Assessing the Knowledge of and Attitude towards Insurance in Ghana
Charles Ackah†‡ and Adobea Owusu
Institute of Statistical, Social and Economic Research (ISSER)
University of Ghana
March, 2012
Abstract
The majority of people living in Africa have to bear the financial burden of catastrophes themselves,
without access to insurance or government assistance. In Ghana, access to insurance is low: 4.1 percent
(excluding public health insurance) in 2010. A previous study suggested that lack of knowledge about
insurance products, and to an extent misunderstanding of the concept of insurance accounts for the low
uptake of insurance among the low-income population in Ghana. This study therefore seeks to determine
the level of insurance awareness in Ghana, where awareness is defined with respect to people‘s
knowledge of and attitude towards insurance. An Insurance Awareness Index was computed to give a
quantifiable measure of a person‘s knowledge of and attitude towards insurance. Knowledge of Insurance
was measured using multiple choice and true/false questions, whilst attitude was tested using a Likert
scale. Index scores were obtained for knowledge and attitude, based on the sum of correct / favorable
responses respectively. A main finding from the qualitative investigation is that most Ghanaians,
especially those in the informal sector, do not take-up insurance as a way of preparing towards future
unforeseen misfortunes. This could be because of the perception among some individuals that planning
ahead for a possible misfortune is like inviting evil. Other reasons given for low insurance uptake were
the general lack of insurance knowledge amongst the populace, low income levels and the reliance on
God‘s protection to prevent calamities. With regards to attitude towards insurance, the study confirmed
the general impression that insurance companies will eventually renege on their promises. It is
recommended that education on insurance is increased, government‘s supervision of insurance operations
is strengthened, and that insurance companies improve their client orientation so as to redeem their public
negative image.
‡
Corresponding author: P.O. Box LG 74, University of Ghana, Legon; Email: [email protected]
The authors would like to thank all those who contributed to the successful completion of this report. First among
them are the staff, agent, clients and non-clients of insurance companies who gave us a good insight into the current
situation regarding insurance awareness, knowledge and attitude in Ghana. We are also grateful to all the field
supervisors and enumerators who carefully collected these insights for our analysis. We are indebted to the Deutsche
Gesellschaft fur Internationale Zusammenarbeit (GIZ) for funding the study. The findings and opinions in this paper
may not reflect the official views of the GIZ.
1. Introduction
Emergencies of all types are by nature, rather unpredictable. Given these, they have the tendency
to render their victims vulnerable, given their concomitant financial shocks. In instances where
these persons are not prepared financially particularly for the emergencies, they suffer double
agony. The poor generally, but particularly those in developing countries, are ordinarily
vulnerable to emergencies and disasters. Cushioning individuals, families and communities
against the financial burden of catastrophes and periods of incapacity and old age, is what
insurance schemes seek to do. Insurance is thus a risk-sharing arrangement (Leppert et al, 2012).
The majority of people living in Africa have to bear the financial burden of catastrophes
themselves, without access to insurance or government assistance. In Ghana, access to insurance
is low: 4.1 percent (excluding public health insurance) in 2010 1. A previous study2 suggested that
lack of knowledge about insurance products, and to an extent misunderstanding of the concept of
insurance accounts for the low uptake of insurance among the low-income population in Ghana.
This study therefore seeks to determine the actual level of insurance awareness in Ghana, where
awareness is defined with respect to people‘s knowledge of and attitude towards insurance. Both
qualitative and quantitative methods were used. The outcomes of the qualitative survey informed
the questionnaire design for the quantitative survey. An Insurance Awareness Index was
developed from the quantitative survey to give a quantifiable measure of a person‘s knowledge
of and attitude towards insurance.
Knowledge of insurance was measured using multiple choice and true/false questions, whilst
attitude was tested using a Likert scale. Index scores were obtained for knowledge and attitude,
based on the sum of correct / favorable responses respectively. Age, gender and educational level
of the household head explained the level of insurance knowledge in an ordered probit
regression. No regional differences could be established.
In the first stage, seven (7) Focus Group Discussions (FGDs) were carried out with staff, agents,
clients and non-clients of three microinsurance companies. A main finding from the FGDs was
that most Ghanaians, especially those in the informal sector, do not take-up insurance as a way of
preparing towards future unforeseen misfortunes. This could be because of the perception among
some individuals that planning ahead for a possible misfortune is like inviting evil.
Other reasons given for low insurance uptake were the general lack of insurance knowledge
amongst the populace, low income levels and the reliance on God‘s protection to prevent
calamities. With regards to attitude towards insurance, the FGDs confirmed the general
impression that insurance companies will eventually renege on their promises. Additionally,
Insurance was thought to be for the affluent, well educated, and formal employees.
In order to complement the qualitative evidence, a quantitative survey of about 300 target
respondents from the same communities was undertaken. Based on the regional population
distribution of Ghana, proportionate allocation from the total sample is made for each region.
Within each region under consideration two sub-metropolises are selected from which a random
1
2
Finmark Trust (2011)
McCord, Wiedmeyer-Pfister (2009)
2
selection of one community each is made. Houses were selected using simple random sampling,
and within each selected house, the same approach was used to select a study household, if a
selected house had more than one household. Respondents were the natural heads of households,
if they were available at the time the study team visited the household. In his/her absence, the
spouse, if any, or otherwise, the next person in command who was available was selected for the
interview.
