project report- Allan

THE INFLUENCE OF ECONOMIC FACTORS ON THE PERFORMANCE

OF HEALTH INSURANCE SUBSECTOR IN NAIROBI COUNTY

Submitted by:

A RESEARCH PROJECT SUBMITTED IN PARTIAL FULFILLMENT OF

THE REQUIREMENTS FOR THE AWARD OF THE BACHELOR OF

SCIENCE IN ECONOMICS OF THE UNIVERSITY OF NAIROBI

July 2016

DECLARATION

I declare that I am the sole author of this research project, and that where other people’s

work has been used, this has been acknowledged. I further declare that to the best of my

knowledge this work has not previously been presented for any academic award.

NAME REGISTRATION

NUMBER

SIGNATUR

E

This project has been submitted for examination with my approval as college

supervisor

Mrs: …………………………………………..

Department of economics,

School of Economics

ACKNOWLEDGEMENTii

We wish to acknowledge the contributions of our families, friends and colleagues at

the university who gave us total support and encouragement towards our pursuit to

obtain a bachelor’s degree. We are equally grateful to our supervisor for the valuable

supervision she gave us, the skills and direction for this study.

TABLE OF CONTENTS

DECLARATION..........................................................................................................ii

iii

ACKNOWLEDGEMENT..........................................................................................iii

TABLE OF CONTENTS............................................................................................iv

LIST OF TABLES.......................................................................................................vi

ABSTRACT................................................................................................................vii

CHAPTER ONE: INTRODUCTION........................................................................1

1.1 Background of the study......................................................................................1

1.1.1 Health insurance subsector in Kenya.............................................................2

1.1.2 Economic factors affecting the health insurance sub-sector..........................3

1.2 Statement of the problem.........................................................................................4

1.3 Objectives of the study.........................................................................................5

1.3.1 General objective...............................................................................................5

1.3.2 Specific objectives.........................................................................................5

1.4 Research questions................................................................................................5

1.5 Significance of the study..........................................................................................6

1.6. Scope of the study...................................................................................................6

1.7 Limitations of the study............................................................................................6

CHAPTER TWO: LITERATURE REVIEW............................................................8

2.1 Introduction..............................................................................................................8

2.2 Theoretical Review...................................................................................................8

2.2.1 Modern Portfolio Theory (MPT)...........................................................................8

2.1.2 Black swam events theory.....................................................................................9

2.1.3 Arbitrage Pricing Theory.....................................................................................10

2.2 Empirical Review...................................................................................................11

2.3.1 The influence of interest rates on the performance of health insurance

subsector...............................................................................................................12

2.3.2 The influence of Inflation on the performance of health insurance subsector

..............................................................................................................................13

2.3.3 The influence of per capita income levels on the performance of health

insurance subsector...............................................................................................15

2.4 Conceptual Framework.......................................................................................17

2.5 Research Gap......................................................................................................18

CHAPTER THREE: RESEARCH METHODOLOGY.........................................19

3.1 Introduction............................................................................................................19

iv

3.2 Research Design.................................................................................................19

3.3 Target Population and sampling frame...............................................................19

3.4 Data Collection...................................................................................................20

3.5 Data Analysis......................................................................................................20

CHAPTER FOUR......................................................................................................21

4.0 DATA ANALYSIS AND PRESENTATIONS.....................................................21

4.1 Introduction............................................................................................................21

4.2 Descriptive statistics...............................................................................................21

4.3 Inferential statistics.................................................................................................22

4.3.1 Correlation analysis.............................................................................................22

4.3.1.1 Correlation between health insurance Performance and interest rates.............22

4.3.1.2 Correlation between health insurance Performance and inflation....................23

4.3.1.3 Correlation between health insurance Performance and GDP.........................24

4.3.2 Regression analysis.............................................................................................25

4.3.2.1 Model summary................................................................................................25

4.3.2.2 Regression coefficients.....................................................................................26

4.3.2.3 Significance level.............................................................................................27

4.4 Interpretation of the Findings.................................................................................28

CHAPTER FIVE........................................................................................................29

5.0 SUMMARY, CONCLUSIONS AND RECOMMENDATIONS.......................29

5.1 Introduction............................................................................................................29

5.2 Summary of Findings.............................................................................................29

5.3 Conclusion..............................................................................................................29

5.4 Recommendations..................................................................................................30

5.5 Limitations of the Study.........................................................................................31

5.6 Recommendations for Further Study.....................................................................31

REFERENCES...........................................................................................................33

APPENDICES.........................................................................................................36

Appendix I: Data Collection Sheet...........................................................................36

v

LIST OF TABLES

Figure 2.1: Conceptual Framework...............Error: Reference source not found

Table 3.1: Target Population of the census study............................................19

Table 3.2: Target Population of the census study……………………………20

Table 4.1: Descriptive Statistics of the Study VariablesError: Reference sourcenot found

Table 4.2 Interest rates and performance of health insurance firms...........Error:Reference source not found

Table 4.3 Health insurance Performance and inflationError: Reference source notfound

Table 4.4 Health insurance Performance and GDP.Error: Reference source notfound

Table 4.5 Model summary............................Error: Reference source not found

Table 4.6 Coefficients (a)..............................Error: Reference source not found

Table 4.7 ANOVA (b) table..........................Error: Reference source not found

vi

ABSTRACT The main objective of this study was to establish the influence of economic factors on

performance of health insurance in Nairobi County. The specific objectives were: to

determine the influence of interest rates on the performance of health insurance

subsector in Nairobi County; to determine the influence of inflation on the

performance of health insurance subsector in Nairobi County; to determine the

influence of per capita income levels on the performance of health insurance

subsector in Nairobi County. The study adopted a descriptive survey design in

addressing the research objectives. The study targeted insurance entities offering

medical insurance in Nairobi Kenya. The study used secondary data in addressing the

research problem. Secondary data will be obtained from reports, journals, publications

and articles related to the research topic. Quantitative data analysis was used in

analysing data in the study. The quantitative analysis mainly focused on descriptive

and inferential statistics. The Statistical Package for Social Sciences (SPSS version

21) program was used to generate the results. The results were presented using tables

and charts to give a clear visual impression of the research findings at a glance. The

study established that economic factors negatively affect the return on assets of the

health insurance companies in Nairobi. GDP, inflation, interest rates were found to

have negative coefficient with the return on assets illustrating that an increase in one

of these variables will leave a negative effect on the performance of the health

insurance companies. The study recommends further studies on the effect of

economic factors on performance on other firms and financial institutions and not just

health insurance companies investigating on what firm specific, industry specific and

macroeconomic factors affect the performance.

vii

CHAPTER ONE: INTRODUCTION

1.1 Background of the study

Health insurance is a type of insurance that covers medical expenses that are incurred

by the insured. Health insurance provides coverage for medicine, visits to the doctor

or emergency room, hospital stays, nursing homes and other medical expenses. The

insured pays premium to get health insurance policy. These policies offered by the

insurance companies differ in what they cover, limits of coverage and the options for

treatment available to the insured. Private health insurance is a contract between the

insured and the insurance company where the insurance company will pay for the

medical expenses if the insured gets sick or hurt (Mbogo. S, 2011)

The basic objective of any insurance mechanism is to protect individuals from risk. In

most situations, the insurer helps in protecting policyholders from unique health risks.

