Life Insurance Premiums Research Articles

معدل الفائدة الفني وتأثيره علي قسط التامين علي الحياة

ملخص البحث يعتبر معدل الفائدة الفني العنصر الثاني الذي يحسب علي أساسه قسط التأمين علي الحياة , وتنشأ الحاجه الي استخدام معدل الفائدة بسبب طول الفترة بين تاريخ سداد الاقساط وتاريخ استحقاق مبلغ التأمين , وفي هذا البحث تم تناول معدل الفائدة الفني من حيث تعريفة وأهميته في التامين علي الحياة وأثره في تحديد تکلفة عقود التامين علي الحياة سواء بالزيادة او النقصان من حيث تأثيره علي الأقساط الصافية لعقود التامين علي الحياة حسب نوع الوثيقة ومدتها , وطريقة سداد القسط وسن المؤمن علية عند التعاقد , وقد أوضحنا الطريقة التي يتم تحديد معدل الفائدة الفني في مصر وقيمتها وتبلغ 4.25% للوثائق الفردية وتقيمها وکانت قليلة جدا بالمقارنة مع معدلات العائد علي الاستثمار في السوق المصري من ناحية , ومع معدل الفائدة الفني في الأسواق العالمية للتامين مثل السوق الألماني والأمريکي والنمساوي وسوق التامين في المملکة المتحدة من ناحية أخري من حيث قيمة المعدل في هذه الأسواق والجهة المسؤولة عن تحديده والأساس التي تستند علية عند تحديد معدل الفائدة الفني وهو أن يساوي 60% من متوسط اخر 10 سنوات للسندات الحکومية في هذه الأسواق لما تتمتع به من ثبات و درجة مخاطرة أقل , ويجب أن يتم مراجعة المعدل علي فترات زمنية متقاربة . Abstract The technical interest rate is the second element on the basis of which the life insurance premium is calculated, and the need to use the technical interest rate arises due to the long period between the date of payment of premiums and the date of maturity of the insurance amount. In this research, the technical interest rate was studied in terms of its definition and importance in life insurance. And its impact in determining the cost of life insurance contracts, whether by increase or decrease in terms of its impact on the net premiums of life insurance contracts, according to the type and duration of the policy, the method of payment of the premium and the age of the insured when contracting , We have clarified the way in which the technical interest rate in Egypt is determined and its value is 4.25% for individual insurance policies and evaluated, and it was very few compared to the rates of return on investment in the Egyptian market on the one hand, and with the technical interest rate in the global insurance markets such as the German, American, Austrian and insurance market in the United Kingdom On the other hand , in terms of the value of the rate in these markets and the party responsible for determining it and the basis on which it is based when determining the technical interest rate, which is equal to 60% of the average of the last 10 years of government bonds in these markets due to its stability and a lower degree of risk , The technical rate should be reviewed at frequent intervals .

Development of VBA Program for Affordable Premium and Coverage for Lower Income Group in Malaysia

Most people should have insurance to protect themselves from damage and financial instability, especially for those in low income group B40. The objective of this study is to suggested affordable life insurance premium for the B40 group using equivalence principle method. The study's findings show that group can choose between two affordable life insurance policies is either policy 1 or policy 2. Next objective is to create a user-friendly calculator that displays life insurance and Takaful policies available in Malaysia based on the B40 monthly household income. Microsoft Excel and Visual Basic for Application (VBA) are used to accomplish this objective. It hoped that this user-friendly interface developed in this study may assist low-income earners in identifying a suitable range of premiums they may afford to pay, thereby increasing the likelihood of purchasing life insurance and Takaful.