The determinants of awareness are age, gender and educational status of respondents. Age is a
statistically significant variable and positively predicts insurance literacy and attitude towards
insurance. Older individuals are generally more knowledgeable in insurance. Higher literacy
scores coincide with respondents being male and enjoying a better education.
The remainder of the paper is organized as follows: Section 2 presents a brief literature review.
Section 3 presents our empirical approach. Section 4 discusses the data used and some
descriptive findings. The results are summarized in Section 5. Section 6 concludes.
2. Literature Review
There is paucity of literature on the determinants of insurance in general in Sub-Saharan African;
literature on micro-insurance specifically seems more prevalent. In a setting like Ghana, and
other Sub-Saharan African countries, the concept of insurance comes within a difficult context.
First, there are several informal and social connections, particularly founded upon the extended
family systems that sometimes extend help to defray some pressing needs. These have the
potential to overshadow the individual‘s sense of vulnerability to financial shocks. However,
with time, the extended family social support system is waning, for several reasons (Apt, 1990;
Owusu, 2007). Another critical factor affecting the demand of insurance in such low income
countries has to do with their non-availability, for most of the time (Churchill, 2006; Leppert et
al, 2012), and generally low information about these schemes, to begin with (Gine et al, 2008;
Giesbert et al., 2011).
Within these contexts, while it is becoming more increasingly necessary for persons in such low
income countries to find some financial buffer for times of unexpected need (Adamba and
Owusu, 2011), the reality is that the vast majority of the populations in Sub-Saharan Africa are
without such financial cushioning. Matul et al. (2010) documented that as low as only about
2.6% of the African population who are very poor (those who spend less than $2 per day) have
some form of (micro) insurance. In Ghana for example, a recent study by the Finmark Trust,
published in 2011, indicated that the level of insurance coverage, not counting the National
Health Insurance Scheme (NHIS), is 4.1% country-wide. Even for the NHIS which the Act of
Parliament which established it makes mandatory for all Ghanaians, only 65% are currently
enrolled in the scheme, some of whom even have defunct membership (Ghana Business News,
2011).
Previous studies explain some of the reasons for this abysmally low uptake of insurance in
Ghana and other countries in the developing world. These include lack of awareness of the
existence of insurance products, and a poor understanding of the concept of insurance (Gine et
3
al., 2008; Wiedmeyer-Pfister and McCord, 2009; Giesbert et al., 2011). Giesbert et al. (2011: 8)
quote several recent authors (Wang and Rosenman, 2007; Gine, Townsend, and Vickery, 2008;
Cai et al., 2009; Cole et al, 2009; Gine and Yang, 2009; Ito and Kano, 2010; Thornton et al.,
2010) in saying that the following factors are amongst those that determine households‘
participation in micro life insurance: basis risk, household wealth, credit constraints, risk
aversion, trust, endorsement from social networks, hyperbolic preferences, and particular
marketing methods.
In a study on the demand for micro health insurance using Botswana‘s Itekanele scheme
collected in 2009, Swami et al. (2012) found that living in a female headed household, living in
an urban area, not being self-employed, having a secondary school education or higher, and an
age for which one is within the economically active bracket (they found a mean age of 42 years)
correlated positively with the demand for the insurance.
With specific reference to participation in a micro life insurance scheme in Ghana, Giesbert and
her colleagues (2011) concluded that insurance is considered a risky venture by their
respondents, based on their finding that risk-averse households and households which considered
themselves to have increased/higher risk were less likely to participate in the life insurance
scheme. Giesbert et al. (2011) also found that adverse selection, and a ―life-cycle effect‖ affected
uptake of the microinsurance they studied.
Using a sample of 350 policy holders of a life insurance which included accident and
hospitalization benefits in two small neighbouring towns (Brakwa and Benin) in the then
Asikuma/Odoben/Brakwa district in the Central Region of Ghana in a cross sectional study
conducted in 2008, Giesbert et al. (2011) studied the correlates of households‘ participation in
microinsurance. In an index Giesbert et al. (2011) developed to explain the correlates to the
households‘ participation in insurance, the following variables promoted the uptake of the
insurance amongst their respondents: willingness to take risks, illness, vaccination, risk
assessment, death experience, illness experience, other shock experience, age, age squared, share
of dependents (in the total number of household members), being married, living in Benin—the
community adjudged smaller of the two study sites and with plausibly more social interaction,
being married, being a female head of household, schooling, being a wage-employee household
or one that employs others, having tangible assets such as bicycle, house, or refrigerator,
amongst others, bigger size of land (in acres) used by the household (per adult equivalent), and
enjoying remittances from others outside the household. The study also found that households
who used other formal financial services were more likely to demand the microinsurance
scheme. Additionally, Giesbert et al. also found that trust in the insurance provider and social
networks play significant roles in the demand for insurance.
Giesbert et al. noted that some of their findings, particularly in relation to the thought of the
microinsurance scheme they studied as being risky seemed to have been so ―because they [the
respondents] do not fully understand the insurance and all its terms and conditions ―(p. 27).
These authors also observed a ―lack of information on the demand side‖ (p. 27) and conclude
that the lack of information is ―one of the most important challenges of microinsurance in
academic and policymakers‘ circles‖ (p. 27). Based on this, they recommend and emphasize
4
―that major efforts are necessary in providing financial literacy to low-income households‖ (p.
28).