There is a wide variety of health systems around the world. In some countries, there is

a concerted effort among governments, trade unions, charities, religious, or other co-

ordinated bodies to deliver planned health care services targeted to the populations

Many developing countries have private health insurance markets which are serving

their middle class; and may also afford some degree of financial protection for the

poor (particularly those that are more commonly characterized as community health

insurance schemes). Many developed countries use supplementary private insurance

to fill gaps in their publicly funded systems offered by governments and pay for

increasing health services demand (Edebalk, Gunnar and Olofsson, 1999).

Health insurance in Kenya is provided by both private and public systems. The main

objective of the health systems has been to insure Kenyans against health risks that

they may encounter in future. It’s considered private when the third party (insurer) is

a profit organisation. In private insurance, people pay premiums related to the

expected cost of providing services to them. Therefore, people who are in high health

risk groups pay more, and those at low risk pay less (Republic of Kenya, 2003a).

There are 16 general insurance firms offering healthcare insurance in their portfolio.

Other firms run medical schemes as their sole business and they are in two categories:

the first category provides healthcare through own clinics and hospitals (these include

AAR Health Services, Avenue Healthcare Ltd and Clinix Ltd), while the other

category provides healthcare through third party facilities (Bupa International,). These

1

medical schemes are also known as Health Management Organizations (HMOs)

(AKI, 2014)

Unless development of health insurance is managed well it may have negative impact

on health care especially to a large segment of population in the country. If it is well

managed then it can improve access to care and health status in the country very

rapidly.

1.1.1 Health insurance subsector in Kenya

Health insurance in Kenya is categorised into private health insurance, public health

insurance e.g. National Hospital Insurance Fund (NHIF), Community-based health

insurance, No insurance (out of pocket). The measure in which the health insurance is

used includes the inpatients and outpatients services.

In Kenya we have both National social security fund NSSF and National Health

Insurance Fund (NHIF) which are both public health insurance schemes and non-

profit institutions created to provide access to health care. NHIF was created by the

NHIF Act in 1966 as a department in the Ministry of Health (MOH). It was mandated

to arrange for manageable health insurance for salaried public as well as private sector

employees. The members of NHIF contribute a compulsory fee ranging from Kshs. 30

and Kshs. 320 per month, which is primarily low compared to other types of

insurance. NHIF operates according to households and the insurance unit comprises

the whole family and relatives who are dependent. It is only the breadwinner who

contributes to the scheme. In families where two (or more) members are working and

earning own salaries, they all have to pay contributions to NHIF. Entitlement to health

care services includes all dependent household members. Children under 18

automatically benefit from NHIF through their parents' affiliation.

On the other hand, Private health insurance which is provided by the private sector

requires members to pay premiums depending on the package they want in the cover.

This type of coverage in Kenya has been classified into two categories that is

commercial health insurance and self-health insurance. Commercial health insurance

is the type of insurance which is profit driven, but with a quest to promote the general

health of a people (Government of Kenya, 2003).

The insurance industry is governed by the Insurance Act and regulated by the

Insurance Regulatory Authority. There are 50 licensed insurance companies for the

2

year 2015. Twenty five companies write non-life insurance business only, nine write

life insurance business only while fifteen are composite (both life and non-life). 16

general insurance firms have healthcare insurance as one of the offerings in their

portfolio (AKI). From the AKI, IRA and the AIBK to the insurance underwriters,

experts in insurance are embracing a new strategy that is aimed at ensuring the

industry commands the respect they deserve and that more customers are taking up

the services and are also becoming critical champions to drive insurance growth so as

to counter the erstwhile, limiting perceptions that insurers are out to fleece the public

with little or no likelihood of making a return from the lucrative covers offered (IRA

report, 2015).

The main objective of the health systems has been to insure Kenyans against health

risks that they may encounter in future. It’s considered private when the third party

(insurer) is a profit organisation (Republic of Kenya, 2003a).

1.1.2 Economic factors affecting the health insurance sub-sector

Economic factors are the changes in things such as costs and prices of goods. Change

in the inflation rate, interest rates, wage rates, exchange rates are also considered to be

economic factors. These factors affect the ability of firms to generate profits and need

close monitoring (Sekhri N. 2004).

Several studies have been done on the topic, for instance Machuki et.al (2011) who

embarked on a research study to investigate the effect of the external environment on

corporate performance. He found the external environment appeared to have great

influence in the companies’ strategic decision making. The study found factors that

were mostly manifested as economic factors to be dynamism, wavering degrees of

external environmental complexity and munificence.

Interest rate fluctuations, competition and liquidity are the key factors that have an

impact financial performance of companies in the Kenyan insurance market (Mwangi,

2013).

In a study to establish the determinants of performance of insurance companies in

Kenya, Wabita (2013) established that economic growth of the insurance industry

positively influences financial performance. Mutugi (2012) also did a study to

establish factors that influence financial performance of life assurance companies in

3

Kenya and found that capital structure, innovation, inflation and ownership structure

are determinants of financial performance.

Another study by Burca and Batrînca (2014) on the factors that influence performance

of insurance companies in Rome found that the determinants of performance in the

Romanian insurance market to be financial leverage in insurance, company size,

increase of gross written premiums, risk retention ratio, growth of GDP/ per capita,

underwriting risk and solvency margin.

A local study by Ndungu Timothy (2015) to investigate the factors influencing the

uptake of National Health Insurance in the informal sector in Kenya found

demographic factors, the level of education, economic factors and the level of

awareness on uptake of health insurance in the informal sector to have an influence in

the uptake of NHIF. The results indicated that the level of education was significant in

influencing their decisions to enrol. The study concluded that demographic factors

(including gender, age, household size, marital status and the number of children in

the household), level of education, socio-economic factors and awareness had

influence on the uptake of NHIF in the informal sector. The study recommended the

need to increase the awareness about health insurance, subsidizing the premiums,

review of premiums payment period, extending the NHIF office network and

increasing the number of health facilities.

1.2 Statement of the problem

Organizations exist in a complex commercial, economic, legal, demographic,

technological, political and social environment. This environment is under constant

change which affects the organizations that operates within it. According to Kotler

(2000) successful firms know the importance of constantly watching and adapting to

the changes in the business environment. Organizations therefore have to align

themselves well so as to cope with the ever changing environment. This will involve

the assessment of a firm’s internal capability and how it is equipped to adapt and

survive in the industry within which it operates. Strategy is vital to the adaptation of

the changing business environment. Health insurance companies like all other

organizations are environmental serving (Ansoff, 1984).

Health insurance is complex and there are serious market-failure problems. This is

because of various demand and supply side imperfections. There are inherent

4

problems in health insurance markets. Kenyans are among the least health insured in

the world. Despite the heavy investments by insurance companies in infrastructure,

operations efficiency, marketing, product development, diversification and

Information Technology, medical insurers continue to post poor results.

Some studies have been carried out on health insurance in the recent past. Mwaura,

(2009) did a study on Viability of accessing health insurance to the urban poor

through community based organizations, which does not address the issue of the

economic factors influencing the performance of health insurance.