PENENTUAN PREMI ASURANSI BERJANGKA LAST SURVIVOR UNTUK KASUS DUA ORANG TERTANGGUNG

Insurance is an agreement between the insurance service company and the policyholder as the insured party. The insured party will pay the premium as agreed upon to the insurance service provider. Insurance in Indonesia has developed rapidly, one of which is the last survivor term insurance. In this study, the determination of the last survivor insurance premium with a tenor of 10 years for the case of two insured persons aged 70 and 20 years respectively using the Indonesian mortality table in 2019. The first case, the two insureds are male and the second case, the two insured are female. The determination of the last survivor life insurance premium is completed by first determining the cash value of the annuity and the single premium. Based on the results obtained, the value of the premium depends on gender and the interest rate. Where, men pay premiums more expensive and the greater the interest rate, the smaller the value of the premium to be paid

Information technology and insurance development in Sub-Saharan Africa

The study examined the relationship between information technology and insurance development in 40 sub-Saharan African countries during the period 2000-2017. The study employed System Generalised Method of Moment for the estimations. Life insurance premiums, non-life insurance premiums and total insurance premiums are used to measure life insurance, non-life insurance and total insurance, respectively. The information technology is measured by mobile phone, fixed telephone and Internet penetrations. The study found that the Internet promotes non-life insurance while its effect on life and total insurance is insignificant. The mobile phone produced a negative effect on life insurance, non-life insurance and total insurance. However, fixed telephone significantly contributed to life insurance, non-life insurance and total insurance. Based on these findings, there is a need for insurers to encourage their client to use information technology tools for insurance activities and also increase their interaction with their customers.

THE INFLUENCE OF REINSURANCE RATE, LOAN INTEREST RATE AND BANK'S FEE BASED INCOME AGAINST THE PREMIUM RATE ON CREDIT LIFE INSURANCE (CASE STUDY: CREDIT LIFE INSURANCE’S POLICY HOLDER OF PT INDOSURYA LIFE IN 2018)

This research has purposes to learn further about the impact of reinsurance rates, loan interest and fee-based income towards premium rates on credit life insurance. The unit of analysis was 50 credit life insurance policy holders at PT Indosurya Life throughout 2018. The independent variables that used in this research are reinsurance rates, loan interest and fee based income. While the dependent variable is premium rate on credit life insurance. The sample collected method was taken by saturated sampling. Researchers took the entire population as a sample where the number of samples used were 50 policy holders from credit life insurance which used premium rates and types of effective loan interest for 40 years of age with 5 years of insurance period. The analytical method used was multiple regression analysis and hypothesis test which is done by t-test. And according to the rdata analysis result, loan interest and fee-based income had a positive and significant affect towards credit life insurance's premium rates. Meanwhile, the reinsurance rate variable did not related to credit life insurance's premium rate. It is very recommended to PT Indosurya Life to increase the premium rate on its credit life insurance, so that will increase its Fee Based Income aswell.

Closed-form solutions for an explicit modern ideal tontine with bequest motive

In this paper I extend the work of Bernhardt and Donnelly (2019) dealing with modern explicit tontines, as a way of providing income under a specified bequest motive, from a defined contribution pension pot. A key feature of the present paper is that it relaxes the assumption of fixed proportions invested in tontine and bequest accounts. In making the bequest proportion an additional control function I obtain, hitherto unavailable, closed-form solutions for the fractional consumption rate, wealth, bequest amount, and bequest proportion under a constant relative risk averse utility. I show that the optimal bequest proportion is the product of the optimum fractional consumption rate and an exponentiated bequest parameter. I show that under certain circumstances, such as a very high bequest motive, a life-cycle utility maximisation strategy will necessitate negative mortality credits analogous to a member paying life insurance premiums. Typical scenarios are explored using UK Office of National Statistics life tables.

Pricing a Combined Life and Health Insurance with Level Premiums and Varying Benefits

The growing interest in insurance poses a threat to insurance companies. As the number of individuals seeking insurance coverage increases, the number of individuals adversely selecting the insurer also increases, which can lead to the insurance product being unprofitable. Thus, this study explores designing an insurance product – a combined life insurance and health insurance product that will reflect the actual claims of an individual to his/her policy – that will hopefully help prevent unprofitability of the insurance product. This is done by applying incentives and penalization, or the bonus-malus system, to the insurance benefit while leaving the premium constant. Assuming that premiums for life insurance and health insurance are constant, transition and pricing models are derived. Considering two forms of combination of life and health insurance: a combined life and hospitalization income insurance and a combined life and medical insurance, we illustrate the derived model assuming Makeham distribution for life insurance claims and Poisson distribution and gamma distribution for the hospitalization income insurance and medical insurance claims, respectively. The proposed design gives a new framework for combining life and health insurance, as well as a methodology for combining other types of insurances.