Giesbert et al.‘s findings were not very different from those of Gine et al. (2008), who studied
demand for rainfall insurance in rural India. For Gine et al.'s study, basis risk between insurance
payouts and income fluctuations, being a risk averse household, as well as being a household
with binding credit constraints did not promote uptake of the (micro) insurance scheme. The
authors summed these factors up as household uncertainty about the product which reduced the
uptake of the product. Alternatively, demand increased with household wealth, participation in
village networks, and familiarity with the insurance vendor.
Our empirical analysis is based on the recent literature on demand for insurance. From the above
literature, the demand for insurance stems from three primary factors: household sociodemographic and related factors such as age, wealth, employment status and type of
employment, education and assets. The second main factor is community characteristics such as
the endorsement of insurance by social networks, the level of social interaction in a community,
and awareness of existing insurance products in a community. Finally, the third element has to
do with the (micro) insurance schemes themselves. Factors such as trust for a provider,
marketing methods of a provider, and the extent to which providers make information available
on the demand side of the scheme to community members. Alternatively, a provider‘s inability to
undertake good marketing methods could lead to a lack of awareness and poor understanding of
insurance schemes by communities and households. Some amount of interaction exists between
all three primary factors. For instance, a household‘s familiarity with/closeness to a provider
leads to trust for the provider, and the latter could elicit endorsement from social networks for a
provider. Also, the marketing methods of a provider, for instance, could lead to positive
perception of an insurance scheme as safe and not risky.
3. Methodology
The sampling comprised of a multi-stage cross sectional process, including purposive and simple
random sampling, for the selection of the study districts, communities, and respondents. Per the
preferences GIZ, the study was carried out in the four regions of Greater Accra, Ashanti,
Western and Northern. These regions were studied, using purposive sampling. In each region,
two districts were selected to reflect an urban/rural (farming/non-farming) dichotomy (see Table
1). Subsequently, a rural and an urban community were selected in each district for the study. In
all study communities, low income neighbourhoods were targeted. Within each selected district,
recognizance surveys were undertaken to inform the selection of the specific study communities.
Similarly, in each selected community, recognizance surveys were conducted ahead of time to
earmark low income neighbourhoods in which the study was conducted. A total of six focus
group discussions (FGDs) were conducted; five for clients, staff and agents of insurance
companies, and a sixth for community members who had no insurance policy at all. Table 2
presents information on the FGD discussants.
Per the recommendations of the GIZ, staff, agents and clients of select insurance companies that
operate micro insurance policies based in the pre-selected regions were studied. Donewell
5
Insurance Company, SIC Life, and Star Assurance Company were selected for the qualitative
investigation. These companies were selected because they operate micro insurance schemes for
the general public and select groups. Table 2 provides more details on the FGDs.
Table 1: Study Regions and Districts
No.
Region
Districts
Rural
1
2
3
4
Greater Accra
Ashanti
Northern
Western
Dangbe West
Atwima-Kwanwoma
Gushegu
Agona Nkwanta
Urban
Greater Accra Metropolitan Area
Kumasi Metropolitan Area
Tamale Metropolitan
Sekondi-Takorad
Source: Authors‘ illustrations
Table 2: Information on FGD Discussants
No
Group
Affiliation
1.
Clients
SIC Life
2.
Clients
3.
Agents
Donewell
Insurance
Company
Star Assurance
Company
4.
Agents and Staff
SIC Life
5.
Agents and Staff
6.
Non-insurance
clients
Donewell
Insurance
Company
Not applicable
Study Region and
District
Study
Community
Greater Accra Region,
Accra Metropolitan
Assembly
Ashanti Region, KMA
Traders,
scattered
4
6
10
Sokoban Wood
Village, Kumasi
3
3
6
5
7
12
4
6
10
3
3
6
5
3
8
Greater Accra Region,
Accra Metropolitan
Assembly
Greater Accra Region,
Accra Metropolitan
Assembly
Ashanti Region, KMA
Ashanti Region, KMA
Traders,
scattered
Traders, Asafo
market
Total
Gender
Male Female
Source: Authors‘ illustrations
In order to complement the qualitative evidence, a quantitative survey of about 300 target
respondents from the same communities was undertaken. Based on the regional population
distribution of Ghana, proportionate allocation from the total sample is made for each region.
Within each region under consideration two sub-metropolises are selected from which a random
selection of one community each is made. Houses were selected using simple random sampling,
and within each selected house, the same approach was used to select a study household, if a
selected house had more than one household. Respondents were the natural heads of households,
if they were available at the time the study team visited the household. In his/her absence, the
spouse, if any, or otherwise, the next person in command who was available was selected for the
interview.
6
Table 3: Distribution of Respondents for Quantitative Study
Region
Urban community
Rural community
Greater Accra (GA)
Ashanti (AR)
Western (WR)
Northern (NR)
Nima (26)
Adabraka (25)
Tafo (32)
Asawase (32)
Sekondi (17)
Takoradi (17)
Kaladan (16)
Kakpagyli (16)
Ayikuma (34)
Esaase (42)
Agona Nkwanta (22)
Nyankpala (21)
Source: Authors‘ illustrations
We employed the Probit model to explore the factors that predicted scores on the attitude and
knowledge indices, ceteris parabus. Each regression model included the following sociodemographic characteristics: age of head, sex of head, educational achievement of head,
employment status of head, locality, and income of household. The analysis examines which
socioeconomic and demographic characteristics determine our measures of insurance literacy
and attitudes towards insurance, and to what extent they do so. To do so, we regress the
household‘s Insurance knowledge and attitude scores on the household characteristics that we
collected from the survey. The results of the multivariate regressions are shown in Table 4.