Kubania (2011) did a study on the environmental challenges affecting performance of

health insurance in Kenya.

Mavalankar and Bhat, 2000 did a study on opportunities, challenges and concerns

facing health insurance in India, which is of a different context with Kenya. It is

against this background that this study seeks to determine the influence of economic

factors on the performance of health insurance sub sector in Kenya. This study will

therefore seek to answer the question: what is the influence of economic factors on

performance of health insurance subsector in Kenya?

1.3 Objectives of the study

1.3.1 General objective

The main objective of the study is to determine the influence of economic factors on

the performance of health insurance subsector in Nairobi County. In order to achieve

this objective, the study narrowed down the research problem to three specific

objectives as discussed below.

1.3.2 Specific objectives

The study will aim at addressing the following specific objectives.

1. To determine the influence of interest rates on the performance of health

insurance subsector in Nairobi County

2. To determine the influence of inflation on the performance of health insurance

subsector in Nairobi County

3. To determine the influence of per capita income levels on the performance of

health insurance subsector in Nairobi County

1.4 Research questions

The study seeks to address the following research questions in order to solve the

research problem.5

1. What is the influence of interest rates on the performance of health insurance

subsector in Nairobi County?

2. What is the influence of inflation on the performance of health insurance


3. How does per capita income levels affect the performance of health insurance


1.5 Significance of the study

To insurance companies, the study will be useful since it will help them in the

understanding of the economic factors affecting the performance of health insurance

therefore assisting them in proper underwriting of health insurance risks and

managing the economic factors and also in coming up with measures to assist them in

increasing the penetration and profitability.

To government, it will create awareness on the policy instruments that need to be

designed to promote the development and performance of health insurance in Kenya.

It will provide the necessary information needed in formulation of sound legal and

regulatory framework for better performance of the health insurance subsector in

Kenya.

The findings of this study will enhance the knowledge that educationists have on

health insurance and add-up to the literature on health insurance to the academicians

and expose the gaps for further research. The scholars will use this study as a basis for

discussion on responsive strategies adopted by the industry players in the insurance

subsector in Kenya. The study will be a source of reference material for future

researchers on other related topics. It will also help other academicians who undertake

the same topic in their studies.

1.6. Scope of the study

The study covered all health insurance companies registered and recognised by the

Commissioner of Insurance as at December 2015 and operating within Nairobi. The

study also focused on the effect of economic factors on the structure and performance

of health insurance industry.

1.7 Limitations of the study

The study was carried out in a company setting. Limitations might included 6

1. The study was or confined to health insurance companies in Nairobi since it

will be our main focus.

2. It’s also important to note that performance is a very interesting subject and

there are many perspectives that would be appealing to investigate more in

depth. However, it was beyond the scope of our study to cover all aspects and

our study was based on corporate perspective. Therefore the researchers

ensured to stay relevant to the corporate perspective.

7

CHAPTER TWO: LITERATURE REVIEW

2.1 Introduction

The study was to establish the influence of economic factors on the performance of

health insurance in Nairobi, Kenya.

This chapter discusses the theories that direct the study. The chapter will then analyse

the already available literature that has been done on the subject in accordance to the

study objectives. The literature review provides a foundation for the study on

influence of economic factors on performance.

2.2 Theoretical Review

Some of the leading theoretical approaches to the study of economic factors and

performance are the Modern Portfolio Theory and Interest Rates, black swam events

theory and the Arbitrage Pricing Theory.

2.2.1 Modern Portfolio Theory (MPT)

Modern Portfolio Theory (MPT) was developed by Harry Markowitz in 1952; it

assists in selecting the most efficient investments by analyzing various possible

portfolios of the given securities. By choosing securities that do not 'move' exactly

together, MPT model shows investors how to reduce their risk. It is based on expected

returns (mean) and the standard deviation (variance) of the various portfolios. MPT

attempts to maximize expected portfolio returns for a given amount of portfolio risk,

or equivalently minimize risk for a given level of return by carefully choosing the

proportions of various assets. It models a portfolio as a weighted combination of

assets, so that the return of a portfolio is the weighted combination of the assets

return. An investor either maximizes his portfolio return for a given level of risk or

maximizes his return for the minimum risk (Markowitz, 1952).

A portfolio that gives maximum return for a given risk, or minimum risk for given

return is an efficient portfolio. It is assumed that investors are rational, they would

like to have higher return and they are risk averse, they want to have lower risk. Thus,

when selecting a portfolio from the portfolios that have the same return, the investor

will prefer the portfolio with lower risk, when selecting from the portfolios that have

the same risk level, an investor will prefer the portfolio with higher rate of return

(Edwin, 1997). 8

Kung’u (2013) points out that any investment firm should have a portfolio of

investments in different types of investment to maximize returns and minimize risks.

Since insurance firms are investments by themselves its standard practice for them to

invest in a diversified portfolio to minimize risk and harness the returns of the various

investment options on offer. When choosing a portfolio investors should maximize

the discounted (or capitalized) value of future returns. Since the future is not known

with certainty, it must be "expected" or "anticipated" returns which are discounted.

Through combining different assets whose returns are not perfectly positively

correlated, MPT seeks to reduce the total variance of 16 the portfolio return. MPT

also assumes that investors are rational and the markets are efficient. MPT

emphasizes maximizing returns while minimizing risks, while giving recognition to

the existence of systematic and non-systematic risks. These concepts are usually

referred to when discussing financial investments.

Insurance being influenced by risks and returns as well, also finds meaning through

MPT. Diversification is the solution against being a victim of concentration risk.

Over-reliance on similar assets‟ profitability and hopes that contingent liabilities do

not become actual obligations are risks that can wipe-out risk portfolios in an instant.

Non-systematic risks and alphas are the main items that give underwriting skills

meaning. Non-systematic risks can be eliminated by widening the coverage of

insurance over more Assureds. In doing so, diversification is achieved. Alphas, on the

other hand, represent the surprise return or inherent profitability of an asset and in

converting this concept onto the insurance industry, this is perhaps the inherent

characteristics of an insured property/person/event and how the hazards and other

circumstances are minimized, wherein it is more probable that the premiums paid by

the Assured will eventually be kept at the end of the insurance policy coverage period.

While financial assets are capable of delivering abnormal returns, insurable risks are

also able to remain abnormally intact and avoid transforming into real obligations for

the insurance company. The fewer obligations an Insurance company has, the more

the profit hence better financial performance.

2.1.2 Black swam events theory

9

The concept of black swan events was popularized by Nassim Nicholas Taleb in

2008. It states that the world is severely affected by events that are rare and difficult

to predict, events of low probability but high impact.

Silberzath (2013), states that a black swan does not create a new category of events,

but is simply the occurrence of a known category, the probability of which was under

estimated. They occur not because their probability is inherently incalculable, but

because the model used to calculate them is wrong, or because though the model was

correct, the possibility of occurrence was dismissed in practice. Their implications for

markets and investment are compelling and need to be taken seriously.

The greatest risks are never the ones you can see and measure, but the ones you can’t

see and therefore can never measure. The ones that seem so far outside the boundary

of normal probability that you can’t imagine they could happen in your lifetime even

though, of course, they do happen, more often than you care to realize. What may be a

black swan to society at large may have limited insurance impact; likewise, some

events that cause catastrophic losses may not seem extreme from other perspectives.

