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).

Empirical study on optimal reinsurance for crop insurance in China from an insurer's perspective

This study investigates the optimal reinsurance for crop insurance in China in an insurer＇s perspective using the data from Inner Mongolia, Jilin, and Liaoning, China. On the basis of the loss ratio distributions modeled by An Hua Crop Risk Evaluation System, we use the empirical model developed by Tan and Weng（2014） to study the optimal reinsurance design for crop insurance in China. We find that, when the primary insurer＇s loss function, the principle of the reinsurance premium calculation, and the risk measure are given, the level of risk tolerance of the primary insurer, the safety loading coefficient of the reinsurer, and the constraint on reinsurance premium budget affect the optimal reinsurance design. When a strict constraint on reinsurance premium budget is implemented, which often occurs in reality, the limited stop loss reinsurance is optimal, consistent with the common practice in reality. This study provides suggestions for decision making regarding the crop reinsurance in China. It also provides empirical evidence for the literature on optimal reinsurance from the insurance market of China. This evidence undoubtedly has an important practical significance for the development of China＇s crop insurance.

On the Role of Consumer Preferences in the Coordination among Health Insurers under Regulated Competition

This paper addresses the coordination problem of price and quality setting insurers, arising on the health insurance market under regulated competition, as introduced, for instance, in the Netherlands in 2006. We use an experimental study to gain novel insights on the impact of the uncertainty about consumer preferences on the coordination problem. This fundamental uncertainty implies uncertainty about the identity of the payoff dominant equilibrium, while the risk dominant equilibrium is independent of the state of the world. The experimental results show that insurers are more likely to coordinate on the payoff dominant equilibrium under incomplete information. When insurers face not only strategic but also fundamental uncertainty in the coordination problem, they delay the response to the risk dominant strategy, and persist longer in trying to coordinate on the payoff dominant equilibrium. For the market we study, this implies that the co-ordination under incomplete information will result in consumers paying higher prices, in contrast to the original objectives of the regulated competition.

INSURE技术联合T-piece治疗新生儿呼吸窘迫综合征的临床有效性

目的探讨新生儿呼吸窘迫综合征(respiratory distress syndrome,RDS)采用INSURE技术+Tpiece方法完成治疗的有效性。方法回顾性选取2023年1—12月齐齐哈尔医学院附属第二医院收治的50例RDS患儿的临床资料,根据不同的治疗方法分为对照组(25例,复苏囊+INSURE技术)、研究组(25例,INSURE技术+T-piece方法)。比较两组血氧饱和度最低值、平均吸氧浓度、鼻塞持续气道正压通气应用时间、心率、并发症发生率。结果研究组血氧饱和度最低值为(90.79±3.59)%,高于对照组的(81.33±2.85)%,差异有统计学意义(t=10.319,P<0.05)。研究组平均吸氧浓度、鼻塞持续气道正压通气应用时间、心率优于对照组,差异有统计学意义(P均<0.05)。两组并发症总发生率比较,差异无统计学意义(P>0.05)。结论临床对RDS患儿在治疗期间,将INSURE技术以及T-piece方法进行充分结合,可有效改善患儿的氧合及血气指标,促进病情康复。

Possibilities and Contradictions of Nanotechnology Applications in Preventive Activities Insurer

One effective and proven tool for managing risk is insurance. At the same time, insurers, reinsurers, insurance, and reinsurance brokers in search of the relevant value of their services in the eyes of insured and long-term benefits are increasingly paying attention to the possibilities of nanotechnology. On one hand, insurers see unlimited possibilities of nanotechnology in preventive and repressive activity in relation to losses. The obstacle in this case, for high-tech companies, is stiff competition from companies which are not innovation leaders, but with the necessary influence and power at the international and national market. On the other hand, understanding the reasons for the application of nanotechnology in the conflict prevention activities of the insurer allows him to develop and implement a more flexible strategy for sustainable development of the business.

