Engineering models for catastrophe risk and their application to insurance

Internationally earthquake insurance,like all other insurance (fire,auto),adopted actuarial approach in the past, which is,based on historical loss experience to determine insurance rate.Due to the fact that earthquake is a rare event with severe consequence,irrational determination of premium rate and lack of understanding scale of potential loss led to many insurance companies insolvent after Northridge earthquake in 1994. Along with recent advances in earth science,computer science and engineering,computerized loss estimation methodologies based on first principles have been developed to the point that losses from destructive earthquakes can be quantified with reasonable accuracy using scientific modeling techniques. This paper intends to introduce how engineering models can assist to quantify earthquake risk and how insurance industry can use this information to manage their risk in the United States and abroad.

Climate Change and Heavy Rainfall-Related Water Damage Insurance Claims and Losses in Ontario, Canada

The objective of this paper was to project possible impacts of climate change on heavy rainfall-related water damage insurance claims and incurred losses for four selected cites (Kitchener-Waterloo, London, Ottawa, and Toronto) located at Ontario, Canada. To achieve this goal, the future climate change scenarios and rainfall simulations, at local scale, were needed. A statistical downscaling method was used to downscale five global climate model (GCM) scenarios to selected weather stations. The downscaled meteorological variables included surface and upper-air hourly temperature, dew point, west-east and south-north winds, air pressure, and total cloud cover. These variables are necessary to project future daily rainfall quantities using within-weather-type rainfall simulation models. A model result verification process has been built into the whole exercise, including rainfall simulation modeling and the development of downscaling transfer functions. The results of the verification, based on historical observations of the outcome variables simulated by the models, showed a very good agreement. To effectively evaluate heavy rainfall-related water damage insurance claims and incurred losses, a rainfall index was developed considering rainfall intensity and duration. The index was evaluated to link with insurance data as to determination of a critical threshold of the rainfall index for triggering high numbers of rainfall-related water damage insurance claims and incurred losses. The relationship between rainfall index and insurance data was used with future rainfall simulations to project changes in future heavy rainfall-related sewer flood risks in terms of water damage insurance claims and incurred losses. The modeled results showed that, averaged over the five GCM scenarios and across the study area, both the monthly total number of rainfall-related water damage claims and incurred losses could increase by about 13%, 20% and 30% for the periods 2016-2035, 2046-2065, and 2081-2100, respectively (from the four-city seasonal average of 12 ± 1.7 thousand claims and $88 ± $21 million during April-September 1992-2002). Within the context of this study, increases in the future number of insurance claims and incurred losses in the study area are driven by only increases in future heavy rainfall events.

A Statistical Analysis of Intensities Estimation on the Modeling of Non-Life Insurance Claim Counting Process

This study presents an estimation approach to non-life insurance claim counts relating to a specified time. The objective of this study is to estimate the parameters in non-life insurance claim counting process, including the homogeneous Poisson process (HPP) and the non-homogeneous Poisson process (NHPP) with a bell-shaped intensity. We use the estimating function, the zero mean martingale (ZMM) as a procedure of parameter estimation in the insurance claim counting process. Then, Λ(t) , the compensator of is proposed for the number of claims in the time interval . We present situations through a simulation study of both processes on the time interval . Some examples of the situations in the simulation study are depicted by a sample path relating to its compensator Λ(t). In addition, an example of the claim counting process illustrates the result of the compensator estimate misspecification.

A Bayesian Inference of Non-Life Insurance Based on Claim Counting Process with Periodic Claim Intensity

The aim of this study is to propose an estimation approach to non-life insurance claim counts related to the insurance claim counting process, including the non-homogeneous Poisson process (NHPP) with a bell-shaped intensity and a beta-shaped intensity. The estimating function, such as the zero mean martingale (ZMM), is used as a procedure for parameter estimation of the insurance claim counting process, and the parameters of model claim intensity are estimated by the Bayesian method. Then,Λ(t), the compensator of N(t) is proposed for the number of claims in a time interval (0,t]. Given the process over the time interval (0,t]., the situations are presented through a simulation study and some examples of these situations are also depicted by a sample path relating N(t) to its compensatorΛ(t).