Nobody wants to de-risk, in the sense that they want to actually take some money off

the table. It’s all about pricing and quantifying risk, and of course hedging against it.

Demand for protection against so-called tail risks is increasing as investors react to

black swan events (Silberzath, 2013)

An investor or a firm does not have to try to be too smart in trying to forecast what is

going to happen and which hedge is going to perform better what they need to do is

accumulate cheap protection. Insurance firms offer this cheap protection where by

large losses can be hedged against by paying small amounts known as premiums. By

having such products, insurance firms accumulate premiums in a pool, since the

occurrence of these events is minimal, they may end up paying none thus better

financial performance.

2.1.3 Arbitrage Pricing Theory

Arbitrage Pricing Theory (APT) was proposed by Stephen Ross in 1976. APT agrees

that though many different specific forces can influence the return of any individual

firm, these particular effects tend to cancel out in large and well diversified portfolio.

This is the principle of diversification and it has an influence in the field of insurance.

An insurance company has no way of knowing whether any particular individual will

10

become sick or will be involved in an accident, but the company is able to accurately

predict its losses on a large pool of such risk. However, an insurance company is not

entirely free of risk simply because it insures a large number of individuals. Natural

disaster or changes in health care can have major influences on insurance losses by

simultaneously affecting many claimants (Ross, 1976).

Cummins (1994) states that insurance companies are corporations and insurance

policies can be interpreted as specific types of financial instrument or contingent

claim thus it is natural to apply financial models to insurance pricing. The models are

designed to estimate the insurance prices that would pertain in a competitive market.

Charging a price at least as high as the competitive price (reservation price) increases

the market value of the company. Charging a lower price would reduce the company’s

market value. Thus, financial models and financial prices are among the key items of

information that insurers should have at their disposal when making financial

decisions about tariff schedules, reinsurance contract terms, etc.

The theory can help the insurance companies to decide whether a security is

undervalued or overvalued thus avoid making losses. It is also very useful for building

portfolios because it allows managers to test whether their portfolios are exposed to

certain internal or external factors that would affect the financial performance of

institutions. Doumpos and Gaganis (2012) estimated the performance of non-life

insurers and found that macroeconomic indicators such as gross domestic product

growth, inflation and income inequality influence the performance of firm.

2.2 Empirical Review

A number of studies have been conducted on the influence of economic factors on

performance. For instance, Kubania B.K (2010) who did a study to determine the

external environmental challenges affecting the performance of health insurance sub

sector in Kenya. He conducted a survey on the 16 insurance companies dealing with

health insurance. He found that several environmental challenges were affecting the

performance of health insurance sub-sector in Kenya which include political factors,

socio-economic factors, social factors, economic factors and technological factors.

The study also revealed a strong correlation between economic factors and the

performance of medical insurance companies. It also found that inflation, per capita

11

income, disposable income, economic growth rate, taxation and interest rate had a

strong impact on the performance of the insurance industry.

2.3.1 The influence of interest rates on the performance of health insurance

subsector

Interest rates are one of the economy single strongest influences and have a profound

effect on everything from individual investment decisions to job creation, monetary

policy and corporate profits. Economic environments have an intense consequence on

the growth of the insurance companies. A strong insurance industry promotes a

developed contractual saving sector which contributes to a more resilient economy

that would be less vulnerable to interest rates and demand shocks while creating a

more steady business environment, including macroeconomic stability (Mboga. C.

2015).

The main risk for life insurance sector are movements in interest rates because they

influence the values of assets and liabilities (KPMG 2002). Moreover, they indirectly

affect policyholders. An increase in interest rates may result in conclusions to lapse

policies because policyholders expect higher borrowing costs (Komarkova &

Gronychova 2012).

Gikungu (2012) did a study on the impact of macroeconomic variables on the

performance of Nairobi Securities Exchange (NSE). He found that there was a general

rise in inflation and interest rate over the period under study. He also found that

inflation rate had a positive but insignificant effect on share prices while interest rate

had a negative but insignificant effect on share prices.

Mboga (2015) embarked on a study to establish the effect of general interest rates on

the financial performance of licensed insurance companies in Kenya. The findings

showed that interest rates, GDP, age, size, liquidity risk and inflation are major

determinants of the return on asset which was a measure of financial performance for

the insurance companies in Kenya. The study established that interest rates negatively

affect the return on assets of the insurance companies in Kenya. GDP, inflation,

liquidity risk were found to have negative coefficient with the return on assets

illustrating that an increase in one of these variables will leave a negative effect on the

financial performance of the insurance companies. The study found a significant

negative statistical relationship between interest rates and financial performance of

insurance companies in Kenya. 12

Doumpos and Gaganis (2012) estimated the performance of non-life insurers and

found that macroeconomic indicators such as gross domestic product (GDP) growth,

inflation and income inequality influence the performance of firms.

Mwangi (2013) did a study to investigate the factors that influence the financial

performance of insurance firms in Kenya. The study was conducted using a

descriptive survey design. The findings of the study showed that fluctuations in

interest rates have an effect on the financial performance of insurance companies both

ways. This is because interest rates affect the rate of borrowings and the rate of return

on investments. Profitability as an indicator of financial performance enables

insurance companies to make decisions on investing in viable ventures while avoiding

the too risky ones.

Akotey and Amoah (2012) researched on determinants of performance of life

insurance companies in Ghana. The findings revealed that life insurers have been

incurring underwriting losses which detract from their financial performance. The

high underwriting losses as the results showed is due to overtrading, high claims

payments and high managerial expenses. The study further showed that gross written

premiums and total assets have a negative effect on investment income. This may be

due to the excessive attention on marketing to grow premiums without a proportionate

allocation of resources towards the management of their investment portfolios. This is

evidenced in the low levels of investment income in the industry.

2.3.2 The influence of Inflation on the performance of health insurance subsector

Chirwa and Mlachila (2004) defines inflation as a rise in the general level of prices of

goods and services in an economy over a period of time. When the general price level

rises, each unit of currency buys fewer goods and services. Consequently, inflation

reflects a reduction in the purchasing power per unit of money which is a loss of real

value in the medium of exchange and unit of account within the economy. Over time,

as the cost of products and services increase, the value of money decreases. Consumer

will therefore have to spend more money for the same products or services, which had

cost less in the previous year.

The insurance industry plays a critical role in financial and economic development of

the Kenyan economy. It is in this case that understanding how economic factor like

inflation influences the sector and precisely investment will help players make sound

13

business decisions. Inflation has a weak negative effect on the insurance investment

as it erodes the value of investments products (Mbogo. S, 2011).

A study by Muthoni, Joseph N (2012) on the effect of inflation on investment among

insurance companies in Kenya showed that inflation had a negative influence on the

investment among insurance companies in Kenya. Inflation had a coefficient of -

0.0668 which indicates that inflationary environment have a negative effect on

insurance investment. High inflation brings with it less predictable returns on capital

purchased and the hope that demand will decrease in the future while low inflation

will encourage investment and a help businesses develop a long term view. The study

recommended that central bank concentrate on policies which keep the inflation rate

lower than the first threshold because it may be helpful for the achievement of robust

economic growth and enhance investment.

