An Extension of One-Period Nash Equilibrium Model in Non-Life Insurance Markets

This paper deals with an extension of the one-period model in non-life insurance markets (cf. [1]) by using a transition probability matrix depending on some economic factors. We introduce a multi-period model and in each period the solvency constraints will be updated. Moreover, the model has the inactive state including some uninsured population. Similar results on the existence of premium equilibrium and sensitivity analysis for this model are presented and illustrated by numerical results.

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).

Automated Actuarial Data Analytics-Based Inflation Adjusted Frequency Severity Loss Reserving Model

In this paper, the Automated Actuarial Loss Reserving Model is developed and extended using machine learning. The traditional actuarial reserving techniques are no longer compatible with the increase in technological advancement currently at hand. As a result, the development of the alternative Artificial Intelligence Based Automated Actuarial Loss Reserving Methodology which captures diverse risk profiles for various policyholders through augmenting the Micro Finance services, Auto Insurance Services and Both Services lines of business on the same platform through the computation of the Comprehensive Automated Actuarial Loss Reserves (CAALR) has been implemented in this paper. The introduction of the four further types of actuarial loss reserves to those existing in the actuarial literature seems to significantly reduce lapse rates, reduce the reinsurance costs as well as expenses and outgo. As a matter of consequence, this helps to bring together a combination of new and existing policyholders in the insurance company. The frequency severity models have been extended in this paper using ten machine learning algorithms which ultimately leads to the derivation of the proposed machine learning-based actuarial loss reserving model which remarkably performed well when compared to the traditional chain ladder actuarial reserving method using simulated data.

Patterns of human-wildlife conflict and compensation practices around Daxueshan Nature Reserve, China

Understanding the spatial patterns of human-wildlife conflict is essential to inform management decisions to encourage coexistence, but it is constrained by the lack of spatially-explicit data. We collected spatially-implicit data of human-wildlife conflicts from 2009-2015 around Daxueshan Nature Reserve, Yunnan, China, and investigated the patterns and drivers of these conflicts. A questionnaire was also designed to capture local resident attitudes toward insurance-based compensation for the losses caused by targeted wildlife. We found that the Asiatic black bear （Ursus thibetanus） was the most conflict-prone animal around the reserve, followed by the rhesus macaque （Macaca mulatta） and Southeast Asian sambar （Cervus equinus）. Conflicts were unevenly distributed among seasons, villages, and communities, with several grids identified as conflict hotspots. Poisson models revealed that human-bear conflicts were negatively related to distance to the reserve and proportion of forest, but positively correlated to the proportion of cropland. Binomial models showed that communities affected by crop depredation were positively correlated with the proportion of cropland and negatively correlated with distance to the reserve, whereas communities affected by livestock depredation were negatively correlated with the proportion of cropland. The insurance-based scheme has compensated over 90% of losses, to the satisfaction of 90.6% of respondents. Our results suggest that human-bear conflict could be potentially reduced by eliminating food crops near the reserve boundary and livestock grazing at conflict hotspots.In addition, the insurance-based scheme could be replicated at a broader scale with improvement in loss assessment.

A Research on Whole Life Insurance

The formulas of premiums and premium reserves of a kind of mixed whole life insurance were obtained by the methods of actuarial science. Then we take a typical policy of whole life insurance in present Chinese market as an example to analyze its expense design and predict its market prospects.

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.

On the Issue of Commercial Insurance and Commercial Insurance Market in the Slovak Republic

The article is concentrated on the Slovak commercial insurance, commercial insurance market, non-life insurance, and international risks on the Slovak Republic. Since 1 May 2004, the Slovak insurance market has been part of the uniform European Union insurance market, which includes over 5,000 insurance companies. After Slovakia’s admission to the European Union, several legislative changes have been adopted in the area of commercial insurance industry, which also influenced non-life insurance and the insurance of international risks as part of non-life risks. The most recent act in the area of commercial insurance mentioned in the paper is the Act of the National Council SR No. 39/2015 Coll. on Insurance, in which there are legislative changes in life and also non-life insurance. Basic terms are defined and commented on in the first two chapters （Lowry, Rawlings, ＆ Merkin, 2015）. The nature of international risks as part of non-life risks is described in the second chapter. International risks are classified in the third chapter; international risks are subdivided in the paper into commercial or trade risks, political and economic risks, and special types of risks.

