scholarly journals An Examination of Product Structure and Efficiency within the Property Insurance Industry in China

2013 ◽  
Vol 6 (11) ◽  
Author(s):  
Chenxi Li ◽  
Gaiqin Hu ◽  
J. Tim Query
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhiguang Li ◽  
Yaokuang Li ◽  
Wei Zhang

Purpose Based on the perspective of complexity theory, the operation process of property insurance companies can be regarded as a complex dynamic nonlinear chaotic system. This paper aims to measure the operating efficiency of 29 Chinese domestic property and casualty (P&C) companies and 18 foreign-invested P&C companies from 2011 to 2017 and outline the path to achieving high-quality development. Design/methodology/approach The data were obtained from the Chinese Insurance Yearbook and China Statistical Yearbook 2012–2018. The data envelopment analysis method was used to calculate the technical efficiency of property insurance companies and fuzzy set qualitative comparative analysis is used for configuration analysis of determinants affecting technical efficiency. Findings This paper founds the average technical efficiency of Chinese domestic P&C insurance companies was 0.914 and that of foreign-invested P&C insurance companies was 0.895. The average total factor productivity of Chinese domestic P&C insurance companies was 1.058 and that of foreign-invested P&C insurance companies was 1.051. There were three modes to improve the company’s technical efficiency, with high loss ratio and low reinsurance ratio, poor employee education and higher leverage ratio and high leverage ratio and low reinsurance ratio as the core conditions. Originality/value This study puts forward four applicable, targeted and proven ways to improve the technical efficiency of China’s P&C insurance industry. These configurations were verified by the cases of existing property insurance companies, which can provide practical references for the insurance industry.


Author(s):  
Zifeng Zhao ◽  
Peng Shi ◽  
Xiaoping Feng

Learning the customers’ experience and behavior creates competitive advantages for any company over its rivals. The insurance industry is an essential sector in any developed economy and a better understanding of customers’ risk profile is critical to decision making in all aspects of insurance operations. In this paper, we explore the idea of using copula-based dependence models to learn the hidden risk of policyholders in property insurance. Specifically, we build a novel copula model to accommodate the dependence over time and over space among spatially clustered property risks. To tackle the computational challenge caused by the discreteness feature of large-scale insurance data, we propose an efficient multilevel composite likelihood approach for parameter estimation. Provided that latent risk induces correlation, the proposed customer learning method offers improved predictive analytics by allowing insurers to borrow strength from related risks in predicting new risks and also helps reveal the relative importance of the multiple sources of unobserved heterogeneity in updating policyholders’ risk profile. In the empirical study, we examine the loss cost of a portfolio of entities insured by a government property insurance program in Wisconsin. We find both significant temporal and spatial association among property risks. However, their effects on the predictive distribution of loss cost are different for the new and renewal policyholders. The two sources of dependence are complements for the former and substitutes for the latter. These findings are shown to have substantial managerial implications in key insurance operations such as experience rating, capital allocation, and reinsurance arrangement.


2011 ◽  
Vol 58 (3) ◽  
pp. 1295-1309 ◽  
Author(s):  
Wen-Ko Hsu ◽  
Pei-Chiung Huang ◽  
Ching-Cheng Chang ◽  
Cheng-Wu Chen ◽  
Dung-Moung Hung ◽  
...  

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhiguang Li ◽  
Yaokuang Li ◽  
Dan Long

PurposeFrom the perspective of cause and effect, the operational processes of property insurance companies can be considered as historical events. The purpose of this study is to measure the operating efficiency of China's property insurance industry, explore the determinants that affect technical efficiency and outline the path to achieving high-quality development.Design/methodology/approachWe chose 44 Chinese property insurance companies as research objects. The data were obtained from the Chinese Insurance Yearbook and China Statistical Yearbook 2015–2017. First, the data envelopment analysis (DEA) method was used to calculate the technical efficiency of property insurance companies. Then, Tobit regression and quantile regression were adopted to explore the influencing factors of technical efficiency. Finally, the fuzzy-set qualitative comparative analysis (fsQCA) method was employed to summarize the path to improving the operating efficiency of property insurance companies.FindingsThe empirical results in the first stage suggested that the operation efficiency of China's property insurance industry was technically inefficient, and the scale efficiency was relatively better than the pure technical efficiency. In the second stage, we observed that the drivers for firm size, reinsurance rate, claim ratio and equity restriction were important determinants of an insurance firm's efficiency.Research limitations/implicationsWe also put forward four applicable, targeted and proven ways to improve the technical efficiency of property insurance companies. These configurations are verified by cases of existing property insurance companies, which can provide practical references for the insurance industry.Originality/valueOur research enriches the insurance literature and efficiency methods, particularly regarding the specific paths of improving the technical efficiency. The relationship between elements and results is analyzed from a systematic perspective, and the research results are not only more consistent with what logic might imply but also more instructive for the improvement of reality.


2011 ◽  
Vol 55-57 ◽  
pp. 1489-1493 ◽  
Author(s):  
Shao Fu Song ◽  
Guang Jin Li ◽  
Ying Sheng Su

This paper presents a practical assessment of brand competitiveness in property insurance industry through Fuzzy Comprehensive Assessment. The multicriteria evaluation model and weighting matrix have been determined by the Analytic Hierarchy Process (AHP). The synthetically appraisal score of property insurance companies can be estimated by Fuzzy Comprehensive Assessment, which contains a two-stage decision. At the end of this paper, three listed property insurance companies have been evaluated following the above methods.


1997 ◽  
Vol 2 (2) ◽  
pp. 4-5

Abstract Controversy attends use of the AMA Guides to the Evaluation of Permanent Impairment (AMA Guides) in defining injured workers’ permanent partial disability benefits: States desire an efficient, nonsubjective way to determine benefits for nonscheduled injuries and are using the AMA Guides to define the extent of disability. Organized labor is concerned that use of the AMA Guides, particularly with modifications, does not yield a fair analysis of an injured worker's disability. From its first issue, The Guides Newsletter emphatically emphasized and clearly stated that impairment percentages derived according to AMA Guides criteria should not be used to make direct financial awards or direct estimates of disability. The insurance industry and organized labor differ about the use of the AMA Guides in defining permanent partial disability (PPD). Insurers support use of the AMA Guides because they seek a uniform system that minimizes subjectivity in determining benefits. Organized labor is particularly concerned about the lack of fairness of directly equating impairment and disability, and if the rating plays a role in defining disability, additional issues also must be considered. More states are likely to use the AMA Guides with incorporation of additional features such as an index to PPD.


Sign in / Sign up

Export Citation Format

Share Document