Kimani J.K et.al (2012) examined the factors associated with participation in the

NHIF among residents of slums in Nairobi town. The study found that only 10% of

the respondents were participating in the NHIF program, while 0.8% of the

respondents had private insurance coverage. The majority of the respondents (89%)

did not have any type of insurance coverage. Females were more likely to participate

in the NHIF program, while respondents who were formerly in a union and who were

never in a union were less likely to have public insurance coverage. Respondents

working in the formal employment sector were more likely to be enrolled in the NHIF

program compared to those in the informal sector. Membership in microfinance

institutions such as SACCOs and community-based savings and credit groups were

important determinants of access to health insurance.

Kirui, Elvis (2014) sought to establish the determinants of ownership of health

insurance among people working in the informal and formal sectors in Kenya.

Findings revealed significant relationship between the sector of employment and

gender of the respondents, religion, education status, marital status and health status.

It was also established that there was no significant relationship between the sector

one was employed in and the status of insurance coverage for such an individual with

the odds of one being employed in the formal sector and having an insurance cover to

that of one having a cover but working in the informal sector was not significant.

Health insurance uptake considering the sector of the economy in this region largely

depends on highest level of education and total annual expenditure in that there is

14

likely to be an increase in health insurance uptake among households headed by males

who have attained higher levels of education and also have higher disposable income.

Most employers are offering health insurance packages to their staff. Indeed, health

care requirements offered by employers determine an employee's preference for

certain jobs. In an attempt to provide personnel with medical insurance, employers

have ended up offering the services in corporate coverage. These effects determine

the health seeking behaviour of employees. However, workers also develop coping

mechanisms in order to access adequate and appropriate health care (Kimonye, J.N

2011).

2.3.3 The influence of per capita income levels on the performance of health

insurance subsector

Income is the most important social and economic determinant of health, since the

level of income determines overall living conditions, psychological functioning and

influences health related behavior such as food security, housing, participation in

cultural and educational activities, which leads to effects to one’s health and lessens

the ability to live a fulfilling life (Auger & Alix, 2009).

In recent and past studies; house hold income in both developed and developing

countries has a positive association with the probability of buying health insurance

where income significantly determines the amount of health insurance purchased

(Osei-Akoto & Adamba, 2011).

In a study by Wanderi, Clara (2012) to establish factors influencing health insurance

practices among individuals in Nairobi Central Business District (CBD), Kenya

showed that uptake of health insurance was at 45.0%. This was relatively high among

employed persons and could be due to employer provided health insurance as well as

relative individual financial strength making it easier to afford and withstand. The

study concluded that poor health insurance practices was due to the high cost of health

premiums that made health insurance unaffordable to most people.

Increasing unemployment rates are typically accompanied by a decline in per capita

income. In this case the number of emergency surrenders would be likely to increase

since people use their life insurance savings either as substitute of complement of

benefits of unemployment insurance. This will definitely affect financial performance

15

of insurance companies due to massive surrender. In this study, they recommend

policymakers to ensure that macroeconomic stability is maintained. In particular they

recommend that unemployment should not exceed established levels, stability of the

currency needs to be maintained and high volatility of interest rates needs to be

avoided (Geneva Association, 2012).

The capacity to afford an insurance premium is directly connected to one’s level of

income. Although the limited ability to pay cannot be considered, strictly speaking, a

market imperfection contributes to the lack of demand for insurance and can be an

equity rationale for public intervention. In developing countries, low incomes inhibit

the development of insurance markets. Incomes for the vast majority of the population

are absorbed by basic necessities, such as food and housing. A recent analysis

indicates that there is very limited provision of insurance in the world’s poorest

countries, although there is some reason to believe that micro-insurance penetration

will increase in the future, particularly for life and health insurance (Roth, McCord,

and Liber 2007)

Robert (2005) in their study on enrolment of minorities, part-time workers, and those

employed in small firms in the United States found that coverage was influenced by

employment status, and size of the employer. Those who were employed were 78.5%

likely to be insured compared to 61.7% who were not in the labour force. Those who

remained unemployed for over one year, in part-time work and those working in small

firms of less than 10 employees were less likely to have health

insurance .Furthermore, 20.7% of those who moved from government employment to

become self-employed lost their health insurance. The researchers concluded that job

loss and movement to small employers were critical factors in explaining loss of

health insurance in an economy dominated by employer-sponsored insurance.

A study by Kirigia (2005) in South Africa showed that approximately 30% of

respondents had at least one person enrolled in a health insurance scheme while

Carrin (2004) concluded in his study that Rwanda had achieved 90% health care

coverage through implementation of Community Based Health Insurance scheme.

Kirigia et al (2005) found that the proportion of people who had health insurance rose

as household income increased with coverage of those earning 1-950 Rand being at

6.3% coverage while those earning above 7600 rand per month having a coverage of 16

90.75, implying that intervention at macroeconomic level to boost disposable incomes

in South Africa would boost enrolment in health insurance

Bhat and Jain (2006) analyzed the demand for private health insurance among lower

and middle income groups and found that households with Insurance had higher

incomes than those which were not insured. In addition, households reporting higher

healthcare expenditures as a percentage of total household expenditure had a higher

probability of purchasing health insurance. However, the researchers observed that the

level of income and health insurance relationship was nonlinear, in that as income

increased, health insurance increased but after a certain point, the relationship

between income and health insurance became negative, indicating that as incomes

increased, households allocated their resources to other uses, purchased less health

insurance, and were willing to retain the health risks.

2.4 Conceptual Framework

The study can be conceptualised as discussed below. The independent variables in the

study are; the influence of interest rates; the influence of per capita income, and the

influence of inflation on the performance of health insurance subsector in the Nairobi

County economy. The intervening variables are; government policies on insurance

and the economy, insurance regulations in Kenya, and other external factors affecting

the insurance industry and the economic performance. The dependent variable in this

case is the performance of the health insurance subsector.

Figure 2. 1 Conceptual Framework

Independent variable

17

Interest rates

Inflation

Per Capita Income

PERFORMANCE OF HEALTH INSURANCE SUBSECTOR

Dependent variable

Government policies Insurance regulations External Factors

Intervening Variables

For purposes of this study the manipulation of any of the independent variables is

expected to affect the performance of the insurance subsector in Nairobi County. The

performance of the insurance subsector is measured by the profitability levels of

insurance entities in Nairobi County.

2.5 Research Gap

The literature review established that a number of studies have been carried out on the

influence economic factors on performance. Researches about effects of economic

factors on performance have already stretched into various fields including the

banking sector, Real estate industry and other service and manufacturing industries.

Such studies in Kenya have been concentrating on environmental and external factors

affecting performance. No study domestically has studied the influence of economic

factors on performance. Researchers have drawn little attention to health insurance

and have focused on insurance industry as a whole. Kenya lacks the comprehensive

theoretical accumulation. Knowledge on economic factors in Kenya is far from

enough and there is also no clear definition of determinants of economic factors on

performance of health insurance in Kenya. For these reasons, the researchers wish to

fill the gap by establishing the influence of economic factors on performance of health

insurance in Nairobi County.