China’s Aging Population Brings Opportunities for Insurers

The rapidly aging population in China is a great challenge for the country’s development and social security system, while it presents opportunities for insurance companies,according to a recent report by The Boston Consulting Group (BCG) and Swiss Re.

Study of Volatility Stochastic Processes in the Context of Solvency Forecasting for Sri Lankan Life Insurers

The main business of Life Insurers is Long Term contractual obligations with a typical lifetime of 20 - 40 years. Therefore, the Solvency metric is defined by the adequacy of capital to service the cash flow requirements arising from the said obligations. The main component inducing volatility in Capital is market sensitive Assets, such as Bonds and Equity. Bond and Equity prices in Sri Lanka are highly sensitive to macro-economic elements such as investor sentiment, political stability, policy environment, economic growth, fiscal stimulus, utility environment and in the case of Equity, societal sentiment on certain companies and industries. Therefore, if an entity is to accurately forecast the impact on solvency through asset valuation, the impact of macro-economic variables on asset pricing must be modelled mathematically. This paper explores mathematical, actuarial and statistical concepts such as Brownian motion, Markov Processes, Derivation and Integration as well as Probability theorems such as the Probability Density Function in determining the optimum mathematical model which depicts the accurate relationship between macro-economic variables and asset pricing.

Disparities between Explanatory Models of Health Clients, Healthcare Providers and Health Insurer

We present qualitative data from a study in Ghana （2011）, where the National Health Insurance Scheme （NHIS） was introduced to improve access to health care. In 2011 membership enrolment and retention in the scheme was stalling. To obtain better insights into socio-cultural factors that influence utilization of healthcare services and the NHIS this study compared Explanatory Models of healthcare clients with those of primary healthcare providers and the NHIS regarding illness, the need for, the quality of, and the control over heaithcare and health insurance services. We found critical disparities in socio-cultural beliefs and perceptions of healthcare and health insurance between these three stakeholder groups, such as the clients＇ holistic view on illness versus healthcare providers＇ bio-medical view; the clients＇ inter-relational focus in perceiving quality of services versus the providers＇ medical technical focus. These differences are leading to misconceptions, blame practice, poor services, non-adherence and low trust. The findings increase our understanding of clients＇ behavior and that of their service providers. We conclude with key messages for policy leaders and operational managers that can guide them in improving services and facilitating client trust and interest to participate in health insurance and utilize healthcare services.

China Approves Four New foreign Insurers

Four more foreign insurance companieshave been given approval to open branchesor set up joint ventures in China by theInsurance Regulatory Commission.They

Willingness to Pay for Antiretroviral Drugs Covered by Medical Insurance among People Living with HIV in 18 Chinese Cities

Objective Antiretroviral drugs covered by medical insurance have been gradually used by people living with human immunodeficiency virus(PLWH)in recent years in China.This study aimed to analyze their willingness to pay(WTP)for antiretroviral drugs.Methods A mixed-methods study design involving a cross-sectional survey and in-depth interviews was conducted.A cross-sectional survey was performed to collect data on the general characteristics,economic status,antiretroviral therapy(ART)status,and WTP of PLWH in 18 Chinese cities from August 2022 to February 2023.Multivariate logistic regression was used to analyze the factors associated with WTP.Representatives of PLWH were interviewed via in-depth interviews,and the data were thematically analyzed.Results Among the 941 PLWH,271(28.80%)were willing to pay for antiretroviral drugs covered by medical insurance.For basic medical insurance for urban and rural residents,PLWH with the following characteristics were more willing to pay:an educational level of senior high school or technical secondary school,having an undergraduate degree or higher,frequently working away from their hometowns,and homosexual transmission.Off-farm workers and recipients of government medical aid were more unwilling to pay.For basic medical insurance for urban employees,PLWH with the following characteristics were more willing to pay:frequently working away from their hometowns;homosexual transmission;personal annual income≥100,000 CNY;and adverse events of antiretroviral drugs.The main reasons for PLWH’s WTP for antiretroviral drugs covered by medical insurance were that the drugs had fewer adverse events and were easier to administer.The main reasons for PLWH’s unwillingness to pay were financial difficulties and privacy concerns.Conclusion Nearly one-third of PLWH are willing to pay for antiretroviral drugs covered by medical insurance.In the future,PLWH with a high WTP can be guided to use these drugs.

