Determinants Of Premiums Research Articles

Modeling of Car Insurance Premiums Using the Bayes Method with Poisson and Exponential Distributions

Car insurance is included in the general insurance category. Determination of general insurance premiums can be done through various approaches, one of which is the Bayes method used in this study. The Poisson distribution is chosen to model the frequency of claims, while the Exponential distribution is used to model the amount of claims. Insurance premiums are calculated by multiplying the expected frequency of claims by the expected amount of claims. Based on the results of the analysis of car insurance data using the Bayes method, it was found that the highest premium rates were for Mercedes brand vehicles, while the lowest rates were for Saab brand vehicles. The results of this calculation can be used by insurance companies as a reference in managing car insurance reserve funds.

Community-Based Disaster Insurance for Sustainable Economic Loss Risk Mitigation: A Systematic Literature Review

This systematic literature review (SLR) explores the role of community-based catastrophe insurance (CBCI) as a tool for sustainable economic loss risk mitigation. Utilizing bibliometric analysis and a literature review, this study aims to reveal the methods employed in CBCI schemes from a novel perspective, highlighting their effectiveness in mitigating catastrophe risks. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology was employed to systematically collect and analyze articles sourced from the Scopus, ScienceDirect, and Dimensions databases. The findings provide a comprehensive summary of the CBCI implementation, including various considerations such as risk-sharing mechanisms, premium determination, and policy frameworks. This research offers a fresh perspective on CBCI as a sustainable approach to catastrophe risk mitigation, contributing valuable insights to policymakers, practitioners, and researchers interested in community resilience and disaster risk management.

Willingness to Pay for Cattle Insurance in Nepal: A Double-Hurdle Model Perspective

Since the adoption of the Crop and Livestock Insurance Directives in 2013, the adoption of livestock insurance has gained popularity in Nepal. In the eight years since implementation, adoption rates have remained low, even with 80% government premium subsidies. This study uses a double-hurdle model for quantitative analysis and focuses on the determinants of willingness to pay (WTP) for cattle insurance. The research identifies significant factors influencing insurance adoption decision, including positive impacts from farmer’s age, education, livestock loss history, awareness of insurance, dairy farm income, number of cattle, and loan access. However, male gender, extensive cattle rearing experience, and larger households negatively affect willingness to insure. A number of factors affect premium determination, including age, size of household, livestock loss, off-farm income, number of cattle, and loan accessibility; on the other hand, factors that have a negative impact on premium levels include breed type, marital status, and revenue from dairy farms. According to the findings, the annual WTP for cattle insurance among dairy farmers varies from $48 to $71 (NRs. 6315-9341), with an average of $58 (NRs. 7631). Interestingly, the majority of farmers demonstrate their commitment to risk management by accepting premiums equal to 5% of the value of the cattle. The research contributes to understanding livestock insurance premiums in developing countries, specifically in Nepal, and suggests a scope for extending insurance programs, while also noting a gap in awareness among dairy farmers regarding government subsidy programs.

Premium Estimation of General Insurance Contracts Using Buhlmann Credibility Model

Insurance coverage is reliant on appropriate premium determination, a focus addressed in this study through the application credibility theory. The aim was to compute short-term insurance premiums by leveraging authentic data from general insurance contracts as published in the IRA annual reports spanning from 2013 to 2021. The study employed the Buhlmann credibility model to derive net credible premiums for 13 non-life insurance contracts, assuming constant changes in business volumes. The estimation of credibility premiums was conducted by initially calculating within and between-portfolio variance with an aim of determining these premiums through linear estimation approach with the help of the credibility premium formula. The results revealed consistent credibility factors across all contracts, although other influencing factors were neglected. Therefore, it was highly recommended that an appropriate credibility model alongside other factors that influence premium estimation be considered to enhance the accuracy of premium estimates. Moreover, embracing heterogeneity over homogeneity is advised to better reflect individual risk profiles. The research underscores the importance of effective premium determination in insurance firms, as premiums constitute their primary revenue. Stakeholders, including insurers and regulators, are encouraged to integrate this approach and other relevant factors to enhance pricing accuracy and overall sector practices.