18

CHAPTER THREE: RESEARCH METHODOLOGY

3.1 Introduction

The chapter presents a discussion of the research design, the population, the sampling

techniques that will be used in the study, the data collection instruments, and the data

collection methods. Data analysis and presentation are also discussed.

3.2 Research Design

This study adopted a descriptive survey design in addressing the research objectives.

According to Upagade & Shende (2012), research design is the arrangement of

activities in research from collection and analysis of data in a way that aims at

combining relevance to the research process while achieving economy in procedure.

Descriptive survey can also be described as a method of acquiring information

through processes such as interviews or administering a questionnaire to a sample of

individuals in the target population (Orodho, 2003). This approach is preferred due to

its wide range of applicability which includes, though not limited to collecting

information on peoples’ attitudes, opinions, habits or any other social issues. Sekran

& Bougie (2011) on the other hand asserts that descriptive study has several

advantages which include; it helps in understanding the characteristics of a group in a

given situation, assists in systematic thinking about aspects in a given situation,

etcetera.

3.3 Target Population and sampling frame

According to Mugenda (2005) target population in research can be said to be the

number of individuals, who the study is interested in describing and making statistical

inferences about. On the other hand Kombo and Tromp (2006) describes population

as a group of individuals, objects or items from which samples are taken for

measurement in a study, or, the entire group of persons and/or elements that have

some similarity. The study targeted health insurance entities in Nairobi Kenya.

According to Denscombe (2010) a sample must be carefully selected to ensure that it

is representative of the population under study and moreover, the researcher needs to

ensure that the subdivisions made in the analysis are accurately catered for. Since the

scope of the study is small, the researchers will not sample the population therefore,

the study will survey all the health insurance in Nairobi County.

19

3.4 Data Collection

The study used secondary data in addressing the research problem. Secondary data

was obtained from reports, journals, publications and articles related to the research

topic and the data was filled into a data collection sheets which summarized the data

in accordance with the research objectives. The use of the data collection sheet was

preferred in this study as it offers an effective way of collecting information from a

large sample in a short span of time and at a reduced cost. Data collection sheets were

used because each company could be issued with the same set of questions in exactly

the same way.

3.5 Data Analysis

Quantitative methods of data analysis was used in analysing data in the study. The

quantitative analysis mainly focused on using descriptive and inferential statistics.

Trochim (2006) asserts that descriptive statistics are used to describe the basic

features of the data in a study or survey. This is because descriptive statistics provide

simple summaries about the sample and the measures. This was done together with

simple graphics analysis which forms the basis of virtually every quantitative

analysis. The Statistical Package for Social Sciences (SPSS version 21) program and

Microsoft excel (version 2013) were used. The results were presented using tables and

charts to give a clear visual impression of the research findings at a glance. Inferential

statistics involve correlation analysis, ANOVA and regression analysis.

The regression model used in analyzing the influence of economic factors on

performance of medical insurance companies was as follows:

Y=α+β1X1+β2X2+β3X3 +ε

Where:

Y= performance was measured using return on assets (ROA) which is was calculated

as net income divided by total Assets

X1= Interest Rates

X2= Consumer Price Index to represent inflation

X3= GDP per capita annual growth in % ratio.

20

CHAPTER FOUR

4.0 DATA ANALYSIS AND PRESENTATIONS

4.1 Introduction

The chapter presents the analysis part of the study. The analysis is based on the

research

objective the objective is tackled according to the analysis techniques designed in the

methodology. Data collected was analyzed and the findings are as presented in this

chapter

inform of tables and narration/ discussion of the results.

4.2 Descriptive statistics

Table 4.1 presents the descriptive analysis results of the variables of the study. The

data collected on the performance of the sector (measured in ROA) and the economic

factors (measured in three aspects; interest rates, the rate of inflation and per capita

income) was analyzed to give the mean values for the entire period understudy as well

as their standard deviations.

Table 4.1: Descriptive Statistics of the Study Variables

Mean Std. Deviation N

ROA .092179 .0055339 21

Interestrate

15.879434 2.2101602 21

Inflation 14.4935 11.401923 21

GDP 4.115667 1.7173726 21

According to the study results in table 4.1, the average ROA (financial Performance)

of the health insurance firms in Nairobi for a five year period (2010-2015). The result

illustrates that the average return on assets was 0.0921 with stand deviation of

0.0055339. This implies that one unit of total assets invested by the medical insurance

company generated a net income of 0.0921 units on average during the study period.

21

The mean interest rate was 15.879% with a standard deviation of 2.21016. Average

mean inflation stood at 14.4935% with a standard deviation of 11.4019. GDP growth

rate registered a mean of 4.115% with standard deviation of 1.17137. Thus, these

values can be relied as representatives of the performance of the health insurance

firms in Nairobi.

4.3 Inferential statistics

The inferential statistics involved the use of correlation and multiple linear regression

analysis. The regression analysis was done using Ordinary Least Squares (OLS)

method. However, before running the regressions, descriptive statistics and

correlation analysis were considered. Correlation analysis shows the relationships

between the different variables considered in the study

4.3.1 Correlation analysis

In this study, the Pearson r statistic is used to calculate bivariate correlations. Values

between 0 and 0.3 (0 and -0.3) indicate no correlation (variables not associated), 0.3

and 0.5 (-0.3 and -0.5) a weak positive (negative) linear association, Values between

0.5 and 0.7 (-0.5 and -0.7) indicate a moderate positive (negative) linear association

and Values between 0.7 and 1.0 (- 0.7 and -1.0) indicate a strong positive (negative)

linear association. The significance of the relationship is tested at 95% level with a 2-

tailed test where a statistically significant correlation is indicated by a probability

value of less than 0.025. This means that the probability of obtaining such a

correlation coefficient by chance is less than 2.5 times out of 100, so the result

indicates the presence of an association.

4.3.1.1 Correlation between health insurance Performance and interest rates

Correlation analysis results for the association between interest rates and performance

of health insurance firms is presented in table 4.2 below. It gives the Pearson s

coefficient value (correlation test) and the significance value (measuring significance

of the association)

Table 4.2 Interest rates and performance of health insurance firms

22

Project sustainability

Interest ratesPearson correlation .803

Sig.(2 tailed) .012N 21

From the table, the Pearson correlation value was obtained to be 0.803. This is a

coefficient value in the interval 0.7 to 1.0 which indicates that the variables have a

strong correlation value which is as well positive. Testing the significance of the

association at 5% level with a 2-tailed test, the association has a significant value of

0.012. This value is less than the critical value at 5% level (0.025, 2-tailed). This

therefore confirms the significance of the association between the two variables. The

results therefore suggest that there is a strong positive correlation between interest

rates and performance of health insurance firms which is also statistically significant.

4.3.1.2 Correlation between health insurance Performance and inflation

Correlation analysis results for the association between health insurance Performance

and inflation is presented in table below. It gives the Pearson s coefficient value

(correlation test) and the significance value (measuring significance of the

association)

Table 4.3 Health insurance Performance and inflation


InflationPearson correlation .863


Based on the findings in the table, health insurance Performance and inflation has a

correlation coefficient of 0.863 which is a strong and positive correlation coefficient.

