Research Dholaikhal

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RESEARCH ON THE EFFECTIVENESS OF MICROINSURANCE IN BANGLADESH

Submitted to

Dr. Muhammad Ziaulhaq Mamun

Professor

Course: K301: Research Metholology

Institute of Business Administration

University of Dhaka

Submitted by

Mushreka Afroze Khan (RH-68)

Ornila Khan (RH-72)

Zeeshan Ahmed (ZR-82)

Waseem Khan (ZR-88)

Ishmam Ahmed Chowdhury (ZR-90)

Wais Al Karim (ZR-93)

Sudipta Saha Turja (ZR-95)

Hikmat Kabir (ZR-99)

Sanjir Ali (ZR-111)

Group: 1

Section: B, Batch:20th


University of Dhaka

July 6, 2014

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July 6, 2014

Dr. Muhammad Ziaulhaq Mamum

Professor


University of Dhaka

Sir:

Re: Submission of term paper

We would like to take this opportunity to present our term paper titled Research on the

Effectiveness of Micro Insurance in Bangladesh for your consideration as part of our Research

Methodology coursework. This report aims to address the effectiveness of Micro Insurance

schemes Bangladesh, including the history, issues, problems, challenges, and a survey of policy

holder to obtain an understanding whether the schemes are truly beneficial.

We have tried our level best to comply with your high standards and we sincerely hope that our

paper meets your expectations.

Sincerely

Mushreka Afroze Khan (RH 68) Ornila Khan (RH 72)

Zeeshan Ahmed (ZR 82)

Waseem Khan (ZR 88)

Ishmam Ahmed Chowdhury (ZR 90)

Wais Al Karim (ZR 93)

Sudipta Saha Turja (ZR 95)

Hikmat Kabir (ZR 99)

Sanjir Ali (ZR 111)

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ACKNOWLEDGMENTS

In course of our research work, being completely new to the field of insurance, let alone micro

insurance, the research team required industry help and information to guide this research

properly. For this we had reached out to two distinguished individuals from the insurance

industry, who had helped us, considerably and furthermore encouraged to look at their industry

at depth.

For their immense role in helping us obtain information and understanding about the insurance

industry we would like to convey our sincerest gratitude to the following people.

1. Mr. Munir Ahmed

Executive Director

Green Delta Insurance Co. Ltd.

2. Md. Manirul Islam

Managing Director & CEO

Pragati Insurance Limited

3. Sujit Kumar Bhoumik

Executive Vice President

Prime Insurance Company Limited

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TABLE OF CONTENTS

Title page

Letter of transmittal

Acknowledgements

Executive summary

1.0 INTRODUCTION

1.1 Issue

1.2 Problems

1.3 Objectives

1.3.1 Broad objectives

1.3.2 Specific objectives

1.4 Hypotheses

1.5 Scopes

1.6 Rationale

1.7 Limitations

2.0 LITERATURE REVIEW

2.1 The micro-insurance industry

2.2 Types of micro-insurance in Bangladesh

2.3 Problems in insurance industry

2.4 Insurance reform program

2.5 Micro-insurance for poverty alleviation

2.6 Who provides micro insurance

2.7 Micro-insurance and SME

2.8 Micro-insurance in public health

2.9 Micro-insurance as a promising sector

3.0 METHODOLOGY

3.1 Data collection

3.1.1 Primary source of data

3.1.2 Secondary source of data

3.2 Sample size

3.3 Sampling technique

3.4 Questionnaire development

3.4.1 Categories of questionnaire

3.4.2 Question patterns

3.4.3 Pretesting

3.5 Data collection

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3.6 Data Analysis

4.0 RESEARCH FINDINGS

4.1 Findings regarding knowledge of policyholders

4.1.1 Knowledge regarding number of companies

4.1.2 Knowledge regarding other programs of company the

respondent is a client of

4.1.3 Knowledge regarding the chosen micro-insurance policy

4.1.4 Knowledge regarding the reason for choosing the micro-

insurance policy

4.1.5 Synthesis of knowledge of policyholders

4.2 Findings regarding claims of micro-insurance

4.2.1 Findings regarding background check on claims

4.2.2 Findings regarding acceptance rate of claims

4.2.3 Findings regarding denial of claims

4.2.4 Findings regarding time of claims

4.2.5 Findings regarding satisfaction of policyholders relating to

claims

4.2.6 Synthesis of micro-insurance claims

4.3 Findings regarding collection and recovery of premium

4.3.1 Findings regarding medium of premium collection

4.3.2 Findings regarding considerations during premium collection

4.3.3 Findings regarding incidence of frauds

4.3.4 Findings regarding handling of frauds

4.3.5 Findings regarding time of recovery of premium after maturity

4.3.6 Findings regarding satisfaction about amount of premium

recovered

4.3.7 Synthesis of micro-insurance premiums

4.4 Findings regarding employees of micro-insurance

4.4.1 Findings regarding instances of misbehavior by employees

4.4.2 Findings regarding perception of employee behavior

4.4.3 Findings regarding the amount charged by agents

4.4.4 Findings regarding unrecorded payments

4.4.5 Findings regarding knowledge of employees

4.4.6 Findings regarding the frequency of visits made by agents

4.4.7 Synthesis of micro-insurance employees

4.5 Findings regarding coverage of micro-insurance

4.6 Combination of findings

5.0 CONCLUSION

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APPENDIX

Appendix 1: Questionnaires for the survey

Appendix 2:Co-ordination schema

Appendix 3: Estimated budget

Appendix 4: Time plan

Appendix 5: Hypothesis tests for the knowledge of policyholders

Appendix 6: Hypothesis tests for the claims of policyholders

Appendix 7: Bivariate correlation analysis

Appendix 8: Hypothesis tests for premium of micro-insurance

Appendix 9: Hypothesis tests for employees of micro-insurance

REFERENCES

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EXECUTIVE SUMMARY

Micro-insurance refers to insurance products designed for the low-income individuals. The word

micro represents the relatively small transaction size or lower premiums, a concept similar to

microfinance. Micro-insurance differs from traditional insurance in terms of the size of

premiums, coverage limits and target customers. The objectives of micro-insurance also vary

amongst different stakeholders. For governments and policymakers, for instance, micro-

insurance is a way to ensure inclusive growth and support the livelihoods of the vulnerable

segment of the society. For social and development organizations, micro-insurance can be an

effective tool to help alleviate poverty.

For a developing country like Bangladesh, micro-insurance seems like a boom that can help

Bangladesh address its problems regarding poverty especially in the agriculture and health

sectors. Indeed, micro-insurance has seen a lot of growth since its introduction in the country

during the 1970s with a growth rate of almost 15-20 percent each year since 2006, as said by Md.

Manirul Islam, Managing Director and CEO of Pragati Life Insurance Limited. Yet, a stellar idea

such as micro-insurance may not be a proper solution to Bangladeshs problems. In order to

justify the use of micro-insurance, we came up with a plan to gauge its effectiveness by setting

up 5 parameters that tests its relevancy here in Bangladesh. These parameters and their

effectiveness are as follows:

Knowledge of the policyholders of micro-insurance 25% effective based on 4 different

tests

Claims on micro-insurance 70% effective based on 5 different tests

Premium collection and recovery of micro-insurance 25% effective based on 6 different

tests

Employees of micro-insurance 60% effective based on 7 different tests

Micro-insurance coverage 10% effective based on 11 different tests

These effective rates were then combined and weighted as per the relevance of each parameter.

The final result showed that the total effectiveness of micro-insurance in Bangladesh stands at

only 34.2%, thus making it irrelevant as a development tool for Bangladesh. However, it should

be mentioned that the scope of this survey was limited to Dhaka only and may not be sufficient

enough to cover the overall scenario in Bangladesh. More extensive research needs to be carried

out in order to truly determine the usefulness of micro-insurance.