Property risk assessment and dynamic premium pricing based on ARIMA

This study aims to improve the efficiency of insurance underwriting decisions and assess community risks, and constructs a dynamic premium pricing model through the ARIMA model. In-depth analysis of historical data provides quantitative and optimal support for insurers to address premium setting and underwriting decision challenges. The results show that the model can predict future risks and losses, facilitate risk classification and premium determination. The classified statistical method analyzes the frequency and time correlation of extreme meteorological events, and provides basis for insurance policy adjustment. Research provides more accurate and dynamic premium pricing and underwriting decision-making tools, simplifies the risk assessment process, and is conducive to insurance market stability and resource optimization, service optimization and long-term market stability.

Product differentiation in the fruit industry: Lessons from trademarked apples

AbstractWe derive price premiums for patented or trademarked apple varieties, also known as “club apples,” compared to open‐variety apples. We use an expansive retail scanner dataset, along with unique data on apple taste characteristics, to estimate monthly club apple premiums for 2008–2018. We find that club apple premiums are around 29% and have consistently decreased from 35% in 2008 to 22% in 2018. Positive club apple premiums relate to consumers' preferences for juicier, more acidic, and sweeter apples. We do not find evidence that consumers place value on the exclusivity of purchasing more expensive and limited varieties. Hence club premiums exist in the market by meeting the demand of consumer segments for apples with distinct taste attributes rather than replacing the demand of traditional consumers who prefer open varieties. We use a vector error correction framework to find short‐run and long‐run determinants of club apple premiums. In the short run, the sales of club varieties may positively associate with the sales of open varieties, given the premium and cost factors. However, in the long run, there is a negative cointegrated relationship between club apple sales, open apple sales, and club apple premiums; and an increase in club apple sales is adversely related to the open apple sales and club premiums. The high initial premiums of protected club varieties have provided incentives for the development of uniquely differentiated apple varieties, while in the long term as production expands, premiums decrease making club varieties less expensive for consumers [EconLit Citations: L66, Q11].

Research on the Impact of Internet Sales on the Rate Determination of Commercial Insurance in China

In the dynamic landscape of the Chinese commercial insurance market, the escalating prevalence of Internet sales has triggered a comprehensive exploration into the intricacies of premium determination. This study delves into the multifaceted influence of Internet sales on commercial insurance rates, employing a blend of theoretical analysis and empirical investigation. The research unveils substantial effects on market competition, consumer behavior, and strategic decisions of insurers. The insights derived not only contribute to the refinement of regulatory frameworks but also offer valuable guidance to insurers, empowering consumers in navigating the evolving complexities of commercial insurance in China.

Determination of Mount Eruption Insurance Premiums in Indonesia Based on Collective Risk and Level of Risk Spread

Volcano eruption insurance is an insurance product that provides financial protection to policy holders who experience losses due to volcanic eruptions. This insurance product is still rarely developed in Indonesia, even though this country is very vulnerable to natural disasters. Therefore, this research aims to carry out a simulation of determining volcanic eruption disaster insurance premiums based on collective risk and the level of risk distribution. The data used in this research is the frequency of events and economic losses due to volcanic eruptions. Event frequency and loss data are analyzed using a collective risk model. Apart from that, determining insurance premiums also takes into account loading factors and the level of risk distribution from volcanic eruption disaster data. From the results of the analysis, it was found that natural disaster insurance premiums had increased, along with an increase in the loading factor provided. In addition, insurance premium expenses are influenced by the collective risks faced by customers. The greater the collective risk faced, the greater the insurance premium that customers must bear. Based on the results of the estimates carried out, it is hoped that this research can provide an overview to the Indonesian government in estimating the Mount Meletus insurance scheme. Meanwhile, insurance companies can get an idea of determining insurance premiums according to conditions in the field.