While coefficients cannot be given a causal interpretation, it is nevertheless informative to
understand what household characteristics are correlated with insurance literacy and attitudes
towards insurance. We further examined whether a household‘s insurance awareness score
influences a person‘s uptake of insurance (or lack thereof).
4. Descriptive Findings
The empirical analysis in this paper is based on cross-sectional data from a survey of 303
Ghanaian households, of which 173 were insured, 113 were not insured, and 17 refused to
indicate their status. The survey was conducted by the authors within four purposively selected
regions in Ghana – Greater Accra, Ashanti, Western and Northern. In the second stage,
purposive and subsequently random sampling methods were used to select two districts from the
Greater Accra, Western, Ashanti and Northern regions.
60 percent of the respondents had one insurance policy or the other with the majority (82
percent) holding the national health insurance policy (NHIS). We investigate households‘
decisions to take up insurance in the next section. We are particularly interested in investigating
whether lack of awareness of the existence of insurance products and a poor understanding of the
concept of insurance correlates with the uptake of insurance.
7
Table 4: Household Participation in Insurance
Do you currently have an insurance policy?
Life/Funeral
Old age annuities/Pension
Property
Automobile
Health
Other
Source: Authors‘ illustrations
Freq.
173
18
1
3
7
142
2
Insured
Percent
60
10
1
2
4
82
1
Not insured
Freq.
Percent
113
40
The primary category of respondents consists of people who have no education or have
incomplete primary education. The JSS category consists of completed primary, some JSS,
completed JSS and some secondary education. The SSS category consists of people who have
completed their secondary education and the Post SSS category consists of people who have any
form of education higher than SSS. Research into the highest qualification obtained reveals that
on average respondents from the Ashanti and Greater Accra regions are educated while their
counterparts in the Northern region are the least educated (Table 5). Table 6 shows that more
males than females are educated. Also, most females find themselves in the ―some primary‖
category compared to their male counterparts and more males than females have attained some
form of Post SSS education.
Table 5: Highest Qualification Completed by Region of Respondents
Highest
Qualification
Western
Greater Accra
Ashanti
completed
Freq
%
Freq
%
Freq
%
Some Primary
JSS
SSS
Post SSS
Total
9
31
8
9
57
15.8
54.4
14.0
15.8
100
23
33
15
15
86
26.7
38.4
17.4
17.4
100
20
49
16
23
108
Table 6: Highest Qualification Completed Gender of Respondents
Male
Highest Qualification completed
Freq
Freq
%
Some Primary
JSS
SSS
Post SSS
Total
28
59
21
43
151
18.5
39.1
13.9
28.5
100
8
51
65
23
13
152
18.5
45.4
14.8
21.3
100
Female
%
33.6
42.8
15.1
8.6
100
Northern
Freq
%
27
11
5
9
52
51.9
21.1
9.6
17.3
100
The results indicate diverse sources of income for the head of respondents. Most of them derived
their income from self employment and this was particularly in the Ashanti region (Table 7).
Wage employment was the next highest source of income and this was highest in the Western
region. Agriculture production as a source of income was highest in Greater Accra and livestock
breeding was a source of income for household heads residing in Accra only. Receiving money
from a family member residing outside the country was highest for people residing in the
Western region, along with other sources of income not included in the aforementioned list.
Table 7: Main Source of Income for Respondents
Source of Income
Western
Greater Accra
Ashanti
Northern
%
%
%
%
Wage Employment
31.58
22.35
26.85
26.92
Self Employment
Agric production
Livestock breeding
Money from family member abroad
Other
40.35
7.02
0.00
5.26
15.79
57.65
10.59
3.53
4.71
1.18
60.19
6.48
0.00
3.70
2.78
46.15
25.00
0.00
1.92
0.00
The trend predicted in the results above show that on average, women earn less than their male
counterparts (Table 9). Low earnings are more pronounced in the Northern region (Table 8).
Table 8: Monthly Household Income by Region of Respondents
Monthly
Greater
Western
Ashanti
Income
Accra
Freq
% Freq
%
Freq
%
Below 200
Ghc 201-400
Ghc 401-600
Above Ghc 600
Total
12
14
6
9
41
29.3
34.2
14.5
22.0
100
30
16
19
7
72
41.7
22.2
26.4
9.7
100
28
30
13
11
82
34.2
36.6
15.9
13.4
100
Table 9: Monthly Household Income by Gender of Respondents
Male
Female
Monthly Income
Freq
%
Freq
%
Below 200
Ghc 201-400
Ghc 401-600
Above Ghc 600
Total
40
47
27
20
134
29.9
35.1
20.2
14.9
100
50
25
17
10
102
9
49.0
24.5
16.7
9.8
100
Northern
Freq
%
20
12
6
3
41
48.8
29.3
14.6
7.3
100
Awareness about Insurance
This section documents the level of insurance literacy and awareness and then explores its
determinants. The results show that many people have heard of the word insurance. However
regional variations exist. Ashanti and Greater Accra regions are the most knowledgeable regions
about insurance, followed by Western and lastly the Northern regions.