23

Its significance tested at 5% level with a 2-tailed test indicated a significant value of

0.006 less than 0.025 (the critical value). Thus, the findings indicate that there is a

strong positive association between health insurance Performance and inflation. This

association was also proved to be statistically significant hence explaining the

reliability of the association.

4.3.1.3 Correlation between health insurance Performance and GDP

Correlation analysis results for the association between health insurance Performance

and GDP is presented in table below. It gives the Pearson s coefficient value

(correlation test) and the significance value (measuring significance of the

association)

Table 4.4 Health insurance Performance and GDP


GDPPearson correlation .887


The study results in the table indicate that, health insurance Performance and GDP

have a correlation of 0.887. This according to the Pearson s correlation scale indicates

a strong positive correlation. Its significant value is 0.015 as the table shows. This is

also a value less than 0.025 at 5% level thus revealing that the association is

statistically significant. The results therefore show that there is a strong and positive

correlation between health insurance Performance and GDP.

24

4.3.2 Regression analysis

The objective of this study was to establish the influence of economic factors on

health insurance performance in Nairobi. To accomplish this, the study conducted a

regression analysis which gives the relationship between the economic factors

(independent variables) used in the study including the interest rates, inflation rate,

GDP and the performance of the insurance firms (measured by the ROA). The data

used was collected for 5 years thus giving a 5 year period data which facilitated linear

regression analysis. The regression results are presented in tables 4.5 and 4.6 below.

4.3.2.1 Model summary

Table 4.5 gives the regression model summary results. It presents the R value which is

the measure of association between the dependent and the independent variables, the

R Square which is the coefficient of determination measuring the extent at which the

independent variables influence the dependent variable as well as the Adjusted R

Square which measures the reliability of the regression results.

Table 4.5 Model summary

Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .974a .949 .909 .04384

a. Predictors: (Constant), x4, x1, x2, x3

Source: Research data (2016)The findings show that R which is the multiple correlation coefficient that shows

quality of the prediction of the dependent variable by the independent variable is

0.974. This is a good indication since it points to a strong correlation. The R-Square

which is the coefficient of determination shows that the three independent variables in

the model explain 94.9% of health insurance performance. Subsequently from the

Adjusted R-Squared it is evident that after adjusting the model for inefficiencies the

independent variables can explain 90.9% of health insurance performance.

25

4.3.2.2 Regression coefficients

In order to answer the proposed model for the relationship between health insurance

performance and the independent variables, the regression coefficients were

calculated and presented in table 4.6 below. These with their significance values (also

given in the table) measures the influence of each independent variable to health

insurance performance (dependent variable) and the effect that would occur to health

insurance performance in an attempt to changing (increasing/decreasing) these

variables.

Table 4.6 Coefficients (a)

Model Standardized Coefficients t Sig.

Beta

1

(Constant) 0.0125

Interest rate -.954 -4.0241 0.0001

Inflation -.049 -4.4511 0

GDP -.743 -4.258 0

a. Dependent Variable: ROA

These coefficients therefore are used to answer the following regression model which

relates the predictor variables (independent variables) and the dependent variables;

Y=α+β1X1+β2X2+β3X3 +ε

Where:

Y= performance was measured using return on assets (ROA) which is was calculated

as net income divided by total Assets

X1= Interest Rates

X2= Consumer Price Index to represent inflation

X3= GDP per capita annual growth in % ratio.

Based on these coefficients, the regression model therefore becomes;

Y (ROA) = 0.0125 – 0.954INT – 0.049INF – 0.743GDP

26

Table 4.6 above portray that holding all the explanatory variables constant, health

insurance companies will realize an average of 0.0125 units in profitability. Interest

rates have a negative coefficient of – 0.954 implying that interest rates negatively

affect performance of health insurance companies. Inflation has a negative coefficient

of – 0.049 implying that inflation negatively affects performance of health insurance

companies. GDP has a negative coefficient of – 0.743 implying that GDP negatively

affects performance of health insurance companies.

4.3.2.3 Significance level

Analysis of the variance (ANOVA) was used to make simultaneous comparisons

between means; thus, testing whether a significant relation exists between dependent

and independent variables. ANOVA indicates a significant F statistics implying that

the model was fit for the estimation.

The results presented in table 4.7 gives the ANOVA results which shows the

reliability of the model developed in explaining the relationship between the study

variables. The significance of the model was tested at 5% level with a 2-tailed test.

Table 4.7 ANOVA (b) table

Model Sum of

Squares df Mean Square F Sig.1 Regressio

n .268 3 .08934 3.436 .015(a)

Residual .026 1 .026 Total .138 4

a. Predictors: (Constant), interest rates, Inflation, GDPb. Dependent Variable: health insurance performance

From the table, the F statistic is 3.436 with a distribution F(3,1), and the probability of

observing a value greater than or equal to 3.436 is less than 0.001 as given by the

significance value of 0.015 which is less than the critical value at 5% level in a 2-

tailed test. This therefore reveals that the regression model developed is statistically

significance and the variation in the results is insignificant that cannot result to a

much difference in case of a change in the study units (population) and therefore the

27

model can be relied upon to explain the influence of economic factors on health

insurance performance.

4.4 Interpretation of the Findings

The average performance of the insurance companies is 0.0125 units when economic

factors affecting financial performance are held constant. Interest rate is statistically

significant (t = -4.0241, p = 0.0001, p < 0.05) at 5% level of significance in explaining

the variation in performance of the insurance companies in Nairobi. The result further

shows that interest rates negatively affect the return on assets for the insurance

companies and a unit increase in interest rate will lead to 0.954 unit decrease in the

performance of the insurance companies. Inflation is statistically significant at 5%

level of significance given that t= -4.4511, p = 0.000. A unit increase in inflation will

lead to 0.049 unit decrease in the performance of the health insurance companies in

Kenya. GDP was established to have a negative coefficient with the return on assets

of the health insurance companies in Nairobi. That is, one unit increase in GDP will

lead to 0.743 unit decrease in return on assets for the insurance companies in Nairobi.

28

CHAPTER FIVE

5.0 SUMMARY, CONCLUSIONS AND RECOMMENDATIONS

5.1 Introduction

This chapter presents the summary of research findings, discussion of key findings,

conclusions made from the study and the recommendations for policy and practice.

The chapter also presents suggestions for further research.

5.2 Summary of Findings

The objective of the study was to investigate the influence of economic factors on the

performance of the health insurance companies in Nairobi. Both descriptive and

inferential statistics were employed specifically using correlation, regression and

ANOVA to establish the significance of the model and also to deduce the relationship

between performances and economic factors. In data analysis and presentation of

results findings showed R-squared of 100% implying that GDP, interest rates and

inflation are major determinant of the return on asset for the health insurance

companies in Nairobi. Using regression outputs of the health insurance companies;

the study established that economic factors negatively affect the return on assets of

the health insurance companies in Nairobi. GDP, inflation, interest rates were found

to have negative coefficient with the return on assets illustrating that an increase in

one of these variables will leave a negative effect on the performance of the health

insurance companies.