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1.0 INTRODUCTION

1.1 ISSUE

Micro-insurance can be defined as an affordable subset of a financial service that uses risk

pooling to provide compensation to low income and poor individuals, entrepreneurs, households

or groups that are adversely affected by specific risks. While there may be great variance

between different micro-insurance schemes, they generally share a number of key characteristics

(Mizan R. Khan, 2013). These characteristics are:

a) Specifically targets low income and poor individuals and households

b) Designed to pool risks faced by the insured

c) Pricing is based on willingness to pay, and is proportional to the likelihood and cost of

the risks involved

d) Products are developed in collaboration with the communities they are supposed to

benefit

e) Products must be of substantive value to the poor in terms of addressing their

vulnerability to poverty

Micro-insurance was first introduced in Bangladesh in the 1970s in the form of health insurance

by an NGO called Ganashasthya Kendra. At present, there are over 60 micro-insurance

providers within the country and the growth rate of micro-insurance has been 33% between the

years 2008 and 2009. The sector is dominated by non-government organization microfinance

institutions (NGO-MFIs). Other types of organizations which operate in this sector are private

insurance companies and a couple of state-owned corporations (Mizan R. Khan, 2013).

1.2 PROBLEMS

Bangladesh is situated in the delta formed by multiple rivers as they meet the Indian Ocean

through the Bay of Bengal. Most of these rivers (Padma, Meghna and Jamuna for instance) are

originated from the Himalayas which lie to the north of the country. The lofty Himalayas in the

north and the funnel-like shape of the Bay of Bengal in the south have made Bangladesh one of

the worst victims of the catastrophic ravages of natural disasters like floods, cyclones, storm

surges, droughts, etc. These natural disasters render Bangladesh towards many losses: loss of

agricultural production, loss of livestock, loss of livelihood and loss of lives (Sakib, 2012).

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Yet another notable fact about Bangladesh is that the country is highly dependent on its

agricultural sector. A total area of 14.943 million hectares are cropped within the country, may it

be singly, doubly or triply in a year. A staggering 47.5% of the total manpower of Bangladesh

earn their livelihoods from this sector and cumulatively account for 19.29% of the countrys

GDP as of 2013 (Ministry of Agriculture, 2014).

When both of the above are combined, the consequence that natural disasters have on the

economy of Bangladesh is overwhelming. Damages to the agricultural sector are defined as full

or partial destruction of assets in the sector. This includes destruction to agricultural land,

permanent plantations, irrigation or drainage systems, storage facilities, machineries, roads, etc.

Production losses occur due to the loss of a full crop due to the calamity, or as a result of a

decline in units yielded (Global Facility for Disaster Reduction and Recovery, 2008). When

methods are looked upon on how to tackle these production and financial losses which the

farmers suffer, one of the solutions that are often mentioned is the use of micro-insurance.

The span of micro-insurance is not only limited to the poor farmers from Bangladeshs

agricultural sector. One of the major applications of micro-insurance can be in the public health

sector. Bangladesh is a country where 88% of ones health expenditure comes from out-of-

pocket expenditure, 10% from non-profit institutions serving households and only a mere 0.8%

from pre-payment and risk pooling plans (Werner, 2009). This is fact enough to show what

micro-insurance is not very popular within Bangladesh.

This leads us to our research question. With so high growth in this sector and with so many

companies serving the general population, why is the micro-insurance not a common tool used

throughout Bangladesh? Is the micro-insurance sector effective?

1.3 OBJECTIVES

1.3.1 Broad objectives:

To find out the effectiveness of micro-insurance in Bangladesh

1.3.2 Specific objectives:

To find out the level of knowledge of the existing policyholders on the policies that are

being offered by the existing micro-insurance companies

To find out the coverage of micro-insurance within Bangladesh in terms of the assets that

are being insured by the existing micro-insurance policies

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To find out the problems faced by the policyholders in the process of insurance claims

and settlements

To find out the problems faced by the policyholders in the process of payment of

premiums

To find out the problems faced by the policyholders in the process of recovering the

premiums following the maturity period

To find out the level of cooperation of the employees of the micro-insurance companies

1.4 HYPOTHESES

Some hypotheses have been derived out of the specific objectives based on our expectations:

The existing policyholders do not have much overall knowledge on micro-insurance.

The claiming process is not effective in the context of micro-insurance in Bangladesh

The process of collection of premium is effective, but that of recovery of premium after

maturity is not.

The coverage of micro-insurance in terms of assets is quite high in Bangladesh.

1.5 SCOPES

The research topic is only limited to micro-insurance. All the other types of insurance

policies are not within the scope of the report.

The paper only considers the opinions of surveyed policyholders from different parts of

Dhaka city and a few selected companies which provide micro-insurance policies.

For all the hypothesis testing that has been carried out in the research process, the

significance level () that has been taken into consideration for drawing a conclusion is

5%.

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1.6 RATIONALE

This report was assigned as a compulsory content in Research Methodology course by our course

instructor. Alongside, there are several beneficiaries of this report.

Companies providing micro-insurance service

Insurance Development and Regulatory Authority Bangladesh (IDRA)

Institute of Microfinance (InM)

Research institutes and individual researchers

Existing and potential policyholders of micro-insurance

1.7 LIMITATIONS

The research area is only limited to the district of Dhaka, the capital city of Bangladesh.

Due to shortage of resources, other districts were not taken into account. So all the

samples taken are from the Dhaka city.

The biggest limitation faced in the process of the research was due to the fact that no self

administered questionnaire was valid. Interviews needed to be carried out personally by

the group mates, which decreased the span of the sample size covered.

Some of the respondents were reluctant to answer to some of the questions in the

questionnaires. Hence, those values were entered into the database as missing values.

Due to unavailability of data regarding some of the aspects of the research paper, some

approximate values were used in certain areas of the research.

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2.0 LITERATURE REVIEW

2.1 THE MICRO INSURANCE INDUSTRY

In 1980, Grameen Bank of Bangladesh started lending to poor people without collateral security,

thereby revolutionizing finance and banking. Inspired by this scheme, a life insurance company

Green Delta of Bangladesh came forward in 1988 to provide financial security to the poor in

the form of micro insurance at a small amount of monthly premium.

After its introduction in Bangladesh, micro insurance spread among other life insurance

companies at a rapid pace. To date, almost every life insurance company in Bangladesh operates

at least more than one micro insurance project. In 2008, about two million new policies were

sold under micro insurance, compared to a million under ordinary individual life. The total micro

insurance premiums in 2008 amounted to approximately half of ordinary and other life

premiums.

For the last few years, micro-insurance portfolios of different companies have grown at an

average rate of more than 20% per annum (Ali M. K., 2009). This spectacular growth of micro-

insurance in such a short period reflects the necessity and acceptability of micro-insurance

among the masses in the country. Given that this trend is expected to continue in the years to

come, premium income under the micro-insurance portfolio will likely to overtake ordinary life

premium.

Currently the insurance industry has 77 insurance companies in Bangladesh, 75 private insurance

companies and 2 public insurance companies (Insurance Development and Regulatory Authority

Bangladesh, 2014).

The insurance sector in Bangladesh is relatively small. However, the sector has shown

remarkable growth in recent years. Parliament on 3rd

March 2010 passed two insurance laws in a

bid to strengthen the regulatory framework and make the industry operationally vibrant. The new

laws, came into effect on 18 March 2010, are Insurance Act 2010 and IDRA 2010 (Insurance

Development and Regulatory Authority Bangladesh, 2014).

While the Insurance Act 2010 has been framed with the view to synchronize functions of the

existing Insurance Department, the IDRA 2010 aims to make an independent regulatory body

that will overlook the industry and protect customers interests. The Insurance Act 2010 now

recognizes and brings under it other than the normal insurances, Islami insurances and micro

insurance businesses.

The act is making way for the micro insurance business opportunities in the insurance sector of

Bangladesh, which has a great prospect for small and medium enterprises as well as the growing

businesses, especially in the rural areas.