We tested insurance literacy with six true/false and multiple choice questions (3 true/false and 3
multiple choice questions). Literacy index is constructed from the responses to these knowledge
questions. The insurance literacy index is the sum of correct answers. The mean insurance
awareness score is 0.65 (Table 10). Male respondents scored higher than females on the
awareness index. There are also regional heterogeneities – respondents in the Ashanti and
Northern regions score higher on the literacy index (Table 11). Surprisingly, Greater Accra
respondents had the lowest score. They thus have the greatest need for insurance awareness
education.
On average, in all regions, the number of people who had knowledge about how insurance works
were more than those who had no knowledge at all. The Western, Greater Accra and Ashanti
regions on average had comparable results in terms of the number of people who could
confidently say they knew how insurance works regardless of gender. The respondents in the
Northern region had the least knowledge about how insurance works. Possibly, this is because of
the high level of illiteracy and poverty in the region. Furthermore, gender differences reveal that
males had more knowledge about insurance than their female counterparts.
Table 10: Knowledge of Insurance
Types of insurance known (MC)
Insurance is for free (T/F)
No need to pay regularly (T/F)
Get money back if no claim (T/F)
Contribute specific amount (MC)
Life insurance (MC)
Insurance Knowledge Index
Mean
0.37
0.83
0.82
0.77
0.78
0.33
0.65
Std. Dev.
0.24
0.38
0.39
0.42
0.41
0.47
0.39
Table 11: Knowledge of Insurance by Gender
Male
0.43
0.83
0.83
0.77
0.81
0.47
0.69
Types of insurance known (MC)
Insurance is for free (T/F)
No need to pay regularly (T/F)
Get money back if no claim (T/F)
Contribute specific amount (MC)
Life insurance (MC)
Insurance Knowledge Index
10
Female
0.32
0.84
0.81
0.78
0.76
0.20
0.62
Min
0.00
0.00
0.00
0.00
0.00
0.00
0.00
Max
1.00
1.00
1.00
1.00
1.00
1.00
1.00
Table 12: Knowledge of Insurance by Region
Types of insurance known (MC)
Insurance is for free (T/F)
No need to pay regularly (T/F)
Get money back if no claim (T/F)
Contribute specific amount (MC)
Life insurance (MC)
Insurance Knowledge Index
Western
0.27
0.86
0.77
0.86
0.82
0.21
0.63
Table 13: Knowledge of Insurance by Age
18-24
Types of insurance known (MC)
0.30
Insurance is for free (T/F)
0.75
No need to pay regularly (T/F)
0.50
Get money back if no claim (T/F)
0.75
Contribute specific amount (MC)
0.75
Life insurance (MC)
0.25
Insurance Knowledge Index
0.55
25-34
0.37
0.84
0.82
0.81
0.83
0.38
0.68
Table 14: Knowledge of Insurance by Income
Poorest
25%
Types of insurance known (MC)
0.35
Insurance is for free (T/F)
0.82
No need to pay regularly (T/F)
0.84
Get money back if no claim (T/F)
0.73
Contribute specific amount (MC)
0.78
Life insurance (MC)
0.28
Insurance Knowledge Index
0.63
Greater
Accra
0.39
0.74
0.75
0.66
0.75
0.36
0.61
35-44
0.42
0.91
0.89
0.81
0.81
0.37
0.70
2
0.42
0.82
0.78
0.74
0.81
0.39
0.66
Ashanti
0.43
0.83
0.86
0.78
0.81
0.43
0.69
45-54
0.38
0.81
0.89
0.75
0.72
0.30
0.64
3
0.42
0.77
0.84
0.84
0.80
0.50
0.69
Northern
0.33
0.92
0.88
0.85
0.75
0.23
0.66
55-65
0.34
0.78
0.81
0.70
0.78
0.30
0.62
Richest
25%
0.42
0.80
0.80
0.80
0.73
0.57
0.69
Attitudes and Opinions
All respondents were asked to give their opinions on several items related to their attitude about
insurance and other financial matters. The results show that regardless of region or gender, most
people were very sure that if they made a claim to the insurance provider, they would receive
their benefits as contracted (Table 15). It seemed more females than males were sure of this and
this shows a high level of confidence in the insurance providers.
Among the key opinion questions, we sought to measure respondents‘ perceptions regarding the
importance of insurance (Table 15). Majority of the respondents were positive about insurance –
11
irrespective of the region of respondent, many of them were of the opinion that they can trust
insurance companies to be fair to them.
We also constructed an index to measure attitudes towards insurance using the Likert scaling
method. The insurance attitude index is the mean of favourable and non-favourable attitudes
towards insurance. The index is constructed from the subjective responses to trust, perception
and importance questions on insurance firms and their products. An index of unitary (one)
represents perfectly favourable attitude towards insurance. Thus, the more positive towards
insurance the higher the index. The mean attitude is 0.74 (Table 8). Male respondents scored
higher than females on the attitude index. The young (18-34) scored better than the elderly.
There are also regional heterogeneities – respondents in the Western region scored higher on the
attitude index than those from other regions. Respondents residing in Greater Accra had the
worst attitude towards insurance. Finally, respondents within the richest 25 percent income group
scored relatively better than their poorer counterparts.