On the Issue of Commercial Insurance Market as in the Slovak Republic

The insurance industry in the Slovak Republic has become an important dynamically developing area of economy.Insurance affects all the activities into the national economy,touching every company,business,citizen,society,and foreign countries.The Slovak insurance market is developed.As at 31.12.2017,there operated 21 commercial insurance companies on the Slovak commercial insurance market.The evolution of the market in life insurance in recent years is more dynamic than in the non-life insurance.

优化我国养老金制度体系:个人养老金制度的发展定位

我国已初步建成了第三支柱个人养老金制度,但该制度尚未实现规模化发展。分析现行养老金制度体系面临的现实困境后发现诸多问题,如第一支柱可持续性面临挑战,第二支柱发挥的作用有限,养老资产规模不足等。个人养老金制度对于优化我国养老金体系具有关键作用。据此,明确个人养老金制度的发展定位,包括完善三支柱养老保障体系、提高基本养老保险待遇水平、增加养老金资产储备、强化个人养老储备意识。提出政府应该协调发展三支柱养老保险,实施税收激励政策并加强宣传教育以激励个人的有效参与,优化养老资产储备的投资管理的相关建议。

基于供需匹配的商业养老财富储备体系路径优化研究

老年人日益多元的养老需求亟需坚实的养老财富储备作为基础。除了制度化的养老金之外,非制度化的商业养老财富储备则可以通过更加灵活的方式为国民提供更丰富的养老经济保障。当前银行、基金、保险、信托等金融机构利用自身特色,创新和开发了类别和形式多样的养老金融产品,给广大国民养老财富储备提供了新的选择。但由于国民财富积累规模有限、养老金融专业认知欠缺,制约了其商业养老财富储备参与能力和意愿;同时,当前我国资本市场发展不稳定不完善,国民信任度不高,商业养老财富储备的针对性服务也有待提升,阻碍了供给的有效性。未来应通过完善收入分配政策、提高国民养老金融素养、丰富商业养老金融产品供给等方式更好匹配商业养老财富储备供给和需求,此外,还要营造良好的养老金融市场环境,重塑国民养老金融参与信心。

中国存款保险基金规模充裕性测度:理想与现实

美国硅谷银行和签名银行的破产为全球存款保险制度变革带来新的警示,本文搭建一个符合复杂配置问题特性的存款保险市场博弈竞争框架,并在博弈竞争框架的基础上推导了一个解决衡量存款保险基金规模充裕性问题的理想定价测度模型,进一步结合2015—2021年38家中国上市银行的实际观测数据进行模拟测度。研究结果表明:中国存款保险基金现实储备水平符合理想“有限充裕”状态,且在系统性银行与非系统性银行赔付标准下,一般风险冲击对中国存款保险基金充裕性的影响效应存在明显差异。建议尽快推行基金储备目标制、建立商业银行综合数据库并推行银行分类监管标准框架。

预付费挂号结合自费转医保的移动支付体系

为减少患者门诊缴费时间,保证预约挂号患者医保报销需要,减轻门诊压力,提高就诊效率,建设一个完整的线上缴费并兼顾医保报销的系统就显得尤为重要。本文构件了以医院微信服务号为核心的移动支付体系、多检验机制等措施实现了患者的在线缴费,并针对线上预约挂号患者无法脱卡享受医保报销问题,联合推出了“自费转医保”。实践证明,线上挂号缴费结合“自费转医保”,能有效地减少患者挂号缴费等待时间,保证了患者的医保报销的需要,明显提高了该院预约挂号人次,缓解了门诊窗口的压力。