Real-world treatment patterns of gastrointestinal neuroendocrine tumors: A claims database analysis

AIM To describe real-world treatment patterns of gastrointestinal neuroendocrine tumors(GI NET).METHODS In this retrospective cohort study,we used 2009-2014 data from 2 United States commercial claims databases to examine newly pharmacologically treated patients using tabular and graphical techniques. Treatments included somatostatin analogues(SSA),cytotoxic chemotherapy(CC),targeted therapy(TT),interferon(IF) and combinations. We identified patients at least 18 years of age,with ≥ 1 inpatient or ≥ 2 outpatient claims for GI NET who initiated pharmacologic treatment from 7/1/09-6/30/14. A 6 mo clean period prior to first treatment ensured patients were newly treated. Patients were followed until end of enrollment or the study end date,whichever was first.RESULTS We identified 2258 newly treated GI NET patients: mean(SD) age was 55.6 years(SD = 9.7),47.2% of the patients were between 55 and 64 years,and 48.8% were female. All regions of the United States were represented. 59.6% started first-line therapy with SSA monotherapy(964 with octreotide LAR,380 with octreotide SA,and 1 with lanreotide),33.3% CC,3.6% TT,and 0.5% IF. The remainder received combinations. Mean follow up was 576 d. Overall mean first-line therapy duration was 361 d(449 d for SSA,215 for CC,267 for TT). 58.9% of patients had no pharmacological treatment beyond first line. The most common secondline was combination therapy with SSA. In graphical pattern analysis,there was no clear pattern visible after first line therapy.CONCLUSION In this study,60% of patients initiated treatment with SSA alone or in combination. The relatively long time to discontinuation suggests possible sustained effectiveness and tolerability.

Research on Insurance Pricing

In this paper, by analysing relationship between insurance premium and insurance compensation, the derivative assets pricing theory and the partial differential equation are used to studythe pricing of insurance products and establish insurance price models. In addition, insurance priceformulas for several general insurance types are also presented. The insurance pricing method thatis given in the paper doesn't depend on mortality ratio and the probability distribution of losses.It is an obvious difference between the insurance pricing method in the paper and the traditionalinsurance pricing methods. Thereby, this paper serves to develop a insurance pricing method, andhas important practical or immediate significance. Finally, the application of the method is given.

Performance Evaluation of Motor Insurance Companies: Panel Data Evidence from Nigeria

This paper evaluated performance of motor insurance companies in Nigeria. The objectives were to determine the following: 1) significant effects of claims settlements on motor insurance firms’ earned premium;2) differences in managerial/technological capabilities among the companies and 3) effects of policy (or time effect) on insurance firms’ output within the study period. Panel data obtained for this study comprised operational data on premium earned and direct claims settlement by these companies over a period of six (6) years. Using panel data statistical models, we found that direct claims settlement negatively affected insurance companies’ earned premium. Also, significant differences in technological and managerial capabilities were found to exist among the companies, though only one company exhibited this heterogeneity. Besides, there were no policy impacts (or time effect) on vehicle insurance firms’ output in the study period. Policy implications of the results were discussed.

Applications of Mogulskii, and Kurtz-Feng Large Deviation Results to Risk Reserve Processes with Aggregate Claims

In this paper we examine the large deviations principle (LDP) for sequences of classic Cramér-Lundberg risk processes under suitable time and scale modifications, and also for a wide class of claim distributions including (the non-super- exponential) exponential claims. We prove two large deviations principles: first, we obtain the LDP for risk processes on D∈[0,1] with the Skorohod topology. In this case, we provide an explicit form for the rate function, in which the safety loading condition appears naturally. The second theorem allows us to obtain the LDP for Aggregate Claims processes on D∈[0,∞) with a different time-scale modification. As an application of the first result we estimate the ruin probability, and for the second result we work explicit calculations for the case of exponential claims.

The Study about Autumobile Insurance Based on Linear Empirical Bayesian Estimation

Automobile insurance is one of the most popular research areas, and there are a lot of different methods for it .We uses linear empirical Bayesian estimation for the study of automobile insurance, giving the estimator of the policy’s future claim size. Thus, a new point of view is given on the pricing of automobile insurance.