Multifactor conditional equity premium model: Evidence from China's stock market

There is mixed evidence of a positive relationship between the stock market risk and return. We reexamine this critical implication of asset pricing theory using fresh data from China's stock market, which is largely segmented from the rest of the global financial market. Using formal variable selection methods and a comprehensive set of predictor variables, we identify conditional market variance, scaled market prices, and inflation as crucial determinants of equity premiums. The estimated simple risk-return relationship exhibits downward omitted variable bias, which underlines the importance of considering multiple factors to explain the variation in equity premiums. We cannot wholly attribute the three-factor conditional equity premium model to data mining, as Guo, Sanni, and Yu (2022) select the same model for the U.S. stock market. These findings challenge existing asset pricing models and provide valuable guidance for future theoretical research.

Analyzing Size of Loss Frequency Distribution Patterns: Uncovering the Impact of the COVID-19 Pandemic

This study delves into a critical examination of the Size of Loss distribution patterns in the context of auto insurance during pre- and post-pandemics, emphasizing their profound influence on insurance pricing and regulatory frameworks. Through a comprehensive analysis of the historical Size of Loss data, insurers and regulators gain essential insights into the probabilities and magnitudes of insurance claims, informing the determination of precise insurance premiums and the management of case reserving. This approach aids in fostering fair competition, ensuring equitable premium rates, and preventing discriminatory pricing practices, thereby promoting a balanced insurance landscape. The research further investigates the impact of the COVID-19 pandemic on these Size of Loss patterns, given the substantial shifts in driving behaviours and risk landscapes. Also, the research contributes to the literature by addressing the need for more studies focusing on the implications of the COVID-19 pandemic on pre- and post-pandemic auto insurance loss patterns, thus offering a holistic perspective encompassing both insurance pricing and regulatory dimensions.

Determining Pure Premium of Motor Vehicle Insurance with Generalized Linear Models (GLM)

Motor vehicle insurance guarantees protection, coverage, and compensation for the risks of accidents, damages, and loss of motor vehicles. It is crucial for companies to determine appropriate insurance premium rates as a preventive measure to avoid difficulties in meeting claims filed by policyholders. This research aims to determine the pure premium of motor vehicle insurance using the Generalized Linear Models (GLM) method, which utilizes the concept of a general linear relationship between independent variables and the dependent/response variable, as well as identifying motor vehicle characteristics that influence the determination of pure premiums. The data used in this study is from Swedish motor vehicle insurance. The research aims to determine the pure premium in the data by modeling claim frequency using the Poisson distribution and claim severity using the Gamma distribution, depending on the significantly influential characteristics. The Maximum Likelihood Estimation method is employed for parameter estimation. After conducting the research, the estimated parameters , , and the pure premium of motor vehicle insurance are found to be 35,572,223.27 kr, with the characteristics influencing the pure premium being the distance traveled by the vehicle, the insured's geographic zone, and the no-claim bonus.

Measurement of Market Risk Premiums: A Sectoral Analysis on BORSA Istanbul

The determination of market risk premium is often a problem for academics and practioners when applying Capital Asset Pricing Model (CAPM). This study intends to measure the market risk premiums (MRP) in the sectors of Borsa Istanbul. The monthly data are extracted from Reuters Database for the period of 2016-2021 for the seventeen sectors of Borsa Istanbul. The whole sampling period is devided into two sub-periods based upon the results of Cusum-Squared test statistics showing a structural break with the Covid-19. The emprical results reveal that the market risk premium on BIST100 is -0.7% with a volatility of 0.3% in the pre-Covid-19 period while the market risk premium on BIST100 is -0.21% with a volatlity of 0.23% post-Covid-19 period. The findings show that a significant increase in market risk premiums and volatilies post-Covid-19 era compared to the pre-Covid era. More, the market risk premiums and their volatilies are estimated by utilizing ARIMA model for the 2022-2024 period. The estimates point even higher market risk premiums and volatilies in the near future.