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2.2 TYPES OF MICRO INSURANCE IN BANGLADESH

1. General Micro Insurance

This type of micro insurance aims to provide security towards everything other than life of the

underprivileged in the economy. As a normal general insurance applies, the micro general

insurance provides the same type of security at a much lower premium. As observed through the

survey, the team recognized that this type of insurance is rare in the micro insurance scenario.

Only recently has it been started to be of use by SMEs (Small Medium Enterprises) due to

insurance being a condition for micro finance. The insurance is still limited to events of fire.

2. Micro Life Insurance

Like normal life insurances, micro life insurances provide security against the policy holders

life. The premiums are lowered to make it available for the lower income group segment of the

country. From the survey observations, this type of micro insurance is yet to be popular with the

target market.

3. Microtakaful (Islami Insurance)

This segment of micro insurance is the type of micro insurance being provided by Islami

insurance companies.

4. Deposit Pension Schemes (DPS)

This is the most popular micro insurance plan launched by the commercial life insurers. This

gained popularity not because of the benefits it provides in relation to its premium rate but

mainly because of the familiarity among the common people of a deposit scheme introduced by

some of the commercial banks with the same title. The premium rates of DPS is determined

usually by dividing the amount of sum assured with the number of premium installments payable

during the term of the insurance. A maturity, total amount of premiums paid during the term is

payable together with the accrued bonuses. A policyholder, instead of receiving the total amount

of premiums at maturity, may exercise the option of pension benefit.

2.3 PROBLEMS IN INSURANCE INDUSTRY

In Bangladesh, the term insurance is not very common. It is limited to only a certain

proportion of the urban community and almost non-existent within the rural community. This

problem arises because of a number of factors as stated by a research done on ALICO,

Bangladesh. The first and foremost of them is the fear of the public of being cheated. People

have preconceived ideas about the existing insurance policies and do not welcome the new ideas

as much as the company hopes they would. Moreover, all the documents of ALICO (and most of

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the private insurance companies) are in English rather than Bengali. On the other hand, ALICO

faces an array of problems too in Bangladesh (some of which are common to other insurance

companies). The rules and regulations regarding this sector are very strict in Bangladesh. The

company itself is afraid of cheats who provide wrong information to collect claims (some cheats

have gone even to the extent of opening fraud branches). The article states that lack of planning,

lack of capital and lack of motivation are three major reasons for which the insurance industry

has not had its desirable influence over the country. (The Lawyers and Jurists, 2013)

2.4 INSURANCE REFORM PROGRAM

The government of Bangladesh is trying to improve the insurance acceptance by embarking on a

reform program. As a first step, the government has replaced the Insurance Act, 1938 with the

Insurance Act, 2010. One of the barriers for starting an insurance company is in the

unavailability of the capital. None of the private life insurance companies have been able to raise

a capital of more than Tk. 30 crore whereas the ideal amount should have been greater than

twice. A main lacking that has been pointed out is the lack of proper training in Bangladesh

Insurance Academy (BIA) and Bangladesh Institute of Bank Management (BIBM). (Ahmed,

2011)

2.5 MICRO INSURANCE FOR POVERTY ALLEVIATION

Micro-insurance is a concept which bridges the two terms micro and insurance to provide a

solution for this insurance deprived nation. Micro insurance refers to the protection of low

income people against specific perils in exchange for regular premium payment proportionate to

the likelihood and cost of the risks available. This way, the target segment becomes more

complete: the 40% of the population of Bangladesh who are stricken by major poverty. The

major cause of this poverty is the deprivation of land and non land asset, access to education,

remunerative occupation and opportunities of diversified income sources. If productivity is

increased, it will alleviate the poverty to a significant level. To aid this fact, many insurance

companies have brought out a single comprehensive micro insurance package to cover for both

life insurance and property risks. What it ensures is that the possibility that some peril may

interrupt the income of the poor household is greatly reduced. The areas in which micro-

insurance has a prospect are mainly: dwelling, stables, stores and shops; pump sets, harvesters,

threshers; handicrafts and household productions; and personal accident and hospitalization.

Some MFI-NGOs are now offering the service of micro-insurance in the name of self

insurance. (Ali K. M., 2011)

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2.6 WHO PROVIDES MICRO INSURANCE

Micro insurance providers can be broadly divided into two categories:

a) Mainstream insurance companies (example: Delta Life Insurance Company)

b) NGOs / MFIs (example: Grameen Kalyan, Sajida Foundation, Shakti Foundation, etc.)

Among the NGO/MFIs some specialize in the provision of healthcare (example: GK), while

others provide a range of financial services as well (example: BRAC and Shakti

Foundation).(Syed M. Ahsan, 2010)

2.7 MICRO INSURANCE AND SME

In Bangladesh, there exist a huge number of small and medium enterprises. The definition of

SMEs, though poses many controversies, consistently point out that the businesses contain a

small number of employees (below 25 as per Bangladesh Bank) and a small spread of fixed

assets other than land and building (below Tk. 5,000,000 as per Bangladesh Bank) (Bangladesh

Bank, 2010).

In many cases, the assets held by these SMEs are insured by insurance firms. As per a South

African case study, it was stated that low-income entrepreneurs are particularly vulnerable to

risks. Lacking adequate financial and other assets, the poor are exposed to the smallest economic

shocks. Their vulnerability is exacerbated by the fact that low-income persons tend to live and

work in riskier environments than wealthier people, with a greater likelihood of illnesses,

accidents and thefts (Aliber, 2001).

This is also very true in case of Bangladesh. The case study also pointed out that as the family of

most of the entrepreneurs depends highly on income from this business, the insurance policies

specifically aimed towards them can also be categorized as micro-insurance.

2.8 MICRO INSURANCE IN PUBLIC HEALTH

One major prospect of micro insurance is the public health sector. It has been stated that micro-

insurance can lower both the ongoing, preventive health cost and also the high catastrophic

health cost for families affected by poverty in Bangladesh. The micro-insurance scheme of India

has been criticized and it has been stated that that scheme will not apply to Bangladesh. This

micro-insurance will reduce the tendency of rural people to turn to minimally-trained village

pharmacists or traditional healers. Instead they will seek professional healthcare due to risk

pooling. But to achieve all these, the initiatives must exercise adept level of professional

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management, product development, management information system and re-insurance (Werner,

2009).

2.9 MICRO INSURANCE AS A PROMISING SECTOR

The concept of micro insurance stems from Dr. Mohammad Yunuss idea of micro credit lending

which initially began in 1980s. The first insurance company to offer micro insurance was Green

Delta of Bangladesh. Since then, micro insurance in Bangladesh has come a long way and

currently it constitutes on average 30% of the income generated. Over the last few years, micro

insurance growth has been at around 20% on average, which is quite commendable. In the

formal side, the most popular scheme is the Deposit Pension Scheme (DPS), which gained

popularity not because of its competitive premium rates, but because of peoples familiarity with

the term DPS as it was introduced earlier by some commercial banks. During early 2000, the

Government of Bangladesh started permitting Islamic Insurance companies; their insurance plans

are known as Takaful. The informal sector of micro insurance is dominated by NGOs. Almost

all major NGOs have micro insurance schemes which cover various factors such as outstanding

loan balance, health, disability and in some cases even provide one time monetary benefit. In

many cases, these micro insurance schemes are financed partly by donor funds. One of the major

challenges faced by micro insurance is the lack of proper regulation. While there are clear

guidelines for general insurance practices, rules and regulations are not as well put for micro

insurance plans. For a healthy growth and consistent growth in the micro insurance segment, a

proper set of rules and regulations must be set up and implemented (Ali M. K., 2009).

3.0 METHODOLOGY

3.1 DATA COLLECTION

3.1.1 Primary source of data

Existing policyholders of different micro-insurance policies have been interviewed

located within the area of Dhaka city.

Micro-insurance policymakers have been interviewed to understand the behavioral

pattern of the policyholders and how it affects the policy.