Table 15: Attitude Index
Age group
18-24
25-34
35-44
45-54
55-65
Mean
0.75
0.76
0.73
0.72
0.73
Gender
Male
Female
0.73
0.74
Region
Western
Greater Accra
Ashanti
Northern
0.76
0.72
0.74
0.73
Income quartile
Poorest 25%
2
3
Richest 25%
0.72
0.74
0.75
0.77
Overall Average
0.74
The overall insurance awareness index is presented in Table 16. It comprises a combination of
the scores on insurance knowledge and attitude towards insurance. The mean insurance
awareness score is 0.70. Male respondents scored higher than females on the awareness index.
Stakeholders should increase insurance awareness among females particularly. There are also
regional heterogeneities – respondents in the Ashanti region scored better on the awareness
12
index. Again, Greater Accra respondents had the lowest score. They thus have the greatest need
for insurance awareness education. Respondents within the age bracket of 25-44 scored better
while the youth (18-24) scored the lowest. In terms of wealth, the rich scored better than the
poor.
Table 16: Overall Insurance Awareness Index
Age group
18-24
25-34
35-44
45-54
55-65
Mean
0.65
0.73
0.71
0.69
0.68
Gender
Male
Female
0.72
0.68
Region
Western
Greater Accra
Ashanti
Northern
0.70
0.68
0.72
0.70
Income quartile
Poorest 25%
2nd quartile
3rd quartile
Richest 25%
0.68
0.71
0.72
0.76
Overall Average
0.70
5. Results and Discussion
The FGDs were undertaken with the following objectives:
i.
ii.
iii.
iv.
To ascertain peoples‘ views on preparing ahead for possible misfortunes.
To determine the possible [catastrophic] factors likely to impact people‘s finances.
To capture people‘s awareness and knowledge of insurance, their attitudes towards it,
their insurance practices, and experiences with having insurance.
To establish peoples‘ alternative sources of financial cushioning aside insurance.
Clients of Donewell Insurance Company in Kumasi, and SIC Life in Accra were studied. They
were mostly traders and were engaged mostly in the micro insurance schemes of these
companies. In addition to the clients, staff and agents of the three insurance companies used for
13
the study, including Star Micro Insurance Company in Accra, were interviewed. Finally, a group
of persons who did not have any form of insurance were also interviewed in Kumasi. All the
groups interviewed comprised of both males and females.
The discussants agreed that generally, Ghanaians barely prepare ahead for misfortunes. The
primary reason was that the Ghanaian culture does not make room for preparing ahead of
misfortune — insurance is simply not a part of our lives; and there is the notion that if you plan
ahead for something ‗evil‘ or a misfortune/catastrophe, it will surely come upon you.
For us as Ghanaians, we don‘t prepare for misfortunes. When you look at Ghanaians, it‘s
only a few that take insurances especially the rich and educated but when you look at us,
carpenters, traders etc we just started taking insurances. For us as Ghanaian, we don‘t do
well when it comes to insurances [Clients, Donewell Insurance Company, Kumasi].
We are what we think and better are we by focusing on the positive side of life as having
evil thoughts invite evil to befall us [Agents, SIC Life].
It‘s not really attitude per say, but the kind of culture we came to meet. Our culture does
not make us think of these misfortunes. We think of what to eat today and not what
misfortunes/evil will happen to us and so we don‘t prepare for such misfortunes
[Staff/agents, Donewell Insurance Company, Kumasi].
I was talking with an old man who said that when you begin thinking of insurance or
getting insured, you are having evil thoughts. There is no need to get insured because
when you do that you are inviting evil [Non-insured group, Kumasi].
It is not part of the Ghanaian culture to prepare ahead for misfortunes [Agents and Staff,
SIC Life, Accra; Agents, Star Micro, Accra].
Other key reasons attributed to this situation, in a descending order of importance are that 1)
Ghanaians are generally presumed to be ignorant about the importance of insurance, 2) the
average Ghanaian is preoccupied with his or her survival (is poor) and is thus unable to save
towards cushioning against future catastrophes; 3) that Ghanaians trust God; He protects us/will
protect us and will not allow catastrophe to befall us. 4) Quite in relation to point (3), it was felt
that Ghanaians generally do not foresee misfortunes.
-
Unless people get sick, they don‘t have the idea of getting insurance because people say
God is a Ghanaian due to His protection of us.
I don‘t know which sickness will make me go to the hospital. May be unless a house
collapses on me or I get an accident; and I know God would not allow it to happen. Even
when I am sick my Mum is a nurse and there are some drugs at home for me to take
[Uninsured group, Kumasi].
The above stated issues were buttressed by a great mistrust for insurance companies among all
the focus group (FG) discussants, and other micro credit schemes. More importantly, the
14
respondents felt unanimously, that Ghanaians as a whole share that view of extreme mistrust for
insurance companies.
There was the general consensus that the vast majority of Ghanaians have heard about insurance,
particularly stemming from the adverts on the National Health Insurance Scheme (NHIS). In
fact, even all the non-insured respondents had heard about insurance. Yet, it was generally
agreed that the vast majority of the Ghanaian populace do not understand the concept of
insurance, and do not have it in their vocabulary.
A slim minority of the non-insured clients were of the opinion that some people have not heard
about the concept of insurance at all, including some of their family members. More importantly,
however, it was generally agreed by all the groups of respondents that Ghanaians lack systematic
education on insurance, and hence, do not understand it.
I don‘t understand it because I have no idea what it is. I don‘t know if after getting my
health insured through the NHIS, my building, my life, etc, will also be insured and
secured. People say that they do understand the various insurance schemes due to their
knowledge of the NHIS but they can‘t tell the names given to these other insurances.