Cross-border mergers and acquisitions by emerging country banks: What do acquisition premiums tell us?

Our knowledge of international expansion motives and strategies of emerging country banks (ECBs) is limited. Using a worldwide sample of cross-border mergers and acquisitions (CBMAs) and a mixed model, we explore firm- and country-level determinants of acquisition premiums. We show that the effects of target bank and target country characteristics on premiums are contingent on the acquirer’s home country: emerging vs. advanced. More specifically, compared to advanced country acquirers, ECBs pay lower premiums for targets that are: (i) more efficient; (ii) offering better functional diversification opportunities; and (iii) based in markets with higher growth prospects or better institutional development levels. Furthermore, state-owned ECBs pay higher premiums. Our findings suggest that CBMAs undertaken by ECBs might not be motivated by competence-enhancing strategies while being less sensitive to the target country’s institutional development.

Determination of Community-Based Health Microinsurance Premiums Based on Health Costs

Low-income households are faced with the financial risk of paying large medical bills when a member of the household falls ill. This health-related risk can affect household welfare because meeting medical expenses has the potential to reduce income capacity. Community-based health insurance is seen as one mechanism for vulnerable low- and middle-income households to overcome barriers and to improve access to health care and financial protection. This research was conducted to determine the calculation of community-based health microinsurance premiums based on health costs and determine the average willingness to pay insurance premiums. The determination of the premium is calculated based on the pure premium and other costs. Data obtained based on surveys and data provided by health facilities. Based on the results of the research, the pure individual premium is IDR 92,297.12 per year. The total individual premium calculated based on pure premium and other costs is IDR 275,256.80 per year. If the premium is paid monthly, a premium of IDR 22,938.07 per month will be obtained. Then the average value is obtained WTP or willingness to pay IDR 38,368.42 per month. The average value of the willingness to pay is greater than the total monthly health micro insurance premium that has been determined.

Determination of the Disability Premium there is Life Insurance with Annual Payment for Type Benefit Waiver of Premium

When there is a work accident that results in someone becoming disabled or sick, it often leads to termination of employment (layoff) for reasons of productivity. A person who has a chance of having a work accident needs to buy a disability life insurance policy to reduce the financial losses that occur. One type of disability benefit in life insurance is the waiver of premiums. The purpose of this study is to determine the amount of annual disability premium that will be paid to be able to benefit from the type of benefit waiver of premium on dual-purpose life insurance either manually or using Excel Visual Basic for Application. The results showed that the calculation of annual premiums can be generalized that the older the insured, the greater the premium paid. Meanwhile, the greater the policy term, the smaller the premium paid.

Bühlmann's Credibility Model with Claims of Negative Binomial and 2-Poisson Distribution

One of the premium determination techniques is to use credibility theory. In this study, a credibility premium determination model was derived with the best accuracy approach in the form of Bühlmann’s credibility premium. The claim data is assumed to have a Negative Binomial and 2-Poisson distribution. Bühlmann's credibility premium formula is given explicitly for these two data distributions. The obtained model is also applied to the correct data following these distributions. From the simulation results, it is obtained that the premium values are very close in value so that both models can be applied to the data and have a high level of credibility because they have a high credibility factor value.