3.1.2 Secondary source of data

It includes various journals and reports on the Micro-Insurance sector of Bangladesh. By

reviewing journals and reports on the micro-insurance sector of Bangladesh, we can understand

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the key factors that are posing barriers to the effectiveness of the policies. Past reports also

present to us the dimensions that have already been ventured into by researchers, allowing us to

save time and money and the opportunity to look into new ventures ourselves.

All of the secondary sources of data used in the research process have been mentioned in the

Reference section of the report.

3.2 SAMPLE SIZE

Currently, micro-insurance covers 6.5 million lives in Bangladesh (Werner, 2009). So, this

population size can be used to determine the number of existing policyholders that we need to

survey. In this case, the targeted sample size can be determined with the following formula:

Here,

n = Sample size

N = Population size

p = Proportion of the population who are micro-insurance policyholders

q = Proportion of the population who are not micro-insurance policyholders

z = Reliability, depending on the level of significance

do = Precision

We assume the product of p and q to be 0.25 (the maximum possible values). For a level of

significance of 5%, the value of z is 1.96. We assume a precision, do of 5%. In that case, the

sample size is:

However due to time and resource limitation, the actual sample size that could be considered for

the whole research process has been 40. For this sample size and using the same formula, the

precision of the research carried out has been calculated below.

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So, Precision = do = 15.50%

3.3 SAMPLING TECHNIQUE

For the purpose of this study, non-probability sampling was used.

Non-probability sampling represents a group of sampling techniques that help researchers to

select units from a population that they are interested in studying. The main purpose for selecting

the non-probability sampling is the limited time and workforce, lack of access to the entire target

population and practicality (easier, quicker and cheaper).

We have taken a combination of judgmental and snowball approaches in coming up with the

desired sample of the policyholders. We have employed the judgmental approach in selecting the

areas from which surveys will be taken and in selecting the companies that were interviewed

during the research process. We have employed the snowball approach in selecting individual

policyholders, since information about them is not available to public at large.

3.4 QUESTIONNAIRE DEVELOPMENT

After finalizing the co-ordination schema to etch out the variables that will be used in the

research process [Appendix 2], questionnaires were designed to carry out the survey [Appendix

1].

3.4.1 Categories of questionnaire

To reach out to the interviewees, two questionnaires were formulated:

a) Questionnaire for the existing policyholders of micro-insurance policies:

This is the main questionnaire for the research since most of the variables listed in the co-

ordination schema are aimed at the existing policyholders of micro-insurance.

b) Questionnaire for the micro-insurance policymakers:

To cross check some of the complex variables and to check for the coverage of micro-insurance,

interviews were carried out to some of the companies providing micro-insurance services. The

names of the personnel who were interviewed are present in the Acknowledgements.

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For all the two questionnaires formulated, the respondents will be interviewed since many of the

policyholders may not know how to read or write. For their benefits, the first questionnaires

addressed towards the existing policyholders of micro-insurance will be translated into Bengali

so that the respondents understand the questions better. The interview of the micro-insurance

policymaking companies will be carried out in English.

3.4.2 Question patterns

For the questionnaire aimed towards the existing policyholders of micro-insurance, the following

answering bases were used:

a) Subjective questions

b) Yes/No questions: Here the answer of Yes has been given a value of 1 and the answer

of No has been given a value of 0

c) Checklist of items

d) 5 point Likert scale: The value of the question patterns range from -2 to +2

For the interview questionnaire aimed towards the policymakers, subjective questions were

asked to gather relevant information.

3.4.3 Pre-testing

The questionnaire aimed towards the existing policymakers was pre-tested among 7 respondents.

On carrying out the pre-test, the following changes were made:

a) For question number C1, the first option, Cash upfront was divided into two separate

options of Through office and Through agents.

b) For question number C5, the previously subjective question was changed to include the

options Fraud agents, Fraud companies, Fraud paperwork and Others for the

reason of specificity.

3.5 DATA COLLECTION:

The data collection spanned over a period of 4 weeks. During this time, several areas were

covered up in an aim to carry out interviews with probable respondents. The major limitation

faced in this process was that the group had to take interviews of the respondents instead of

handing them a self administered questionnaire.

The areas that were taken into consideration are listed below.

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Dhaka University

Kataban

Nilkhet

Uttara

Eskaton

Shahbagh

Dhanmondi

3.6 DATA ANALYSIS

For the purpose of data analysis, the collected data were entered into SPSS and different

statistical tests were administered. The tests that were carried out include:

a) One sample T-Test: Hypothesis tests were carried out for different variables where the

sample means of the data collected for those variables were used to check whether the

population means of those variables conformed to different standard values.

b) Frequency analysis: The frequency of answers as per the choices to different questions

was presented where necessary and the results were explained as to how it can be related

to the effectiveness of micro-insurance.

c) Correlation coefficients: For some variables, the correlation has been found out to see the

strength and direction in which they move.

14

4.0 RESEARCH FINDINGS

4.1 FINDINGS REGARDING KNOWLEDGE OF POLICYHOLDERS

4.1.1 Knowledge regarding number of companies

As already stated in the preceding sections of the report, the total number of insurance companies

in Bangladesh is 77 (Insurance Development and Regulatory Authority Bangladesh, 2014) of

which as high as 60 companies provide micro-insurance facilities (Mizan R. Khan, 2013).

Moreover, majority of the respondents are policyholders of micro life insurance. There are in

total 30 companies which provide life insurance (Insurance Development and Regulatory

Authority Bangladesh, 2014). Thus, for the hypothesis test carried out below, it has been

assumed that all of these life insurance companies provide micro-life insurance.

In this section, the claim that the policyholders do not know the correct number of companies has

been tested statistically. It has been assumed, as stated above, that the correct number of

companies is 30. Thus, the correct number of companies other than the company of which the

respondent is a client of is 29.

The set of hypotheses taken into consideration and the tables generated by SPSS are given in

[Appendix 5], under the subtopic of Hypothesis 1. A simpler table showing the mean of the

sample and the significance level has been given below.

Sample mean ( ) 4.56

Significance level for 2 tailed test 0%

The mean perceived value of the sample (x ) in this context is only 4.56 which shows, to a very

large extent, the respondents are unaware of the correct number of companies.

The significance level of the two tailed test carried out shows that the value is 0% (as underlined

in the table above). This means that at any significance level above 0%, we can reject the null

hypothesis that the mean number of companies perceived by policyholders is 29. The alternate

hypothesis that the mean number of companies perceived by the policyholders is not 29 is

accepted.

Conclusion: At a significance level of 5%, the policyholders of micro-insurance do not have the

appropriate knowledge regarding the number of companies currently in the industry.

15

4.1.2 Knowledge regarding other programs of company the respondent is a client of

In this section, we will check whether the respondents think that they have good idea about the

other insurance offers of the company that he/she is a policyholder of. One assumption that is

made here will be that even if half the respondents feel that they have a good understanding of

the other programs being offered by the insurance company that he/she is a policyholder of, we

can conclude that the micro-insurance companies are effective in this context.

The set of hypotheses taken into consideration and the detailed tables generated by SPSS are

given in [Appendix 5], under the subtopic of Hypothesis 2. A simpler table showing the

frequency distribution of the answers and the significance level has been given below.

Knowledgeable Unknowledgeable

Frequency distribution 31 9

Proportion of frequency 22.5% 77.5%


From the tables it can be seen that the sample mean for this variable as received from the

questionnaire is 0.225. This means that only 22.5% of the respondents claimed that they had

knowledge regarding the other programs of the same insurance company.

The significance level for a two tailed test is 0% in this context. As this hypothesis testing had

been a one tail test, the significance level for two tail test is to be divided by 2 to get that of the

one tail test. Even after doing that, the significance level is 0%.

Thus, it can be concluded that for any significance level greater than 0%, the null hypothesis that

at least half the policyholders have a good about the other programs of the company that they

are the policyholder of is rejected and the alternate hypothesis that less than half the

policyholders believe they have good idea about the other programs of the company that they

are the policyholder of is established.