Ghanaians need to be educated about insurance [Non-insured respondents, Kumasi].
-- I have heard about it but I don‘t know its nature, as to whether it‘s slit (long skirt) and
kaba or browse (blouse), I don‘t really know how it is done and what it entails.
--I have heard about it but I didn‘t know whether anybody/everybody can get insured. I
thought it was for the rich but the NHIS gave me the understanding that it was for
everyone [Non-insured respondents, Kumasi].
…I think it was not that the companies were not truthful to them but they did not really
understand what they were taught by the insurance companies. I think insurance existed
in the olden days, because in the old villages, people contributed some money to help
bury the dead. But the introduction of the foreign one did not have much understanding
among the citizenry. I think the teaching and understanding of insurance is very low
[Clients, Donewell Insurance Company, Kumasi].
In part, the study revealed that many a Ghanaian‘s concept of insurance is colored by the concept
of Susu (micro savings) and cannot differentiate between the two.
I think about the future by saving a little at the bank and also through Susu where when I
am in need I go for it. [Non-insured group, Kumasi.]
Okay it‘s just a few of them who really understand. When you go to the markets for
instance, they say it is like Susu; that they are paying the money and they can collect it
any day when they feel like taking the money [Agents, Star Micro Insurance Company,
Accra].
Generally, the clients understood insurance better than the non-clients. Even for the former, it is
doubtful that they all understood the concept of insurance very well.
15
-
[Insurance is] preparing oneself against misfortunes so that one can receive help in the
future.
[Insurance is] simply saving some money whiles one can work with both hands and feet
so that in case of misfortunes one can fall on it to care for oneself until death
[Clients, Donewell Insurance Company Limited, Kumasi]
Again, the respondents agreed that Ghanaians generally have a poor attitude toward insurance.
This situation stems from two main reasons: the primary one has to do with a very great
misconception of and mistrust about the operation of insurance companies in Ghana. Several
reasons were given to explain why there is the great mistrust for insurance companies and their
operations. These included: 1) how insurance started in Ghana 2) the operations of the insurance
companies are not transparent, making claims from them is difficult, and 3) they are corrupt. The
latter is explained subsequently in the report. With the former, it was felt that when insurance
started Ghana had a very small population, and now the population is huge so the companies are
not able to keep up with the increasing population to adequately cover it with education on
insurance. Also, the concept of insurance was presented in the past as if it was for a select few,
and thus did not get the attention of the mass of the people (this is discussed in depth later).
Some people also say that insurance companies are bad; that when you give them your
money at long last they will disappoint you. They don‘t give you your money back
[Agents, Star Micro Insurance Company, Accra].
I think it is because of how insurances were started. Some people see it as something for
the rich or very educated. Some people will tell you that I don‘t own a car or house so I
do not need insurance [Staff/agents, Donewell Insurance Company, Kumasi].
The second reason for the poor attitude towards insurance can be summed up under all the
above-stated cultural and related reasons. For instance, although the funeral insurance package
seemed to be one of the most patronized, from the view of the staff and agents, there was still the
feeling that in a number of ways, the social support system caters for certain catastrophes, which
makes it unnecessary to purchase insurance for such things. When it comes to funeral
ceremonies for example, people go and borrow money, and at the end of the day, people donate
to cover the expenses and they return what they borrowed. So people do not see the need to have
funeral insurance for instance.
People know this and therefore do not see the need to get insurance for funerals
[Female agent, Star Micro Company Limited].
Compared to the insured clients, the uninsured ones particularly had a greater sense of depending
on social assistance when they experience misfortunes that could have great financial
implications. The uninsured group mentioned the following ways in which they deal with
financial problems in their households:
-- My family members are there to help but if they are not willing to help, they can stop.
-- God takes care of us and nothing bad will happen to me.
-- When I am sick, I go to the drug store and get some drugs.
-- Friends and family members are there to help [me].
16
When probed further how their households deal with unexpected financial catastrophes, they
(non-insured group) stated the following:
-- We (the household/family) will contribute little by little to solve it.
-- As it‘s being done, I will seek assistance from radio listeners and also present my case to
Metro TV and TV3 for help.
-- For me, I have not received any help but I have heard of several people who have received
assistance from Fox FM (in Kumasi).
-- During my father‘s death, he was saving in a bank so we received a loan from the bank.
-- Sometimes we send our case to the Church for assistance.
To an appreciable extent, there was also the feeling that it is the government‘s responsibility to
provide insurance for the population:
I have it (getting an insurance policy) in mind but currently my finances are not good.
The government should assist us to get insured. We will be thankful....If the government
says he would help I/we will accept it but to get one (an insurance scheme) soon, that will
not be possible [Non-insured group, Kumasi].
Beyond this, the respondents generally revealed a huge mistrust among the general public about
(micro) insurance firms, and suspicion for insurance companies in general. It was felt that
insurance firms are generally not trustworthy as they collect people‘s monies with ease and put
them through hurdles including taking them to courts when it comes to making claims. The
agents from Star Micro Company agreed in unison to the following explanation/testimony
provided by one of their male agents during the interview:
Sometimes they have negative minds about the insurance. The market women would say‘
even ELAC…ELAC which is situated just here (within the market) didn‘t give me
anything how much more you who just came (from outside the market)? You are coming
for my money, what am I going to gain from you?‘ If this happens, they have negative
minds about you the agent. So you have to change their mind. So unless you talk and talk
and talk before he or she will understand… [Agents, Star Micro Insurance Company,
Accra].