运用保险理论的备用容量辅助服务分散决策机理初探

电力市场中的备用容量辅助服务一般都是集中处理的 ,由系统运行人员确定并向备用容量供应商购买所需的备用容量 ,再把相应的费用分摊给用户。这种方法很难保证辅助服务的高效率 ,并会导致辅助服务市场中的投机现象。备用容量可以通过分散决策的方法由每个用户自主决定吗 ?如果可以 ,怎样使每个用户制定最优的辅助服务购买计划 ?如果采用分散的方法 ,即每个用户都尽可能最大化自己的利益 ,能否使其实现全社会效益最大 ?文中就这些问题做了基础性探讨 ,并针对两种情况进行了建模和分析 :1通过要求电能供应商提高发电可靠性来减小用户电能被中断的风险 ,其中采用了“供给者保险”( provider insurance)方法 ;2假设市场有电能供应商、用户 (被保险者 )和备用容量供应商 (承保者 ) 3个参与者 ,用户和备用容量供应商就备用容量进行交易 ,并以两者间的保险条款促使备用容量供应商履行其责任。两种情况的研究均表明 ,一旦用户购买了适当定义的保险单 ,就会对承保者引入约束和激励 ,使其为自身利益而积极地提供用户所要求的可靠性或备用容量。同时 ,购买保险还可以使用户减少预期的停电损失 ,将风险转移到中立的承保者身上。文中还证明了所提出的分散决策方法能够达到社会效益最优。

两种备用容量分散决策方法及其比较

电力市场中的辅助服务一般都是集中处理的。系统运行人员负责确定并购买所需的备用容量 ,再把相应的费用分摊给用户。备用容量决策一般基于经验和规程 ,不进行优化计算 ,所以这种做法可能导致低效率。在市场环境中 ,应鼓励采用分散决策方法 ,以便通过市场的“无形之手”达到市场均衡点和市场效率。文中提出了两种分散决策方法来确定备用容量 ,即分别基于合同和联营体的分散决策方法。这两种方法在实现中均应用保险理论来引导备用容量的最优分散决策 ,并同时减少用户的停电损失。证明了在一定条件下 ,基于联营体的方法更加有效 。

电力市场环境下备用容量的集中和分散优化决策

针对电力市场环境下,应该采用何种方式确定和荻取所需要的备用容量这个有普遍争议的问题,提出了集中优化方法和应用保险理论的优化方法。集中优化方法是以从发电公司购买成本和用户停电损失之和最小化为目标,通过集中方式确定所需的总的运行备用容量及其价格并在相关的发电公司间分配这些容量的方法。应用保险理论的分散优化方法是用户通过购买保险,把停电可能引起的损失转移给独立调度机构(ISO),从而引导ISO对备用容量进行有效的管理;同时,当发电公司没有投入所成交的备用容量时,ISO会对其进行高昂的惩罚,从而激励发电公司很好地履行合同职责。文中先导出了与备用容量相关的各个发电公司的成本函数和用户的效用函数,然后给出了相应的分散优化和集中优化的数学模型,以及求解算法,证明了在完全竞争的市场中分散优化方法可以得到和集中优化方法相同的最优解,即最大化社会福利。最后以有14个发电公司参与的模拟电力市场为例进行了仿真计算,说明所提出方法的基本特征。

考虑离群值的非寿险准备金进展法

在准备金进展法中考虑离群值的影响,采用残差箱线图对相关索赔数据进行离群值检验,然后选择合适插补值的一种改进的准备金进展法,并对支付率和结转率的尾部数据加以修正,改善了最后两个进展年的异常值不能被有效识别的情况。研究表明:改进的准备金进展法能够有效识别和调整增量已决赔款和增量已报案赔款中的离群值,降低了离群值对最终准备金评估结果的影响。

模糊利率下的寿险精算模型

利用可信性理论,把利息力累积函数描述为梯形模糊变量,将其引入到全离散定期人寿保险精算模型中,给出了该寿险的均衡纯保费和准备金的计算公式,并用数值算例说明了方法的可行性.

保障保护地内居民受益的自然资源经营方式——以九寨沟股份制为例

本文通过对九寨沟自然保护区的研究发现,在现行保护地管理体制下,由保护地管理机构主导、当地居民参与的股份制经营方式能较好地保障居民利益并保护资源;但资源经营的安排者和生产者未彻底分离致使经营效率低下,并影响该经营方式的可持续性。本研究认为九寨沟式的股份制经营方式仅是一种折中的方式,长期来看应将资源经营的安排者和生产者彻底分离。

寿险中的破产理论及应用

本文研究了求解寿险中破产概率的简洁方法 ,得到寿险破产模型 ,设计了求解寿险中的破产概率的一种算法 ,并得到寿险破产概率的一个上界。