Conclusion: At a significance level of 5%, a proportion of less than 50% of the policyholders of

micro-insurance have the appropriate knowledge regarding the other micro-insurance programs

that the company that he/she is a client of offers.

4.1.3 Knowledge regarding the chosen micro-insurance policy

In this section, we will check whether the respondents think that they have a good understanding

of the micro-insurance program that they are currently under. In this case too, the assumption

that if half the respondents feel that he/she has good knowledge regarding the chosen program,

the micro-insurance companies can be tagged as being effective in this context.

16

The set of hypotheses to be considered for this part and the tables generated by SPSS are

included in [Appendix 5] under the sub heading of Hypothesis 3. A simpler table showing the

frequency distribution of the answers and the significance level has been given below.

Knowledgeable Unknowledgeable

Frequency distribution 24 16

Proportion of frequency 0.6 0.4


From the above tables, we can see that the sample mean for this category is 0.60. This means that

60% of the respondents believe that they have good understanding of the micro-insurance policy

that he/she has taken up.

The hypothesis test carried out gives its result in the next table. The significance level being

shown in this context is 21% for a two tailed test. However, this is a one tail test for which this

level of significance must be divided by 2. Thus, the significance level for the one tail test is

10.5%.

So it can be said that for any value of significance level below 10.5%, the null hypothesis that at

most half the policyholders believe they have a good understanding of the chosen insurance

program cannot be rejected and the alternate hypothesis that more than half the policyholders

believe they have a good understanding of the chosen insurance program cannot be established.

For any value of significance level above 10.5%, the null hypothesis that at most half the

policyholders believe they have a good understanding of the chosen insurance program is

rejected and the alternate hypothesis that more than half the policyholders believe they have a

good understanding of the chosen insurance program can be established.

Conclusion: At a significance level of 5%, it cannot be concluded that a proportion more than

50% of the policyholders of micro-insurance have appropriate knowledge regarding the chosen

micro-insurance policy.

4.1.4 Knowledge regarding the reason for choosing the micro-insurance policy

In this section, the answers of the question to A5 [Appendix 1] has been arranged into two

groups: whether the respondents have taken the policy knowing its repercussions or whether they

have taken the policy by being affected by the words of another person or party.

A hypothesis test has been carried out below to check the claim whether statistically the

proportion of the population aware of the repercussions of the policy is greater than 50%. The set

17

of hypotheses to be considered for this part and the tables generated by SPSS are included in

[Appendix 5] under the sub heading of Hypothesis 4.

A simpler frequency table and the values of the significance level as per the hypothesis test has

been given in the table below.

Knowledge of the

repercussions

Influence of other

party

Frequency 28 12

Proportion p = 0.70 q = 0.30


From the above table, we can see that the significance level for two tail test is 1%. But as the

hypothesis in this context is a one tail test, this percentage must be divided by 2. So the

significance level for one tail test is 0.5%.

Thus, it can be said that for a level of significance less than 0.5%, the null hypothesis that no

more than 50% of the policyholders know the reason for choosing the policy that they are under

cannot be rejected and the alternate hypothesis more than 50% of the policyholders know the

reason for choosing the policy that they are under cannot be established. For a level of

significance greater than 0.5%, the null hypothesis can be rejected and the alternate hypothesis

that more than 50% of the policyholders know the reason for choosing the policy that they are

under can be established.

Conclusion: At a level of significance of 5%, it can be concluded that the more than half the

policyholders of micro-insurance know the reason for choosing the micro-insurance policy.

4.1.5 Synthesis of knowledge of policyholders

To combine the results from all the simple variables into the parameters, the conclusions from

the individual simple variables have been rated either 1 or 0. A value of 1 means that in

terms of that simple variable, the micro-insurance in Bangladesh.

For the knowledge of the policyholders, the simple variables and their corresponding values as

per the conclusions are listed in the table below:

Simple variable Conclusion Value

Knowledge regarding

number of companies

The policyholders do not have appropriate

knowledge regarding the number of companies.

0

18

Knowledge regarding other

programs of the company

Less than half the policyholders have appropriate

knowledge regarding other policies of the company.

0

Knowledge regarding the

chosen micro-insurance

policy

More than half the policyholders do not know the

reason regarding the choice of the micro-insurance

policy.

0

Knowledge regarding the

reason for choosing it

More than half the policyholders know the reason

for choosing the policy.

1

Average value 0.25

4.2 FINDINGS REGARDING CLAIMS OF MICRO-INSURANCE

4.2.1 Findings regarding background check on claims

In the Insurance industry claims turn out to be a major hurdle for the policyholders to be

applying for claims. The first stage of the claim process in micro insurance is for the policy

maker to validate the claim of the policyholder by performing a thorough background check via

independent third party.

In the case of our sample, we first tested for how many of the policyholders within the sample

have actually claimed for insurance and secondly we tested how thorough the background check

was according to the policyholders who have claimed their insurance.

In the aspect of how many insurance claims, we made a frequency table as shown below. The

table helps us understand how many of our sample has actually made a claim. Within the sample

only 7 policyholders have made a claim in the tenure of their policy, while 32 policyholders have

never applied for an insurance claim.

Made an Insurance Claim

Frequency Percentage

Yes 7 17.5

No 32 80.0

Total 39 97.5

Mean .18

19

Significance Value (two tailed) .006

In the first part of this section we will check as to whether any of our samples have made a claim

on their insurance. An assumption here is that the sample policyholders have not yet made a

claim against their insurance scheme.

The set of hypothesis taken into consideration and detailed tables generated from SPSS are given

in [Appendix 6], under the subtopic Hypothesis 1. A simpler table of showing the frequency

distribution of the answers, the mean value and the significance value obtained above.

We can observe from the table that the sample mean for this variable as received from the

questionnaire is 0.18. This means that only 18% of the sample has made claims against their

insurance scheme.

The significance for a one tailed test is 0.06% for this simple variable. In case of a two tailed test,

the significance value would have been divided by 2 to get that of a one tailed test, and obtain

0.03%.

Hence it can be concluded that for any significance level greater than 0.03% the null hypothesis

that a significant proportion of the policyholders have not made claims is rejected and the

alternate hypothesis a significant proportion of the policyholders have made claims is

established.

In the second part of this segment we try to find out whether the claims that have been made

within the sample were validated with proper background check. The assumption we have made

for this part is that none of the claims that were made, were validated with a thorough

background check.



distribution of the answers, the mean value and the significance value obtained is given below.

Mean Significance Value

Thorough Background Check 0.78 0.00

From the table it can be seen that the sample mean for the simple variable as received from the

questionnaire is 0.78. The significance level for the two tailed test is 0 in this context. If we turn

it into a one tailed test and divide the significance value with 2, we would still obtain a value of

zero.

20

Thus it can be concluded for any significance level greater 0%, the null hypothesis that the

policyholders perceive that the background check on claims is not thorough is rejected and the

alternate hypothesis that the policyholders perceive that the background check on claims is

thorough is established.

Conclusion:

At significance level of 5%, a significantly large number of policyholder has made a

claim against their insurance scheme.

At a significance level of 5%, the policyholders of micro-insurance perceive that the

background check on claims is thorough.

4.2.2 Findings regarding acceptance rate of claims

In this segment we will test to see whether the claims that have been made by the respondents

were accepted by the policymaker. Here again we assume that the acceptance rate of the claims

made by the respondents is equal to or less than 15. 15% is the industry standard rate of

acceptance. For which we test whether the respondents of our sample have a different rate or not.




Frequency Mean Significance Value

Acceptance Rate of

Claims

5 0.48 0.000

We can see from the table that the sample mean for the simple variable is 0.48 based on the

questionnaires. This means that 48% of the respondents have experienced their claim to be

accepted by the policymaker.

The significance level for this simple variable is 0.000 in a two tailed test. Considering a one

tailed test, we divide the significance value by 2 and still obtain 0.000. We would still have a

significance level of 0%.

We can come to the conclusion that for any significance level greater than 0.0%, we reject the

null hypothesis that acceptance rate of claims is equal to or less than zero and the alternate

hypothesis acceptance rate of claims is greater than zero is established.