The Extreme Machine Learning Actuarial Intelligent Agricultural Insurance Based Automated Underwriting Model

The paper presents an innovative approach towards agricultural insurance underwriting and risk pricing through the development of an Extreme Machine Learning (ELM) Actuarial Intelligent Model. This model integrates diverse datasets, including climate change scenarios, crop types, farm sizes, and various risk factors, to automate underwriting decisions and estimate loss reserves in agricultural insurance. The study conducts extensive exploratory data analysis, model building, feature engineering, and validation to demonstrate the effectiveness of the proposed approach. Additionally, the paper discusses the application of robust tests, stress tests, and scenario tests to assess the model’s resilience and adaptability to changing market conditions. Overall, the research contributes to advancing actuarial science in agricultural insurance by leveraging advanced machine learning techniques for enhanced risk management and decision-making.

Does community-based health insurance affect lifestyle and timing of treatment seeking behavior?Evidence from Ethiopia

Objectives This paper aims to investigate the effects of enrollment in the Ethiopian community-based health insurance(CBHI)scheme on household preventive care activities and the timing of treatment-seeking behavior for illness symptoms.There is growing concern about the financial sustainability of CBHI schemes in developing countries.However,few empirical studies have identified potential contributors,including ex-ante and ex-post moral hazards.Methods We implement a household fixed-effect panel data regression model,drawing on three rounds of household survey data collected face to face in districts where CBHI scheme is operational and in districts where it is not operational in Ethiopia.Results The findings show that enrolment in CBHI does not significantly influence household behaviour regarding preventive care activities such as water treatment before drinking and handwashing before meals.However,CBHI significantly increases delay in treatment-seeking behaviour for diseases symptoms.Particularly,on average,we estimate about 4-6 h delay for malaria symptoms,a little above 4 h for tetanus,and 10-11 h for tuberculosis among the insured households.Conclusions While there is evidence that CBHI improve the utilization of outpatient or primary care services,our study suggests that insured members may wait longer before visiting health facilities.This delay could be partly due to moral hazard problems,as insured households,particularly those from rural areas,may consider the opportunity costs associated with visiting health facilities for minor symptoms.Overall,it is essential to identify the primary causes of delays in seeking medical services and implement appropriate interventions to encourage insured individuals to seek early medical attention.

China Continues to Be World’s Second Largest Insurance Market

Allianz Group recently released the Allianz Global Insurance Report,predicting that China will consolidate its position as the world’s second largest insurance market in the next decade.The report analyzes the business performance of the global insurance market in 2023 and forecasts the development direction and trends of the global insurance industry in the next decade.2023:A year of significant growth According to the report,in 2023,the global insurance industry grew by an impressive 7.5%,which is the fastest rate since the pre-Global Financial Crisis(GFC)era.

Telematics as a Transformative Agent for the Zimbabwean Auto Insurance Ecosystem

Zimbabwe has witnessed the evolution of Information Communication Technology (ICT). The vehicle population soared to above 1.2 million hence rendering the Transport and Insurance domains complex. Therefore, there is a need to look at ways that can augment conventional Vehicular Management Information Systems (VMIS) in transforming business processes through Telematics. This paper aims to contextualise the role that telematics can play in transforming the Insurance Ecosystem in Zimbabwe. The main objective was to investigate the integration of Usage-Based Insurance (UBI) with vehicle tracking solutions provided by technology companies like Econet Wireless in Zimbabwe, aiming to align customer billing with individual risk profiles and enhance the synergy between technology and insurance service providers in the motor insurance ecosystem. A triangulation through structured interviews, questionnaires, and literature review, supported by Information Systems Analysis and Design techniques was conducted. The study adopted a case study approach, qualitatively analyzing the complexities of the Telematics insurance ecosystem in Zimbabwe, informed by the TOGAF framework. A case-study approach was applied to derive themes whilst applying within and cross-case analysis. Data was collected using questionnaires, and interviews. The findings of the research clearly show the importance of Telematics in modern-day insurance and the positive relationship between technology and insurance business performance. The study, therefore revealed how UBI can incentivize positive driver behavior, potentially reducing insurance premiums for safe drivers and lowering the incidence of claims against insurance companies. Future work can be done on studying the role of Telematics in combating highway crime and corruption.

