Experience Rating in Group Life Insurance

Abstract

Methods for experience rating of group life contracts are obtained as empirical Bayes or linear Bayes solutions in heterogeneity models. Each master contract is assigned a latent random quantity representing unobservable risk characteristics, which comprise mortality and possibly also age distribution and distribution of the sums insured, depending on the information available about the group. Hierarchical extensions of the set-up are discussed. An application of the theory to data from an authentic portfolio of groups revealed substantial between-group risk variations, hence experience rating could be statistically justified.     

Incentive Effects of Community Rating in Insurance Markets: Evidence from Massachusetts Automobile Insurance

Rate regulations in insurance markets often impose cross-subsidies in insurance premiums from low-risk consumers to high-risk consumers. This paper develops the hypothesis that premium cross-subsidies affect risk taking by insurance consumers, and tests this hypothesis by examining the marginal impact of premium subsidies and overcharges on future insurance costs. The empirical analysis uses 1990–2003 rating cell-level data from the Massachusetts automobile insurance market, in which regulation produced large cross-subsidies across cells. Consistent with the hypothesized effects, premium subsidies are found to be significantly related to higher future insurance costs, and the opposite effects are found for premium overcharges.     

寿险公司信用评级制度探析

随着我国保险市场对外开放步伐的加快，国内保险市场竞争主体的日益增多，实行与国际接轨的保证评级制度已势在必行，这既是保险企业建立竞争优势和保证持续、健康发展的内在要求，也是社会公众加强对保险公司了解的要求，更是监管部门加强对保险公司偿付能力监管、更好的履行监管职责的迫切要求。     

论构建中国保险信用评级制度的微观基础

当前,我国保险市场出现了较严重的市场失灵;一方面某些保险人及其行为代理人违背诚信原则,引起了公众的信任危机,抑制了保险市场的进一步拓展;另一方面保险人之间的无序竞争,恶性竞争态势牺牲了保险市场的经营效率。这在很大程度上是由于我国保险市场交易主体之间的严重的信息不对称分布格局所致。本文从信息不对称角度出发,提供了一个矫正我国保险市场信息不对称状态的制度安排-保险信用评级制度的微观理论框架。     

风险导向的保险保障基金费率模式研究

保险保障基金的费率模式是构建保险保障基金制度的核心问题之一,模式的不同选择对保险公司的经营管理有着不同的导向作用。中国现有的单一费率模式未考虑风险,具有明显不足。在分析了其他各国和地区所采用的与风险相关联的保险保障基金费率模式后,本文提出应基于我国“偿二代”监管体系构建出动态转移式费率模式在设计出与风险分级挂钩的动态转移式费率模式的规则之后,基于实际数据并遵循政策的延续性原则测算了初始费率,设计了动态转移式费率模式的费率转移规则并进行了测算。研究表明,动态转移式费率模式基本保持了原有保险保障基金的规模,且能给保险公司注重偿付能力风险管理和注重保险产品保障能力提供有力的正向指引。     

全国主粮作物减产风险评估与保险费率厘定研究

《关于加快农业保险高质量发展的指导意见》对开展农业保险风险区划提出了具体要求.本研究针对水稻、小麦、玉米三大主粮作物,利用作物模型集合模拟器、配合县级历史单产统计数据,使用单产时空融合方法还原了1991～2016年全国10 km栅格水平的单产损失率,厘定了保险纯风险损失率和大灾风险附加费率.结果 显示,在100％保障水...     

信用评级业：创新、升级、信用监管

本文从信用评级业存在与发展的市场前提入手,分析制约评级业现时发展的桎梏,认为在全球新一轮经济结构调整的过程中,古老的信用评级正面临着生死抉择与历史机遇,信用评级业必须创新理念、革新技术、升级业态,从传统的行为与等级预测升级发展为信用资本定价。在此基础上,全文论证并阐述了信用是资本、信用评级是资本定价、信用评级涉及社会资源再分配的理念,认为必须构建新的政府信用监管框架,成立＂中国信用监督管理委员会＂、国家级信用研究中心、打造我国自主经营的相关航母机构。     

Credibility Estimation of Distribution Functions with Applications to Experience Rating in General Insurance

This article presents a new credibility estimation of the probability distributions of risks under Bayes settings in a completely nonparametric framework. In contrast to the Ferguson's Bayesian nonparametric method, it does not need to specify a mathematical form of the prior distribution (such as a Dirichlet process). We then show the applications of the method in general insurance premium pricing, a procedure commonly known as experience rating, which utilizes the insured's claim experience to calculate a proper premium under a given premium principle (referred to as a risk measure). As this method estimates the probability distributions of losses, not just the means and variances, it provides a unified nonparametric framework to experience rating for arbitrary premium principles. This encompasses the advantages of the well-known Bühlmann's and Ferguson's approaches, while it overcomes their drawbacks. We first establish a linear Bayes method and prove its strong consistency in nonparametric settings that require only knowledge of the first two moments of the loss distributions considered as a stochastic process. Then an empirical Bayes method is developed for the more general situation where a portfolio of risks is observed but no knowledge is available or assumed on their loss and prior distributions, including their moments. It is shown to be asymptotically optimal. The performance of our estimates in comparison with traditional methods is also evaluated through theoretical analysis and numerical studies, which show that our approach produces premium estimates close to the optima.