Analysis About Solvency Of Property Insurance Company In Our Country Based On Semi-parametric Logistic Regression

The insurance industry plays an important role in the modern financial system, in modern society, insurance has become an indispensable part for protecting the normal economic operation and social stability. Lack of solvency will not only affect the interest of the insured and affect the operational stability of insurance company, but also affect the healthy development of China's insurance industry. Insurance Solvency refers to the risks borne by insurers in the event of responsibility for payment of compensation and when it has the financial ability to compensate. Insurance solvency regulation has become the core of every national regulatory agency to monitor the insurance industry. It is of great significance.This Dissertation mainly researches the influence factors of Property Insurance Company Solvency. First it elaborated the solvency status at home and abroad, introduced the commonly ways used to study solvency and the current situation of domestic insurance regulation; Then it explained the meaning and significance of solvency supervision, listed the three important kinds of solvency regulation mode in the world and Assessed their Enlightenment to our country. Subsequently our analysis focused on the factors which affect the insurance company solvency, Since the "insurance solvency regulations" in 2008 does not involve monitoring indicators, but some amount of supervision.We selected 11 important factors closely related to solvency as the main indicators reference to Insurance Regulatory Commission on the insurance solvency margin and regulatory indicators of the provisions of regulations in China 2003. Finally we give a Logistic regression model and semi-parameter Logistic regression model.Data comes from the "China Insurance Yearbook" (2005-2008),We use the Logistic regression model to analyze the significant degree of individual indicators, as well as the impact on the solvency. Then we get the Logistic regression model of six indicators.In order to further analyze, we give a semi-parameter Logistic regression models. The six variables which significantly affect solvency are as the linear part of the influence of factors of the semi-parametric logistic regression model. Factors which are not significant are as the non-linear part of the semi-parametric model. Finally, we get the semi-parametric logistic regression model.Comparison of the results of two methods, Both models have in common is the relevance of the solvency and indicators, But the coefficients of two methods is inconsisten. Semi-parametric Logistic regression model is advantageous than normal Logistic regression model in analying solvency. However, this method is only an attempt for analying the solvency, There are many issues that need further study and discussion.