SETTLEMENT OF DEFAULTS IN THE LIFE INSURANCE POLICY BETWEEN THE INSURER AND THE INSURED

When the policy holder or insurance participant or the insured experiences a disaster or suffers a loss or damage as stated in the contract, the insured has the right to file an insurance claim. The recipient of this insurance is not only the insured whose name is listed as the policy holder of the insurance company but can also be another person appointed directly by the insured. The formulation of the problem in this study is the Default in the Life Insurance Policy between the Insurer and the Insured, howSettlement of Defaults in Life Insurance Policies Between the Insurer and the Insured and What are the Legal Consequences for Settlement of Defaults in a Life Insurance Policy between the Insurer and the Insured. The purpose of this research is to analyze Default in a Life Insurance Policy between the Insurer and the Insured, To Analyze Settlement of Defaults in Life Insurance Policies Between the Insurer and the Insured To Analyze Legal Consequences Settlement of Defaults in Life Insurance Policies Between the Insurer and the Insured.This research method is normative legal research. The conclusions in this study have answered the problems that arise, namely:Default in a Life Insurance Policy between the Insurer and the Insured that a life insurance agreement is made between the policy holder and the insurer, with the consequence that the policy holder pays the premium and the insurer provides risk protection to the policy holder and/or the insured within a certain time as stipulated in the agreement. Default can be done by the policyholder, one of which is by not paying life insurance premiums until the grace period ends.Settlement of Defaults in Life Insurance Policies Between the Insurer and the Insured that The insurer and the insured binding themselves in the insurance agreement must be in accordance with the provisions of the applicable laws and regulations, which are contained in Article 1338 Paragraph (1) of the Civil Code. This provision states that when the agreement has been agreed by both parties, then the agreement will apply as a law that will bind the parties therein. Because of lawSettlement of Defaults in Life Insurance Policies Between the Insurer and the Insured that if the premium is not paid by the policyholder, the life insurance agreement can be canceled by law and the policy will be canceled or called lapsed, namely the termination of insurance coverage as a result of not paying premiums until the insurance contract period ends and the premiums that have been paid will not be returned.

Annual Premium of Life in Insurance with Uniform Assumptions

This Study discusses life insurance for life with a uniform assumption method. The purpose of this study is to calculate the annual premium that must be paid by life insurance participants. This research was conducted at the General Insurance Group company, which is located on the street Arifin Ahmad. To determine the annual life insurance premium, the interest rate and discount factor, initial lifetime annuity, single premium, and the annual premium. After doing the research, the results of the calculation of the annual premium for life insurance for life using uniform assumptions for each participant life insurance are different. The amount of annual life insurance premiums uses a uniform assumption that is smaller than the annual life insurance premiums obtained from insurance companies.

Customer Segmentation for Life Insurance in Iran Using K-means Clustering

Concerning life insurance, penetration rate is one of the main goal of every developed insurance industry. In this sense systematic marketing is a significant component in strategic plan of insurance companies. To achieve the goal insurers need to group their client into different groups in which some common features are shared and people demonstrate a similar pattern. This paper utilizes K-means clustering as an unsupervised learning algorithm in order to divide customers into number of clusters. The clusters are constructed based on two independent variables namely; car and life insurance premiums. Then the descriptive statistics of other determining features are provided with which the most willing group in purchasing life insurance is presented.

