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).

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.

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.

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.

《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。

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。

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。

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。

农业保险精准理赔问题研究——以山东滨州为例

农业保险对稳定粮食生产、促进乡村振兴意义重大。我国是全球农业保险保费规模最大的国家,农业保险发展迅速,但是理赔不精准等问题阻碍了农业保险高质量发展。本文以山东滨州地区农业保险实践为例,着重探讨农业保险平均赔付、协商赔付等理赔不精准问题,分析原因并提出推进理赔科技化与数字化建设、完善理赔监督管理制度、加快试点创新型农业保险产品、提高保障水平等建议。

极端天气下某防波堤工程索赔及保险赔付实践

南亚某离岸防波堤,按规范和合同要求施工,由于遭遇到极端天气,导致部分防波堤被冲毁,项目管理团队依据FIDIC条款,对极端天气进行界定,并开展防波堤施工期工程索赔和保险理赔,最大限度的减少极端天气对防波堤实施的影响,上述工程索赔及保险赔付实践可以为后续同类项目在遇到类似工况下施工期索赔及保险赔付提供借鉴。

基于工程维修视角对质量全生命周期管理的研究

随着既有建筑物运营时间推移,配套基础设施故障问题频发,维修费用支出也逐年增加。本文通过对A园区近年维修事项进行分类汇总,从维修专业、维修原因等维度进行分析,并提出解决方案及思考建议,向前延伸,助力设计、施工期间的质量管理;向后拓展,助力运行维护的规范开展及运营期间的质量提升;同时通过保险理赔助力公司降本增效,为公司可持续发展提供了重要保障。

船舶事故保险索赔——以元宏轮螺旋桨丢失为例

本文通过分析元宏轮螺旋桨丢失事故的保险索赔案例,探讨了船舶事故保险索赔的策略、流程和关键要素。文章首先回顾了事故的发生和处理过程,然后详细分析了索赔的各个环节,包括损失评估、证据收集、索赔策略和法律依据等。最后,文章总结了船舶保险索赔的最佳实践,并提出了相应的建议。

农业巨灾保险气象理赔指数设计

气象灾害是造成农业巨灾的主要灾害之一,设计农业巨灾保险气象理赔指数,可以为开展农业巨灾保险提供技术支撑。文章利用鹰潭市3个区(市)国家气象站1991—2020年和区域气象站2015—2020年观测资料,结合鹰潭气候以及气象灾害出现特点,经专家咨询和调研,确定暴雨、干旱、大风和低温冻害等4种气象灾害作为鹰潭农业巨灾保险的气象灾种。根据不同灾害出现的气候概率以及投保单位的要求,设计鹰潭市农业巨灾保险不同等级的气象理赔指数;研究结果确定的4种气象灾害理赔指数,可根据客观气象数据决定是否理赔,不仅科学透明,同时指数化保险不但免去核灾过程的工作量和成本,还可以优化缩减赔付过程中的许多中间环节,有效避免了核灾过程中保险公司与投保人可能出现的争议以及道德风险。以2022年鹰潭市出现历史罕见的干旱为例,文章研究成果经受了实践检验,以乡镇为基本区域的干旱灾害保险气象理赔指数实际表现适用性良好。

汽车保险与理赔领域中的信用建设与社会责任:课程思政的价值导向与实践路径

本研究致力于论证在汽车保险及其理赔业务中诚信体系构建的关键性,并探讨如何借助课程思政的手段,将对社会负责的理念深植于这一领域之中。本文首先深入剖析了汽车保险理赔行业内信用体系的现有状况与面临的问题,接着强调了高校课程思政在引导正确价值观中的作用,并以“汽车保险与理赔”这门课程为例,提出了具体的课程思政实施路径与策略,旨在为促进汽车保险市场的健康成长提供实践指引。

基于GA-BP神经网络的车险索赔频率预测与优化研究

车险索赔频率的预测对于车险定价有着重要意义,近些年来,随着大数据技术的兴起,传统车险定价模型已经不能满足现在保险公司维度越来越高的大量的客户数据需求,为了提升车险索赔频率的预测精度,采用法国某保险公司车险客户的真实数据,将遗传算法加入到BP神经网络之中,对相关模型进行比较来选择最优模型。研究结果表明:遗传算法优化模型的预测精度明显优于BP神经网络,对车险索赔频率预测性能更好,可以有效降低车险定价成本。

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.