扎根理论视角下安全生产责任保险事故预防功能发挥研究

作为安全生产社会治理体系的重要制度设计之一,安全生产责任保险借助社会专业力量防范化解事故风险,是安全生产工作理念实现从“管理”到“治理”的重要推手。为解决现阶段安全生产责任保险推行过程中事故预防功能发挥不显著这一问题,采用扎根理论探究了事故预防技术服务落实不到位的成因机制,包括参与主体内生动力不足、服务覆盖范围不全面、联动协调机制不健全、监管反馈工作未闭环以及规范性文件保障不坚实5个相互关联的主范畴,并通过差异显著性检验验证了主范畴的提炼效果。最后,提出深化宣传、拓宽范围、加强联动、定期评价、严格奖惩与完善标准6项措施建议,旨在推动安全生产责任保险从被动事后赔付向主动风险防控转变。

The First Two Moments of Aggregate Claims in a Markovian Environment

We consider the discounted aggregate claims when the insurance risks and financial risks are governed by a discrete-time Markovian environment.We assume that the claim sizes and the financial risks fluctuate over time according to the states of economy,which are interpreted as the states of Markovian environment.We will then determine a system of differential equations for the Laplace-Stieltjes transform of the distribution of discounted aggregate claims under mild assumption.Moreover,using the differentio-integral equation,we will also investigate the first two order moments of discounted aggregate claims in a Markovian environment.

Insurance ratemaking method for risk of construction diversion project

Based on analyzing risk factors of diversion project,synthetic risk rate and engineering insurance period,the frequency and distribution law of loss are researched on the grounds that foundation pit is submerged after diversion project ceases to be effective.And then,the standpoint that these total loss is subject to non-homogeneous compound Poisson processes is put forward.Furthermore,the collective risk model of the total loss about engineering insurance is established on the basis of construction diversion project risk.Ultimately,insurance ratemaking method for construction engineering risk and its mathematical expression are presented,which provides theoretical method for the insurance ratemaking of hydropower engineering to some extent.

地方政府干预视角下农业保险公司的双重经营压力分析

基于2008-2020年31个省(区、市)的面板数据,运用固定效应、门槛回归等模型,从业务理赔、成本费用双重维度,定量评估地方政府干预对农险业务经营的影响。结果显示:地方政府干预显著提高了农险业务的简单赔付率和综合费用率,造成了农险公司的双重经营压力。进一步研究发现,当参保密度跨过负向门槛值后,地方政府干预造成的农险赔付压力显著减弱。鉴于此,应通过划定地方政府干预红线、加快科技赋能农业保险等措施,促进农险公司科学、自主经营。

《汽车保险与理赔》新形态教材开发策略思考

《汽车保险与理赔》课程与其它汽车类专业课具有明显区别,其教学过程主要依据保险条款与理赔流程进行,如采用传统以内容体系为主的教材进行授课,可能会由于授课内容过于枯燥而难以吸引学生。因此,鉴于《汽车保险与理赔》这门工科课程的文科属性,急需撰写相关新形态教材,以提高教师授课效果并增加学生学习兴趣。

云南省野生动物肇事补偿现状及对策研究

云南省野生动物肇事频发,收集2014—2020年云南省野生动物公众责任险理赔等数据,结合州(市)肇事野生动物物种数据进行量化分析,比较分析陕西、贵州、甘肃、吉林等省关于补偿范围、补偿标准、财政负担等野生动物肇事补偿办法的规定。现阶段云南补偿工作仍存在着补偿范围有限、标准不一、程序复杂、经费不足等问题,结合现有国家补偿政策建议从健全法律法规、加大普法宣传、加强多学科研究、拓宽经费来源、简化申请流程等方面进行提升。