Issues of Improving the Methodology of Agricultural Damage Assessment

The main role in the agricultural insurance program is damage assessment, which is very peculiar due to its specificity. Damage assessment is carried out by determining the percentages of loss, final real production and expected real production according to the insurance conditions of the plant damaged by insurance risks, this process is carried out by an agro expert. The damage assessor evaluates the deviation of the condition of the vegetative and generative parts of the plant, fruits from the standard/initial condition as a result of injuries caused by the insured risk. The assessment is done only to determine the percentage of quantitative and not qualitative losses. The purpose of determining the percentage of damage is to determine by how much the percentage of the crop/plants that existed before the occurrence of the insured risk occurred/will occur, compared to what it was before the occurrence of the risk. Perfection of damage assessment methodology in the agricultural insurance program is vital for the farmer. The specifics of properly conducted agro loss assessment will contribute to the development of agriculture and agro-insurance. As the research shows, a lot of work is needed to regulate agricultural losses. In order to perfect the methodology of damage assessment, it is necessary to conduct practical studies and to certify agricultural experts. Furthermore, it is necessary to share the world experience for the development of agro-insurance, taking into account the local specifics; Moreover, the perfection of the necessary agricultural insurance state program for correct assessment of risks, adequate determination of insurance premium and full compensation of financial losses of farmers are necessary; It is quite important to create and to improve damage assessment methods for different cultures individually. Keywords: Insurance, farmer, damage, appraisal, expert, agriculture.

A quantile-based analysis of risk-return dynamics in the South African equity market

ABSTRACT This paper employs quantile autoregression to investigate the influence of ‘market size’ and ‘industry’ effects on the South African equity market volatility response to return shocks. It is now well documented that equity market volatility exhibits asymmetric response to positive and negative return shocks. This paper provides empirical evidence which shows that the South African equity market asymmetric volatility response is significantly a large company phenomenon and with the exception of the Resources 10 and Financials 15 Indices, there is generally no volatility asymmetric response heterogeneity at the sector level. These results have important implications for investors and fund managers in relation to portfolio construction, risk management and optimal equity risk premium determination.

Simulasi Perhitungan Premi Asuransi Kesehatan dan Jiwa pada Penderita Covid-19 yang Dipengaruhi Model Penyebaran Penyakit Menular SIDRS

Determination of health and death insurance benefits according to the needs of policyholders is very important to determine from the beginning of making an insurance policy, especially for insurance that takes over the risk of being infected with the COVID-19 virus. Several factors that must be taken into account in determining the amount of benefits and premiums due to COVID-19 are the human population factor that is susceptible, infected and death in the SIDRS infectious disease spread model. In this study, the influence of these three factors on actuarial calculations is examined in more depth to produce an appropriate premium determination formula by taking into account two payment schemes in lump sum and annuity. From the simulation results by applying data on COVID-19 cases in Indonesia to determine the parameters of the SIDRS model, it is concluded that the premium with an annuity benefit payment scheme is smaller than the premium with a lump sum benefit scheme. Furthermore, it is also concluded that if the population of policyholders increases, the premium price will also be lower.

Customers Satisfaction on Robots, Artificial Intelligence and Service Automation (RAISA) in the Hotel Industry: A Comprehensive Review

Due to the 4th Industrial Revolution, Artificial Intelligence and other internet technologies such as RAISA (Robots, Artificial Intelligence and Service Automation) have been adopted in various industries, including the hospitality and tourism industry. As the industry traditionally offers services through manual labor force, more companies adopt RAISA through a commercial service in the form of chatbots, delivery robots, robot concierge, conveyor restaurants, self-service information/check-in/check-out kiosks, and many others. The current academic resources mainly focus on customer perception or evaluation of robots themselves, and few studies link robot services with customers’ overall experience of hospitality services. This study aims to evaluate the current status of RAISA studies in the hotel industry and propose directions for future research. Thirty-seven articles were identified from Google Scholar. These articles were reviewed from four perspectives, namely, journal/year distribution, methodology, research context, theoretical foundation. Findings reveal that most studies on RAISA in the hotel industry focus on RAISA’s impacts on the hotel industry, RAISA service quality, customer acceptance of RAISA service, customer satisfaction and factors influencing Customers’ Satisfaction on RAISA Service and quantitative approach is the dominant research method. To this end, five research directions cover outstanding themes as follows: 1) strategic assessment of RAISA performance, 2) hotel financial impacts on RAISA employment, 3) customers’ satisfaction and RAISA service quality, 4) macro environment impacts on RAISA in hotels, and 5) premium determinants on customers’ acceptance on RAISA.