Conclusion: With a significance level of 5%, majority of the respondents say that their claims

have been accepted by the policy makers.

21

4.2.3 Findings regarding denial of claims

In this section we will observe as to why there was any denial of claims amongst the

respondents.


Claims Made 7 100

Claims Denied 2 28.6

Reasons: 1. Claim before maturity not provided

2. Policy nullified.

As you can see in the table above, a total of 7 insurance claims were made within our sample,

while 5 of the claims were accepted, only 2 were rejected. As the reason show, one of the claims

were rejected because of the firms policy of not providing claim before maturity and another

being that the policy was made void.

If we look at the percentages we can see that 28.6% of the claims made were rejected. Although

the percentage appears to be high, we must remember that 100% means only 7 claims. So the

percentage can be said to be exaggerated.

Conclusion: The information obtained is not enough for us to measure the effectiveness in the

denial of claims of policyholders. Value of Effectiveness: 0.5

4.2.4 Findings regarding time of claims

In accordance to question number B6 [Appendix 1], this section looks into how much time is

taken for the policymakers to pay off the premium of a claim.

In the sample only four respondents have received their claim amount during the survey. Out of

five of the claims which were accepted, four claims were paid off within a maximum of 3

months and a minimum time of zero. The variation cant be used as an average amongst the

micro insurance industry as the number of claims received is low.

Time Taken for Claim to be Given

(in months)


0 1 0.25

1 1 0.25

2 1 0.25

22

3 1 0.25

Total 4 100

Conclusion: Although we can say that 4/5 or 80% of the claims were paid off, however we cant

say whether this aspect of Insurance Claim is effective or not because there are only four

samples, causing each time taken to have an equal percentage of 25. Value of Effectiveness: 0.5

4.2.5 Findings regarding satisfaction of policyholders relating to claims

We divided this section of the findings into two parts. The satisfaction of the policyholders is

firstly tested with satisfaction with the time taken for the company to evaluate the claim and

respond and the time taken for the company to provide the claimed amount. Secondly we test

and find out the satisfaction of policyholders with the claim amount they have obtained.


in [Appendix 6], under the subtopic Hypothesis 4 & 5. A simpler table of showing the

frequency distribution of the answers, the mean value and the significance value obtained are

given accordingly.


Satisfaction with B4 and B6 1.00 0.089

B4 = Satisfaction with time taken for claim evaluation and response.

B5 = Satisfaction with time taken for the claim amount to be given.

We can see that the sample mean for the first satisfaction related variable is 1.00.The

significance value for the satisfaction variable is 8.9% in a two tailed test. Considering a one

tailed test for this simple variable, we obtain the significance level of 4.45%.

Hence we can come to the conclusion that any significance level greater than 4.45% would mean

that we reject the null hypothesis of policyholders are not satisfied with the time taken to

evaluate and provide the claim amount and establish that claim that they are indeed satisfied

with the processes.

The second part of this segment is whether the respondents are happy with the premium amount

they receive after a claim is made. The claim for this part is that the policyholders are satisfied

with the claim amount that they receive.

23


Satisfaction the Amount of Claim Received 0.40 0.587

From the table we can see that the sample mean for the variable is 0.40 in this context. We can

also see that the significance level for the variable is 58.7%. Thus the significance level for a one

tail test is 29.4%.

Finally we can come to the conclusion that any significance level greater than 29.4% would

result in rejection of the null hypothesis, the policyholders are not satisfied with the claim

amount, and while establishing the alternate hypothesis that they are satisfied. For a

significance level lower than 29.4%, the null hypothesis cannot be rejected and the claim cannot

be established.

Conclusion:

With a significance level of 5%, we can say that the policyholders are satisfied with the

time taken for claim evaluation and time taken for the claim to be received.

For the significance level of 5%, we must accept the null hypothesis that respondents are

not satisfied or neutral with the claim amount they receive.

4.2.6 Synthesis of micro-insurance claims



terms of that simple variable, the micro-insurance in Bangladesh is effective. A value of 0 on

the other hand means that it is ineffective

For the aspect of claims of the policyholders, the simple variables and their corresponding values

as per the conclusions are listed in the table below:


Background Checks on

Claims

Insurance Claim Respondents have claimed

against their insurance. 1

Thorough Background Checks Respondents

believe that their claims have been followed by

proper background checks.

1

Acceptance Rate of Claims More than zero respondents have said that

acceptance rate of claims is high

1

24

Denial of Claims Not enough information to make a valid value of

effectiveness

0.5

Time of Claims Not enough information to make a valid value of

effectiveness

0.5

Satisfaction relating to

Claims

Satisfaction with B4 and B6 1

Satisfaction with Amount Realized from Claim 0

Average value 0.7

4.3 FINDINGS REGARDING COLLECTION AND RECOVERY OF PREMIUM

4.3.1 Findings regarding medium of premium collection

From the research, it has been found out that the micro-insurance policyholders usually collect

the premiums through three major ways:

a) Through their offices: The policyholders have to come over to the offices of the

respective micro-insurance company that they are the clients of and have to pay the

premium over the counter to an employee of the company. This is mostly applicable for

urban or semi-urban areas, where setting up an office appears to be useful for the

company.

b) Through agents: For mostly the rural population, the policyholders use this method of

premium collection. Independent agents holding the authorized license provided to them

by the Insurance Development and Regulatory Authority (IDRA) are appointed to go to

these particular locations on selected days and collect the premiums from the

policyholders.

c) Bank accounts: Instead of directly providing the premium to the company, on many

instances, the policyholders pay the amount through a bank. This is advantageous for the

company because this method increases their geographical reach.

A table showing the frequency of the different medium is given below.

Medium Frequency Percentage

Through office 15 37.5%

25

Through agents 16 40%

Through bank accounts 6 15%

All of the three mentioned above 1 2.5%

Other methods 2 5%

Conclusion: There are enough methods of premium collection to tackle the different

geographical locations of Bangladesh.

4.3.2 Findings regarding considerations during premium collection

In this section, two different considerations from the perspective of the policyholders while

paying the premiums were reflected upon. Hypotheses tests have been done on both of the

considerations. They are:

a) Consideration of the policyholders occupation (whether the policymakers consider the

occupation of the policyholder, during the process of premium collection)

b) Consideration of the policyholders expense patterns (whether the policymakers consider

the expense patterns of the policyholder, during the process of premium collection)

For these two variables, a bivariate correlation analysis at 1% significance level has been carried

out [Appendix 7] which shows that the correlation coefficient for these two variables is 0.884,

meaning that the correlation between these two variables is quite high.

For consideration regarding the occupation of the policyholders, a hypothesis test was carried out

(the details are in [Appendix 8] under the subheading of Hypothesis 1) where the claim that

the process of premium collection takes into consideration the occupation of the policyholders

was tested.

For that test, the findings are shown in the table below:


Significance level for 2 tailed test 6.6%

From the table above, we can see that the significance level for two tailed test is 6.6%. Thus, the

significance level for one tailed test will be 3.3%.

Thus, for any significance level higher than 3.3%, the null hypothesis can be rejected and the

claim that the process of premium collection takes into consideration the occupation of the

policyholders can be established.

26

For any significance level lower than 3.3%, the null hypothesis cannot be rejected and the claim

that the process of premium collection takes into consideration the occupation of the

policyholders cannot be established.

For consideration regarding the expense pattern of the policyholders, a hypothesis test was

carried out (the details are in [Appendix 8] under the subheading of Hypothesis 2) where the

claim that the process of premium collection takes into consideration the expense patterns of the

policyholders was tested.

For that test, the findings are shown in the table below:



From the table above, we can see that the significance level for two tailed test is 9.9%. Thus, the

significance level for one tailed test will be 4.95%.

Thus, for any significance level higher than 4.95%, the null hypothesis can be rejected and the

claim that the process of premium collection takes into consideration the expense patterns of the

policyholders can be accepted.

