- ItemDeterminants of insurance penetration and density in under developed, developing and developed countries(Strathmore University, 2016) Otieno, Dansol ObondoThe need for greater Insurance penetration in both life and non-life segments has been underscored by economic surveys . Insurance penetration has remained low not only in Kenya but in Africa as a whole and other under developed and developing countries. This study is set out to establish factors causing the low Insurance uptake, the challenges faced by the insurers in marketing their products and subsequently identify strategies the Insurance Companies can adopt to enhance Insurance uptake. This is through the studying the relationship more so between Insurance Penetration and Density and their determinants in developed, developing and under developed countries, with the aim of finding out if there exists a relationship and why this relationship holds. This is to help in understanding why developed countries with high insurance penetration and low market shares among firms, both competing and non-competing are doing better than those with the inverse of this relationship more so under developed countries. Secondary data was collected via financial reports of insurance firms and insurance performance within countries via the regulatory bodies . In as much as there are various obvious ways of improving insurance penetration in countries, this study highlights that various insurance policies and regulations goveming the insurance industry have an effect on the performance within the insurance firms in as much as the mechanisms to promote rapid insurance penetration do exist, by studying the above phenomena.
- ItemThe financial implication of longevity improvements on the liabilities of annuity providers.(Strathmore University, 2016) Kosgei, Winnierose WDifferent countries around the world have experienced and improvement in mortality over the years. This improvement can be attributed to factors such as technological advancements in the medical field and improved living standards among others. This is generally a good thing , but for life insurance companies and defined benefit pension schemes that provide benefits in form of annuities, there lies the risk of longevity. Which is the risk that people will live longer than expected requiring them to be paid benefits for longer periods . This paper studies the implication of changes in Kenyan mortality on the value of an annuity. It focuses on the mortality of the annuitants in Kenya. These are people who have purchased life annuities from Kenyan insurance companies. Exponential extrapolative methods are used to obtain reduction factors that are later used to extrapolate mortality from the year 2011-2050. An annuity of Ksh.1 is then priced over the extrapolated period for each age range for all years, in order to determine how an annuity changes over the years. From the analysis , the Kenyan mortality has been reducing. This has an inverse effect on the value of annuities as the annuity prices are observed to increase with an increase in mortality over the years. This therefore exposes the Kenyan insurance companies to longevity risk.
- ItemAgricultural micro-insurance in Kenya: determinants of the loss and profit experienced in insurance companies in Kenya in 2014(Strathmore University, 2016) Kirui, Fiona CABSTRACT The Kenyan agricultural production sector is faced with a lot of risks that will affect a farmer's level of income. The Kenyan insurance market offers two types of-agricultural micro insurance products, index based crop insurance and indemnity based crop insurance. This study has investigated the significant factors that affect profitability of an insurance company. To provide answers to the research questions quantitative methods were employed. Use of simulation of variables, correlation tests, and regression analysis were the major quantitative tools used to analyse the data availed. The results of the study conducted showed that companies that offer index based products are more profitable compared to companies that offer pure indemnity products. It was also noted that a combination of both products leads to a higher profit margin as opposed to offering pure based products.
- ItemThe viability of insuring outpatient care for a micro health insurance scheme(Strathmore University, 2015-11) Oseko, Brian MigiroOutpatient care is not widely insured due to demand side moral hazard. This is compounded by the fact that there is very high out-of-pocket expenditure especially for the poor. Micro Insurance firms cater for the needs of the poor but outpatient care is rarely part of the cover given to them. Even with the ones that provide the cover, it is limited. The purpose of this study is to assess the feasibility of a micro insurance company to insure outpatient care. The study focuses on outpatient utilization for three schemes. Outpatient costs are assessed as a measure of utilization and premium payments are also used as a measure of utilization. The study uses a panel data set from a Kenyan insurance company for the years 2012-2014. It incorporates the use of hypothesis tests to assess outpatient medical costs. The level of utilization of the outpatient benefits is very low. A small number of policyholders utilize more than their premiums paid and even less exceed the cover limits. This shows that these schemes are viable. More importantly it raises the question; why is the level of utilization in these schemes low given the high levels of outpatient utilization in Kenya?
- ItemInter - sector volatility spillover among equities on the Nairobi Stock Exchange(Strathmore University, 2015-11) Chuchu, Michael NyangasiThis paper investigates the existence and magnitude of volatility spillovers among equities on the Nair obi Securities Exchange. The multivariate VARMA - GARCH model is used to test for spillover effects between four broad sectors of the NSE: Agricultural, Financial, Commercial and Services and Industrial. The significance of the parameters of the model are used as an indicator of the spillover effect between sectors. Based on the empirical results, the biggest volatility spillover is from the commercial and services sector to the broad industrial sector. There are also significant spillovers from the industrial and agricultural sectors to the financial and commercial and services sectors, as well as from the financial and commercial and services sectors to the broad industrial sector.