The influence of climate change on the life insurance in the EU: A panel data approach

The financial sector, as one of the most sensitive economic sectors, is alert to all trends and changes in the environment. The aim of the article is to study the impact of climate change on the life insurance market using panel data from 28 countries of the European Union (EU) for the last 9 years. This study is based on a panel model, where the amount of premiums under life insurance contracts is defined as a function of the fundamental factor of climate change - greenhouse gas emissions. According to empirical findings, an increase in greenhouse gas emissions per thousand tons leads to an increase in the amount of life insurance premiums by 0.1786 million euros. It has also been found that an increase in greenhouse gas emissions per thousand tons leads to an increase in deaths in the European Union by 1.0442 people, and these consequences are statistically significant. In general, our results suggest that the life insurance market as well as the non-life insurance market is dependent on climate change. The empirical results of this study provide valuable insight into how greenhouse gas emissions affect mortality in the European Union.

The Annual Premium of Life Insurance on The Joint-Life Status based on The 2011 Indonesian Mortality Table

Life insurance is insurance that protects against risks to someone's life. Joint Life Insurance is insurance where the life and death rules are a combination of two or more factors, such as husband-wife or parent-child, and if the first death occurs, then the premium payment process is stopped. The annual premium is the premium paid annually. In this study, the annual premium is calculated continuously with the equivalence principle based on the 2011 Indonesian Mortality Table. The calculation shows that the amount of annual premiums for 2 (two) and 3 (three) people is not much different. The factors that influence the annual premium amount are the duration insurance period, age at signing the policy, interest rates, life chances, force of mortality, and the number of benefits.

The effect of geopolitical risks on insurance premiums

This article deals with the estimation of the risk‐insurance nexus. We specifically examined the effect of geopolitical risk on insurance premium in a panel of 18 countries, while controlling for the effect of real income. Second‐generation econometric methods were employed for this purpose, and the results provided strong evidence of a positive impact on insurance premiums by geopolitical risks. We specifically found that the impact of geopolitical risks on nonlife insurance premium is higher than the impact on life insurance premium. Real income was also found to have a significantly positive effect on insurance premiums, and the impact on nonlife insurance premium was similarly larger than the impact on life insurance premium. On the basis of income elasticity, we found that insurance has the semblance of a luxury good, and on the basis of the panel causality tests, we confirmed the feedback hypothesis. We therefore conclude that exposure to geopolitical risks raises insurance premiums either as a result of increased insurance demand to hedge against geopolitical uncertainty or as a result of uncertainty tax factored into insurance premiums in unstable environments.

Insurance and economic policy uncertainty

Just as the world has witnessed the increased importance of the insurance sector over the past few decades, it has also witnessed a sharp rise in risks and uncertainties. Surprisingly, studies analyzing the relationship between economic policy uncertainty and the insurance sector are almost non-existent. Another major limitation of insurance literature is the choice of methodology. Most studies on the insurance sector do not take into consideration issues of heterogeneity and cross-sectional dependence, and are therefore subject to errors. To address the identified gaps, this research investigates the impact of economic policy uncertainty on insurance premiums in a panel of 15 countries over the period 1998–2016 by employing heterogeneous panel estimation techniques with cross-sectional dependence. The Durbin-Hausman cointegration tests of Westerlund (2008) confirm that a long-run relationship exists between the variables. Findings from the error correction based panel estimations show that the insurance sector is not immune to the effects of economic policy uncertainty. Economic policy uncertainty raises insurance premiums both in the short and long run, although the long-run impact is greater than the short-run impact. In addition, economic policy uncertainty exerts a bigger influence on non-life insurance premium than on life insurance premium, indicating that the economic risks covered by non-life insurance are more sensitive to uncertainty than the mortality and longevity risks covered by life insurance. Our findings further show that national income, education, population, financial development and institutional quality all raise insurance premiums, while inflation lowers insurance premiums.