For any significance level lower than 4.95%, the null hypothesis cannot be rejected and the claim

that the process of premium collection takes into consideration the expense patterns of the

policyholders cannot be accepted.

Conclusions: At a level of significance of 5%,

It can be concluded that the process of premium collection takes into consideration that

the occupation of the policyholders.

It can be concluded that the process of premium collection takes into consideration that

the expense patterns of the policyholders.

4.3.3 Findings regarding incidence of frauds

The hypothesis tested in this section of the report deals with the incidence of fraud. The claim for

the hypothesis being tested in this scenario is the proportion of population who has been the

victims of fraudulent activities is not 0.

The set of hypothesis for the testing of this claim is given in [Appendix 8] under the subheading

of Hypothesis 3. The frequency distribution of the responses for this question along with the

significance level received through the hypothesis test is given in the table below.

27

Has faced fraud in

micro-insurance

Has not faced fraud in

micro-insurance

Frequency 7 33

Proportion p = 0.175 q = 0.825


From the table above, we can see that the significance level for two tailed test is 0.6%. Thus, for

a significance level greater than 0.6%, the null hypothesis can be rejected and the alternate

hypothesis showing the claim that the proportion of population who has been the victims of

fraudulent activities is not 0 can be accepted.

For a significance level lower than 0.6%, the null hypothesis cannot be rejected and we cannot

conclude that the claim is true.

Regarding the awareness of fraud, the following frequency table shows which types of the three

types of fraud: fraud agents, fraud companies and fraud paperwork are the respondents aware of.

Frequency Proportion

Fraud agents 14 0.32

Fraud companies 16 0.36

Fraud paperwork 2 0.05

Missing values 12 0.27

Conclusions:

At a significance level of 5%, it can be concluded that the proportion of population who

has been the victims of fraud is not zero, and is thus significantly large.

27% of the respondents are not aware of any sort of fraudulent activities, which is quite

alarming.

4.3.4 Findings regarding handling of frauds

The respondents seemed to have a generic negative perception of the companies when it came to

how effectively the frauds were being handled. The claim that according to the policyholders,

the companies do not deal with frauds effectively has been tested in this section. The detailed

table generated by SPSS has been given in [Appendix 8] under the subheading of Hypothesis

4.

28

A simpler version of that table with the most important points is shown below:

Sample mean ( ) -0.16


As the significance level for two tailed test is 59%, that for a one tailed test will be 29.5%. Thus,

for significance level of greater than 29.5%, the null hypothesis will be rejected and the claim

that the policyholders believe that the companies do not deal with frauds in an effective manner

will be established.

For significance level of less than 29.5%, the null hypothesis cannot be rejected and the claim

that the policyholders believe that the companies do not deal with frauds in an effective manner

cannot be established.

Conclusion: At a significance level of 5%, it cannot be concluded that the companies do not deal

with frauds effectively.

4.3.5 Findings regarding time of recovery of premium after maturity

From the managerial interviews carried out, the interviewees confirmed that the time of payment

of all the aggregated amount of the premium usually took two months after all the necessary

paperwork were completed by the policyholders subsequent to the maturity of the insurance (if

applicable).

Thus, the mean of the answer to question C8 [Appendix 1] has been tested against the value of

2. The claim being made in this case is that the actual time of recovery of premium is greater

than 2 months after the maturity.

The tables generated by SPSS for the test of this hypothesis and the set of hypotheses being

considered to test the claim made above have been included in [Appendix 8] under the

subheading of Hypothesis 5. A simpler table of the most important values is given below:

Sample mean ( ) 4.11 months


From the table above, we see that the mean from the respondents is 4.11 months. When tested

against the claim being made, the significance level for two tailed test is 0.6%, meaning that the

significance level for one tailed test is 0.3%.

So at a significance level of greater than 0.3%, the null hypothesis can be rejected and the claim

that the actual time of recovery of the premium following the maturity is more than 2 months

29

can be accepted. At a significance level of less than 0.3%, the null hypothesis cannot be rejected

and it cannot be concluded that the actual time of recovery of the premium following the

maturity is more than 2 months.

Conclusion: At a significance level of 5%, the claim that the actual time of recovery of

premium following the maturity is greater than 2 months is accepted. The micro-insurance of

Bangladesh is ineffective in context of this simple variable.

4.3.6 Findings regarding satisfaction about amount of premium recovered

The policyholders were asked to mention how satisfied they were on the amount of premium

recovered following the maturity from past experiences, if applicable. With the aggregate result,

a claim that the policyholders are satisfied regarding the amount of premium recovered after

maturity was tested.

The details of the test are present in [Appendix 8] of the report under the subheading of

Hypothesis 6. A table showing the findings of that test has been given below.



Thus, we can see from the above table that the significance level for two tailed test is 55.7%.

This means that the significance level for one tailed test is 27.9%.

So, at a significance level of greater than 27.9%, the null hypothesis can be rejected and the

claim that the policyholders are satisfied regarding the amount of premium recovered after

maturity can be accepted.

At a significance level of lower than 27.9%, the null hypothesis cannot be rejected and it cannot

be concluded that the policyholders are satisfied regarding the amount of premium recovered

after maturity.

Conclusion: At a significance level of 5 percent, the claim that the policyholders are satisfied

with the amount of premium that they are recovering after the maturity cannot be accepted.

Thus, in this case, the micro-insurance is ineffective.

4.3.7 Synthesis of micro-insurance premiums



terms of that simple variable, the micro-insurance in Bangladesh.

For the parameter of micro-insurance premiums, the values are given in the table below:

30


Medium of premium

collection

There are three major ways of premium collection,

which is effective in context of Bangladesh.

1

Considerations regarding

premium collection

The process of premium collection does not take into

consideration the occupation of the policyholders.

0

The process of premium collection does not take into

consideration the expense patterns of the policyholders.

0

Incidence of fraud The proportion of population who has encountered fraud

is significantly large.

0

A large proportion of the population is not aware of the

types of fraud that are most common.

0

Handling of frauds It cannot be concluded that the companies do not handle

fraud effectively.

1

Time of recovery of

premiums after maturity

The time of recovery of premium after maturity is

significantly larger than 2 months (which was the

average time claimed by the companies).

0

Satisfaction about amount

of premium recovered

The policyholders are not satisfied regarding the amount

of premium recovered following the maturity

0

Average value 0.25

4.4 FINDINGS REGARDING EMPLOYEES OF MICRO-INSURANCE

4.4.1 Findings regarding instances of misbehavior by employees

In this section we firstly look into whether the policyholders of micro insurance have ever faced

moments where the employees of the company misbehaved. Here we assume that the instances

of misbehavior of employees are zero or less than zero.




31

Mean Significance Level

Misbehavior by Employees 0.10 0.044

As we can see from the table, the sample mean obtained from the questionnaires for this simple

variable is 0.10. This means that only 10% of the respondents have experienced instances of

misbehavior by employees/agents of the insurance firm.

The level of significance for a two tailed test in this context is 0.044. If we consider a one tailed

test then the significance level would be divided by 2 and result in being 0.022 or 2.2%.

This means that for any level of significance greater than 2.2%, the null hypothesis the mean of

instances of misbehavior by employees/agents is zero will be rejected, while establishing the

alternate hypothesis mean of instances of misbehavior of employees is greater than zero.

Conclusion: With a significance level of 5%, we can conclude that the respondents have

experienced instances of misbehavior by employees or agents. Value of Effectiveness: 0

4.4.2 Findings regarding perception of employee behavior

In this part of the findings we test as to what the perception of policyholders is regarding the

behavior of employees of the insurance firms. For this case we assume that the level of

satisfaction is equal to or below zero signifying that it is unsatisfactory.





Perception of Employee

Behavior

1.08 0%

As we can observe from the table that the mean value for the variable is 1.08, signifying that the

respondents have a satisfactory perception towards the behavior of employees. Thus the claim is

that the perception of the policyholders regarding employee behavior is positive.