5.3 Conclusion

The results obtained from the model shows that there is a negative and statistically

significant relationship between economic factors and performance of health

insurance companies in Kenya. This implies that economic factors are important

determinants of the performance of the health insurance companies in Nairobi. The

result further shows that economic factors negatively affect the return on assets for the

health insurance companies and a unit increase in interest’s rate will lead to 0.954 unit

decrease in the performance of health insurance companies. A unit increase in

Inflation lead to 0.049 unit decrease in the performance of health insurance

29

companies. A unit increase in GDP will lead to 0.743 decrease in the performance of

health insurance companies.

5.4 Recommendations

The study recommends that the government through the insurance regulatory

authority should ensure that the health insurance companies follow the doctrine of

interest rates set when pricing their products so as to ensure to protect consumers from

unfair, deceptive, and abusive practices of overpriced policies. Stronger regulations

should be set to improve the transparency, fairness, and appropriateness of consumer

and investor products and services.

Central bank as a regulator should monitor general interest rates, because the

likelihood of very low interest rate is one reason insurers have redesigned and re-

priced some products, offering less-generous features to individuals. These include

long-term care insurance and retirement-income products with minimum-income

levels. Insurers stand to lose from persistently low interest rates. According to the

study, economic factors are a significant factors in influencing the return on assets and

therefore affect the performance of health insurance companies in Kenya.

The study also advises the management of health insurance companies to carefully

match their asset and liability cash flows in order to manage their interest rate risk.

Insurers should establish a well matched portfolio of their assets and liability in terms

of cash flows or rather they should ensure that they create additional reserve so that it

can assist them to cover the interest rate since low interest may create a discrepancy

on the earnings.

Lastly it is important for the Kenyan government to raise regulatory standards

concerning insurers, new requirements for transparency, high quality services and

insurance policies, improve international cooperation, stronger regulation of interest

rates, enhancing crisis management tools and improving oversight of financial

markets. This will attract foreign investors and expand the health insurance industry

thus economic growth.

30

5.5 Limitations of the Study

One of the critical concerns was the credibility, accuracy, validity and dependability

of the data. Secondary data being information that has previously been collected by

persons may be subject to errors, being out of date and even creative accounting from

insurance company management, especially the periodic reports. This study used

secondary data obtained from the financial statements electronic journals and websites

belonging to the target insurance companies, Association of Kenya Insurers (AKI)

and Insurance regulatory Authority (IRA), to help evaluate the influence of economic

factors on performance of health insurance companies in Kenya

An important concern was ability to find study participants, solicit quick and useful

feedback during the research study. Some insurance company executives were either

unavailable or too busy, others even refused to give consent to access critical and

private information.

Another challenge the researchers faced was the time aspect. More time is required

for the researchers to read most if not everything they can on the topic. Given that

data collection involved visiting the various insurance companies for the information

that is not available on the internet and consumed a lot of time.

Future researchers will need to allocate more time to the project work and prepare to

manage this time effectively. The cost of doing the entire research was also a

challenge. Completing the entire research incurred a lot of cost from printing and

binding charges, transport fees to various health insurance companies to gather data,

internet cost among others. Future researchers will need to prepare financially in order

to complete their research.

5.6 Recommendations for Further Study

This particular study only used a population of 21 health insurance companies.

Further research study can be carried out in future using a larger population on the

relationship between economic factors and performance.

This study used five years, a period of study which though helpful, may not quite be

adequate to make complete unquestionable conclusions. The researcher recommends

further studies on the effect of economic factors on performance be done using a

31

longer period which can reveal more sufficient and conclusive information about the

relationship.

Similar studies can be done on other firms and financial institutions and not just

health insurance companies investigating on what firm specific, industry specific and

macroeconomic factors affect the performance. This can help identify the areas of

concern in order to improve the performance of the firms and enhance economic

growth in Kenya.

32

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APPENDICES

Appendix I: Data Collection Sheet

Year ROA CPI

index

GDP/ per

capita

income

Interest

rates

2011

2012

2013

2014

2015

Source: Researcher (2016)

36

Appendix II: Licensed Insurance companies in Kenya as at 31.12.2014

1. AAR Insurance Kenya Limited

2. APA Insurance Limited

3. Africa Merchant Assurance Company Limited

4. Apollo Life Assurance Limited

5. AIG Kenya Insurance Company Limited

6. British-American Insurance Company (K) Ltd

7. Cannon Assurance Limited

8. CIC General Insurance Limited

9. CIC Life Assurance Limited

10. Continental reinsurance limited

11. Corporate Insurance Company Limited

12. Direct line Assurance Company Limited

13. East Africa Reinsurance company ltd

14. Fidelity Shield Insurance Company Limited

15. First Assurance Company Limited

16. GA Insurance Limited

17. GA life assurance Ltd

18. Gateway Insurance Company Limited

19. Geminia Insurance Company Limited

20. ICEA LION General Insurance Company Ltd

21. ICEA LION Life Assurance Company Limited

22. Intra Africa Assurance Company Limited

23. Invesco Assurance Company Limited

24. Kenindia Assurance Company Limited

25. Kenya Orient Insurance Limited

26. Kenya Reinsurance Corporation Limited

27. Liberty Life Assurance Limited

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28. Madison Insurance Company Kenya Limited

29. Mayfair Insurance Company Limited

30. Mercantile Insurance Company Limited

31. Metropolitan Life Kenya Limited

32. Occidental Insurance Company Limited

33. Old Mutual Life Assurance Company Limited

34. Pacis Insurance Company Limited

35. Pan Africa Life Assurance Limited

36. Phoenix of East Africa Assurance Company Ltd

37. Pioneer Assurance Company Limited

38. REAL Insurance Company Limited

39. Shield Assurance Company Limited

40. Takaful Insurance of Africa

41. Tausi Assurance Company Limited

42. The Heritage Insurance Company Limited

43. The Jubilee Insurance Company of Kenya Ltd

44. The Kenyan Alliance Insurance Co Ltd

45. The Monarch Insurance Company Limited

46. Trident Insurance Company Limited

47. UAP Insurance Company Limited

48. UAP Life Assurance Limited

49. Xplico Insurance Company Limited

Source: www.ira.go.ke (2014)

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Appendix III – List of health insurance Companies As at 31.12.2014

Medical insurance Companies in Nairobi

1) Apollo Life insurance Limited

2) CFC Life insurance Limited

3) CIC Life insurance Limited

4) First Assurance Company Limited

5) ICEA LION Life insurance Company Limited

6) Intra Africa Assurance Company Limited

7) Invesco Assurance Company Limited

8) Kenindia Assurance Company Limited

9) Metropolitan Life insurance Kenya Limited

10) Old Mutual Life insurance Company Limited

11) Pan Africa Life insurance Limited

12) Pioneer Assurance Company Limited

13) Shield Assurance Company Limited

14) Tausi Assurance Company Limited

Composite Insurance Companies in Kenya

1) British American Insurance Company (K) Limited

2) Cannon Assurance Limited

3) Corporate Insurance Company Limited

4) Geminia Insurance Company Limited

5) The Heritage Insurance Company Limited

6) The Jubilee Insurance Company of Kenya Limited

7) The Kenyan Alliance Insurance Company Limited

Source: AKI (2014)

39

project report- Allan

Documents

Transcript of project report- Allan