Forecasting Life Insurance Premiums and Insurance Penetration Rate in Uganda

Forecasting Life Insurance Premiums and Insurance Penetration Rate in Uganda

The Effects of Insurances, Pensions and Mutual Funds on Economic Growth

Earlier studies on the impact of the insurance sectors activities on economic growth have largely failed. To examine the financial development market interaction of pensions and mutual funds linkages, through which insurance assets affects economic growth. This study re-examines the impact of life insurance premium volume, non-life insurance premium volume, insurance company assets, pension fund assets and mutual fund assets on economic growth. Using panel data of 33 countries over the period 2000-2016. The study applied the Autoregressive Distributed Lag (ARDL) model in panel setting using the PMG (Pooled Mean Group) and MG (Mean Group) estimators in this analysis. The study findings indicate that cointegration exists among all series and that insurances and mutual funds stimulate economic growth in both the short and long run.

MENENTUKAN FORMULA CADANGAN PREMI ASURANSI JIWA LAST SURVIVOR MENGGUNAKAN METODE NEW JERSEY

Last survivor life insurance is a type of life insurance for two or more people, with premium payment up to the last death of the insured and at that time also provide the benefit from the insurer. The purpose of this research was to determine the formula for last survivor life insurance premium reserve using New Jersey method. To calculate the reserve: first we determine the benefit, and then the annuity and finnaly the annual premium. The premium reserve value in the New Jersey method on first year is zero. The premium reserve in the New Jersey method starts in the second year, for years, with where n represents the term of the insurance participant’s contract.

Awareness and Perception Regarding Tax Saving Instruments among Teachers of Higher Education

The study attempted to know the awareness and perception regarding various tax saving instruments available to save the tax to the teachers of higher education. The study conducted to determine the tax-saving investment options which are preferred to save tax and what the factors are considered before making investment decisions. Descriptive statistics used to analyze the data collected through the 347 respondents of the Ghaziabad region. The study found most of the teachers of higher education are availing deduction of fees of their wards under section 80 C. investment in PPF and Life insurance premium are also found most used instruments for availing deduction of 80 C. The teachers of higher education are well aware of the various deductions, reliefs, and rebates available as per the Indian income tax act. They prefer those options of investment which are having low risk, high returns, and full tax benefits. It is also found people are not investing in NPS though there is an option to save extra tax by investing up to Rs. 50,000. That is due to the lack of awareness of NPS. The medical deduction is also underutilized. So, the study recommends to invest in NPS and increase the amount of expenditure on health insurance to reduce the tax liability of the teachers of higher education.

Insurance and inequality in Sub‐Saharan Africa: policy thresholds

AbstractIn this study, we examine how insurance affects income inequality in Sub‐Saharan Africa, using data from 42 countries during the period 2004–2014. Three inequality variables are used, namely: the Gini coefficient, the Atkinson index and the Palma ratio. Two insurance premiums are employed, namely: life insurance and non‐life insurance. The empirical evidence is based on the Generalised Method of Moments (GMM). Life insurance increases the Gini coefficient and increasing life insurance has a net positive effect on the Gini coefficient and the Atkinson index. Non‐life insurance reduces the Gini coefficient and increasing non‐life insurance has a net positive effect on the Palma ratio. The analysis is extended to establish policy thresholds at which increasing insurance premiums completely dampen the net positive effects. From the extended analysis, 7.500 of life insurance premiums (percentage of GDP) is the critical mass required for life insurance to negatively affect inequality, while 0.855 of non‐life insurance premiums (percentage of GDP) is the threshold required for non‐life insurance to negatively affect inequality. Policy thresholds are provided at which insurance penetration decreases income inequality in Sub‐Saharan Africa.

PERHITUNGAN PREMI ASURANSI JOINT LIFE DENGAN MODEL VASICEK DAN CIR

Premium is a sum of money that must be paid by insurance participants to insurance company, based on insurance contract. Premium payment are affected by interest rates. The interest rates change according to stochastic process. The purpose of this work is to calculate the price of joint life insurance premiums with Vasicek and CIR models. The price of a joint life insurance premium with Vasicek and CIR models, at the age of the insured 35 and 30 years has increased until the last year of the contract. The price of a joint life insurance premium with Vasicek model is more expensive than the premium price using CIR model.