The level of significance for a two tailed test in this context is 0%. If we consider a one tailed

test, the significance level would be divided by 2 and result in being 0% again brining no change.

32

We can conclude here by saying that for any level of significance above 0%, the null hypothesis

the policyholders are not satisfied by the employee behavior and do not have a positive

perception, and the claim that they are indeed satisfied is established.

Conclusion: With a level of significance of 5%, we can conclude that the perception of

policyholders towards employee behavior is satisfactory.

4.4.3 Findings regarding the amount charged by agents

With this section, we test to see whether the amount being charged as commission or premium

rate is acceptable by the respondents or not. For this case we hold the industry standard of agent

commission of 15% and check whether the respondents believe the agents deserve the amount.





Perception of Acceptable

Commission Fees

11.50 0.209

From the table we can extract the sample mean for the variable to be 11.50. This means that

according to our respondents the average rate of commission or premium rate should be around

11.5%.

The significance level for a two tailed test in this context is 0.209. If we consider a one tailed test

for the same variable the significance value would be divided by 2 and 0.104 can be obtained.

Thus we can come to the conclusion that for a level of significance greater than 10.4%, the null

hypothesis that the deserved rate of commission for agents is 15% is rejected and the alternate

hypothesis the deserved rate of commission for agents is not 15% stands.

Conclusion: With a significance level of 5%, the null hypothesis is not rejected and we come to

the conclusion that the deserved rate of commission for agents is 15%. For such that any

significance level under 10.4% can be considered the same, so at 5% the commission of 15%

(industry standard) and the sample mean value of 11.5% can be considered the same. Value of

Effectiveness: 1

4.4.4 Findings regarding unrecorded payments

In the insurance industry, unrecorded payments can be held as the precursor for attempts at

fraudulent activities. In this section we test as to whether the respondents have ever faced

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instances of unrecorded payment. Our assumption lies on the hypothesis that the mean of

instances of unrecorded payment is less than or equal to zero.





Instances of Unrecorded

Payment

0.18 0.6%

Extracting the sample mean value of 0.18 from the table above we can say the about 18% of the

respondents have faced instances of unrecorded payment. Thus, the claim that we want to test is

that the number of times there were unrecorded payments is significantly greater than zero.

The significance level for the simple variable, in this context, 0.6%. If we convert this two tailed

test into a one tailed test, the level of significance is divided by 2 and we obtain 0.3%. In the end

this means that for any level of significance higher than 0.3%, the null hypothesis is rejected and

the claim is established.

Conclusion: With a significance level of 5%, the null hypothesis is rejected and we can say that

there are instances of unrecorded payments within the policyholders. This means that there are

chances that these respondents are on the stepping stone of an attempt of fraudulent activity.

Value of Effectiveness: 0

4.4.5 Findings regarding knowledge of employees

This section of the findings understands the findings regarding knowledge of the employees. The

test of knowledge has been divided into two parts. The first part understands the perception of

the policyholders towards the knowledge of the micro insurance employees. The second part

deals with the knowledge in a subtle way, by asking as testing whether there have been instances

of failure to answer.


in [Appendix 9], under the subtopic Hypothesis 5 & 6. A simpler table of showing the mean

value and the significance value obtained is given below.

34

(a) Employee knowledge


Knowledge of Employees 1.16 0%

The sample mean for the variable as on the table is 1.16. This means that from the sample,

respondents believe that the employees are knowledgeable. Thus, that is the claim that we want

to prove via the hypothesis that we are testing.

The level of significance of a two tailed test in this context is 0%. If we assume a one tailed test

for the variable then the significance level would still be 0%.

We can come to the conclusion that that for any level of significance greater than 0%, we can

reject the null hypothesis the employees are not knowledgeable and establish the claim that

they are in fact knowledgeable.

Conclusion: With a significance level of 5%, we may conclude that the employees in the micro

insurance industry are knowledgeable by rejecting the null hypothesis. The more knowledgeable

the employees are, the more effective the micro insurance scheme. Value of Effectiveness: 1

(b) Failure to Answer

The perception of the policyholders can be biased and gullible, for which we did a second test

which in a subtle manner looks into the fact of knowledge of employees of the micro insurance

companies. In this case we assume that the mean of the failure to answer is equal to zero.


Failure to Answer 0.25 0.1%

The sample mean for the variable as shown above is 0.25. This means that 25% of the

respondents had instances where the employee was unable to answer the queries of the

policyholders.

The significance level for a two tailed test of the variable is 0.001 in this context. If we consider

a one tailed test the level of significance will become 0.05% for the variable.

We can now come to a conclusion that any level of significance above 0.05% will cause the null

hypothesis mean of failure to answer is equal to zero to be rejected and the alternate hypothesis

mean of failure to answer is greater than zero to be established.

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Conclusion: With a significance level of 5%, we can say the null hypothesis is rejected, meaning

that there are instances of failure to answer by the employees of the micro insurance companies.

This shows as to how, the perception of the policyholders may have been wrong. This renders the

industry as ineffective.

4.4.6 Findings regarding frequency of visits made by agents

In this section we test whether the frequency of visit made by agents is high or low for those

policyholders who have to pay the premiums via agents. Here we assume that the agents do not

visit the policyholders regularly.


in [Appendix 9], under the subtopic Hypothesis 7. A simpler table of showing the mean value

and the significance value obtained is given below.


Regular Visits of Agents 0.87 0%

The sample mean for the variable as shown on the table is 0.87. This means 87% of the

respondents have agents who regularly visit the policyholders. Thus, the claim that we want to

test is that a significantly large proportion of policyholders believe that agents visit regularly.

The significance level for a two tailed test in this context is 0%. If we consider a one tailed test

for the variable, the level of significance would still be 0%.

Thus we can conclude that for at any level of significance above 0%, we reject the null

hypothesis and establish the alternate hypothesis that a significantly large proportion of

policyholders believe that agents make regular visits.

Conclusion: With a level of significance of 5%, rejecting the null hypothesis, we can claim that

the agents regularly visit the policyholders making the micro insurance scheme effective in

Bangladesh in this context.

4.4.7 Synthesis of micro-insurance employees


Instances of Misbehavior by

Employees/Agents

The policyholders have experienced instances

where agents/employees misbehaved with them.

Rendering the insurance ineffective.

0

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Perception of Employee

Behavior

The policyholders believe that the employees

behavior is satisfactory 1

Amount of commission

charged by Agents

The mean commission suggested by policyholders

is the same as the 15% being charged currently in

the industry causing this section to be effective.

1

Instances of Unrecorded

Payments

Policyholders have faces instances where the firm

or its agents have not recorded the payments. This

renders this section as ineffective.

0

Knowledge of Employees

Policyholders believe that knowledge of

employees regarding micro insurance schemes is

satisfactory.

1

However there have been several instances of

failure to answer queries by the agents which

causes this section to be ineffective.

0

Frequency of Visits made by

Agents

87% of the policyholders have agents who visit

regularly to collect the premiums. 1

Average value 0.60

4.5 FINDINGS REGARDING COVERAGE OF MICRO-INSURANCE

In this part of the report, we try to find out as to whether micro insurance is able to cover most of

the variety of insurance needs of the people of Bangladesh.

The table below shows how the different items need to be insured, are already insured, or both,

in the perspective of our sample respondents.

Items

Assets that need

to be insured

(Frequency)

Assets that are

insured

(Frequency)

Both

(Frequency)

Value of

Effectiveness

1) Hospitalization 5 3 1 0

2) Primary health care 5 - 2 0

3) Maternity 3 - - 0

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4) Life Insurance 4 15 19 1

5) Retirement savings plans 5 1 2 0

6) Against weather 4 1 - 0

7) Against rising cost of cultivation

- - - 0

8) Against pest attacks and diseases

1 - - 0

9) Livestock - - - 0

10) Housing 3 1 - 0

11) Vehicles 7 1 - 0

Total 37 22 24 1

Average Value of Effecti

Research Dholaikhal

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