunity)and adaptive immunity(specific immunity).Insurance companies suffer from inherent immunity deficiencies such as lack of creditor governance,large maturity differences in assets and liabilities,and significant information asymmetries.The homogeneity of the insurance industry’s operations also makes many insurers generally vulnerable and susceptible to contagion from external shocks at the same time.Adaptive immunity is the immunity built up by insurers through internal governance or industry governance,and is the last line of defense against external risk contagion,helping insurers to recover quickly from risk.Insurers’ last line of defense against external shocks is also very volatile due to potential problems such as weak governance mechanisms and weak internal controls.Government bailouts can act as a lender of last resort to help troubled companies emerge from risk in a manner similar to pharmaceutical interventions,but they must also be applied with due consideration of their side effects.This paper presents a SIR model based on the transmission process of infectious diseases.The core idea is to divide the population of the study area into finite combinations of several populations and to express the dynamics of infection transmission between different populations in the form of differential equations.In order to simulate the dynamics of systematic risk transmission in the insurance industry in a more visual way,this paper estimates the magnitude of the transmission rate based on the classical SIR model of infectious disease dynamics using the comprehensive risk rating data of insurance companies;at the same time,it proposes an improved SIR model applicable to risk transmission analysis in the insurance industry,and then applies Python programming to simulate the risk transmission process.Based on the simulation results,it is found that under the hypothetical environment of the current insurance system,reducing the contagion rate,increasing the self-recovery rate and increasing the government bailout rate can reduce the peak number of troubled crisis companies,and the degree of impact decreases in the order of self-recovery rate,government bailout rate and contagion rate.The paper also analyses the marginal effects of self-recovery and government bailout rates on the peak number of distressed crisis firms and finds that at current low levels of self-recovery and government bailout rates,increasing self-recovery and government bailout rates can significantly reduce the peak number of distressed crisis firms regardless of the value of the contagion rate,and that increasing the self-recovery rate is more effective than increasing the government bailout rate in preventing systemic risk in the insurance industry.