微管注入PS与INSURE技术治疗早产儿RDS的临床效果评价

目的探讨微管注入肺表面活性物质(PS)技术与气管插管-PS给药-拔管(INSURE)技术治疗≥30周早产儿呼吸窘迫综合征(RDS)的临床效果。方法选取RDS早产儿80例,按随机数表法分为观察、对照2组各40例。对照组采用INSURE技术,观察组采用微管注入(LISA)技术给与PS治疗。比较2组临床疗效、血气指标(PaO_(2)、PaCO_(2)和pH值)、脑血流动力学参数(PSV、EDV和RI)、临床相关指标和出院前病死率及并发症发生率。结果观察组患儿疗效高于对照组(P<0.05)。观察组患儿治疗后PaO_(2)、pH值均高于对照组,PaCO_(2)低于对照组(P<0.05)。2组患儿T0~T3时PSV、EDV、RI水平比较差异无统计学意义(P>0.05)。观察组患儿氧疗时间、插管用时均短于对照组(P<0.05);2组无创通气时间、住院时间及出院前病死率比较差异无统计学意义(P>0.05)。2组患儿治疗期间并发症发生率比较差异无统计学意义(P>0.05)。结论LISA和INSURE技术给予PS技术治疗早产儿RDS,可显著提高临床疗效,改善患儿血气指标。

INSURE策略治疗早产儿呼吸窘迫综合征失败的危险因素分析

新生儿呼吸窘迫综合征(RDS)是因缺少肺泡表面活性物质(PS),导致新生儿肺发育不成熟,引起呼吸功能障碍的严重肺部疾病~([1])。该疾病多发于胎龄在34周以下的早产儿,主要症状为呼吸困难逐渐加重等,严重影响患儿生命健康,具有较高的病死率~([2])。

An Analysis and Prediction of Health Insurance Costs Using Machine Learning-Based Regressor Techniques

One of the most significant annual expenses that a person has is their health insurance coverage. Health insurance accounts for one-third of GDP, and everyone needs medical treatment to varying degrees. Changes in medicine, pharmaceutical trends, and political factors are only a few of the many factors that cause annual fluctuations in healthcare costs. This paper describes how a system may analyse a person’s medical history to display their insurance plans and make predictions about their health insurance premiums. The performance of four ML models—XGBoost, Lasso, KNN, and Ridge—is evaluated using R2-score and RMSE. The analysis of medical health insurance cost prediction using Lasso regression, Ridge regression, and K-Nearest Neighbours (KNN), and XGBoost (XGB) highlights notable differences in performance. KNN has the lowest R2-score of 55.21 and an RMSE of 4431.1, indicating limited predictive ability. Ridge Regression improves on this by an R2-score of 78.38 but has a higher RMSE of 4652.06. Lasso Regression slightly edges out Ridge with an R2-score of 79.78, yet it suffers from an advanced RMSE of 5671.6. In contrast, XGBoost excels with the highest R2-score of 86.81 and the lowermost RMSE of 4450.4, demonstrating superior predictive accuracy and making it the most effective model for this task. The best method for accurately predicting health insurance premiums was XGBoost Regression. The findings beneficial for policymakers, insurers, and healthcare providers as they can use this information to allocate resources more efficiently and enhance cost-effectiveness in the healthcare industry.