农业保险对农民收入的影响研究——基于2013-2021年省级面板数据

农业保险作为一种风险管理工具,旨在减轻农民因自然灾害所遭受的损失,确保农民收入稳定增长。本研究结合农业保险保障赔付效益,在分析农业保险对农民收入的影响机制基础上,利用2013-2021年全国30个省份(未包括港澳台及西藏)的省级面板数据,从农业保险保障密度、保障深度和赔付效益3个维度衡量农业保险发展水平指数,并构建双向固定效应模型进行实证分析。结果表明:第一,由于农业保险定价不科学与理赔不尽规范使得农业保险保障赔付效益不足,农业保险对农民收入具有显著的负向作用。第二,异质性分析表明,以“胡焕庸线”为界的东南部地区,农业保险对农民收入显著为负,西北部地域该影响并不显著。最后,提出运用互联网技术科学定价、加强市场监管,规范理赔、促进区域间农业保险市场协调发展等的政策建议。

余缺调剂全国统筹制度下的基本养老金时空差异研究

为了分析余缺调剂全国统筹制度对基本养老金收支地区差异的影响,在精算预测2021—2050年基本养老金收支的基础上,用泰尔指数、空间计量经济学方法测度时空差异。结果表明:余缺调剂制度能够缓解基本养老金近期收支压力,延缓赤字时间,但无法改变远期基金缺口和地区差距扩大的趋势;余缺调剂制度能够降低基本养老金收支的地区差异,但长远来看,调剂力度越来越小,基本养老金收支依然存在明显的空间异质性;基本养老金收支存在空间依赖性,收支比高的地区和收支比低的地区呈现集中分布特征。未来需要及时充实统筹调剂金,保证统筹调剂金的长期供给,制定差异化支持政策,优化经济空间布局,以延缓养老金缺口时间,降低区域差距。

医院商保“一站式”结算平台的设计与应用

目的解决商业健康保险报销“理赔难、手续繁、报销慢”的问题,提升医疗服务效率,改善医院商保患者的就医体验。方法在确保信息安全的前提下,建立统一的接口标准和服务流程,实现医院、医保、商保的数据联通,打通医院和保险公司之间的数据孤岛。结果武汉市某三级甲等医院成为湖北省首家成功构建商保“一站式”结算平台的医院,实现医院就诊患者出院时医保、商保和自付的“一窗口”“一站式”结算。结论提供商保“一站式”结算服务是医院通过“互联网+医疗健康”推进便民惠民服务、改善患者服务体验的重要举措,大幅节省了商保患者的时间和精力,实现了商保患者“看病结算最多跑一次”的目标。

印度农作物保险损失理赔模式及其启示

作为以小农户为主体的国家,印度非常重视农作物保险的发展,为了提高理赔数据质量,印度建立了以政府为主导的农作物理赔查勘制度,将全国农作物理赔数据集中在一个平台。印度政府相关部门还积极研究农作物产量测算技术,有效提升了农作物保险的理赔速度和质量。近年来,随着中国农作物保险的快速发展,产生越来越多的保险索赔,快速、准确地测算农作物损失的重要性日益突出。借鉴印度经验,创新农作物保险的理赔模式,提升理赔数据质量,维护农民利益,促进农作物保险高质量发展,为乡村振兴提供更好的保险服务。

冬小麦保险理赔的高精度气象数据查询研究——以河南省一次大风气象灾害为例

为解决河南省冬小麦保险理赔中气象凭证获取渠道不统一、查询效率低、理赔控制难、理赔不规范等问题,本文首先对2018—2021年河南冬小麦保险案例进行分析,发现暴雨、风灾、冻灾和旱灾是河南省主要的农业气象灾害保险理赔类型。基于风灾持续时间短、成灾范围小、保险理赔获取气象凭证查询难度大,本研究以河南省冬小麦风灾为例,对气象站点数据、智能网格实况数据和基于站点数据克里金插值法三种方法进行对比,研究河南冬小麦风灾保险理赔优化查询方法。结果表明:基于站点数据,克里金插值法优于站点数据和智能网格实况数据;当极大风速大于10 m/s时,克里金插值法可以作为未覆盖站点数据的有效补充,在保险理赔查询气象凭证中具有较好的适用性,可提高保险理赔中获取气象凭证的有效性和准确性,为冬小麦农业保险风灾理赔的气象查询提供参考依据。