For me I want to explain why for us as Ghanaians we don‘t take insurances as my brother
mentioned earlier. Before you enter into any venture for the first time, you normally
listen to the experiences of other people. I have a cousin whose leg was amputated due to
a car accident. The benefit he had to receive from his insurance took about eight years.
He had to go to court before receiving his benefits. The benefit that was given him in the
long run was not the full benefit as promised initially. They will always use enticing
speech to get you into it but later they would not give you your full benefits. Having
heard this, you will be advised to rather invest in farming in the village. For that, when
your leg is cut, they will harvest some cocoa, sell it and use it for your hospital bills
[Clients, Donewell Insurance Company, Kumasi].
17
My uncle‘s nephew had an accident. For six years, they had to travel to Accra frequently
to their office in order to make their claims. Even through this travelling, one of them had
an accident and died. With this, I will say that the insurance was not beneficial [Noninsured persons, Kumasi].
What people do not like is the fact that you go through so much stress before you make
claims. Even when your money is given to you, it turns out to be lesser and insufficient
[Non-insured group, Kumasi].
In addition, there was the general consensus amongst the clients that the policies of the insurance
companies are cumbersome, and sometimes, it is simply not lucrative to work with them. A male
client of SIC Life recounted his experience where he needed GHc 1,400 to clear goods from the
Tema Harbour and had a policy with SIC Life worth GHc 7,000 that would mature in 4 months.
According to him, SIC agreed to give him the loan on a condition that they would hold unto his
benefits, if it matured, till he has paid off the loan he took from them. ‗What is the point in this?
Why won‘t they rather reduce the saving by the loan amount and give me my entitlements? I did
not take the loan; I rather claimed part of my entitlement.‘ ‗When you hear these things, you are
definitely discouraged from having the coverage with them...‘ a female colleague in the
discussion quipped, in support of the male respondent.
This situation is partly worsened by the general feeling even amongst the staff and agents of
insurance companies, that the companies do not pay much attention to educating the clients in
the insurance schemes. Nevertheless, the clients of the SIC Life Company felt that they
understand the insurance scheme, to a large extent. Against this background, however, the
respondents were of the view that most Ghanaians would not have a problem having insurance in
the areas of theft, fire, accident, education, home, motor, funeral and life policies.
Concentrating on the catastrophes farmers in Ghana frequently face, the majority of the
discussants, mostly the insurance agents and staff, felt that the farmers need to protect their
investments by purchasing insurance, with the reservation that it will be difficult for the
insurance firms to support such a venture. However, all the non-insured respondents felt that the
government should have policies that protect Ghanaian farmers against loss of their investments
without having the latter bear the cost because Ghanaian farmers play a very crucial role in the
life of the country.
When we look at our farmers, they feed the whole nation so either the government or an
NGO should put some funds down/create a fund from which they can help insure
farmers….Farmers are very important so the government should be able to assist them
just as the government helps the ministers [Non-insured respondents, Kumasi].
The rather poor attitude toward insurance among Ghanaians was blamed on the way insurance
was purported to have started in the country—it started too late, education on insurance has not
kept pace with the increasing population, it was promoted as being for the rich, the well
educated, and formal sector employees; the initial insurance companies were said to be corrupt,
and the health insurance scheme was particularly politicized and criticized by some groups as
being bad.
18
Some of the clients disclosed that some Ghanaians think that insurance is only for workers in the
formal sector, or for the rich and well educated persons:
For many, they think insurance was for government workers but artisans, traders or small
scale workers like us do not need insurance. I think the low education level is the cause
for the low patronage [Clients, Donewell Insurance Company, Kumasi].
I have heard about it. Initially when insurance cropped up through the NHIS, we all knew
about it but then some leaders stood up against it and so I thought it was not good to get
insured [Non-insured group, Kumasi].
In line with the general mistrust for insurance companies, there was a consensus that generally,
Ghanaians would be more comfortable dealing with credible insurance firms and, thus, would
more gladly buy policies from firms that are government- or institutionally- or Church-owned.
With some of my clients, because they think the interest on the Sikaplan is not much,
they go to these private savings companies and then all of a sudden the businesses close
down, their money is then lost; they will say oh with SIC Sikaplan it is a government
institution no matter how the profit on it is not that much, your money is still safe and
secure so they will come back; because of the risk that happen to them, they will come
back, and come and save with Sikaplan [Agents/Staff, SIC Life, Accra].
I got mine from Donewell Insurance Company because I got to know that they belonged
to a church [Staff/Agents, Donewell Insurance Company, Kumasi].
For some, it‘s because of the personal relationship and the fact that it is run by a church –
the Methodist Church. Some say it‘s because of the slogan ―If it must be done, it must be
done well‖ [Staff/agents, Donewell Insurance Company, Kumasi].
6. Multivariate Results
After controlling for other variables in the probit regression models, we found a few factors that
were significantly related to lower levels of insurance literacy and unfavorable attitudes towards
insurance (Table 17). Insurance literacy was particularly high for households headed by males.
Households with higher levels of income had significantly higher insurance literacy.
Respondents with more than a senior high school education had higher levels of insurance
literacy. Interestingly, female-headed households scored better than male-headed households.
Both education of the head and income status of the household were found to be positively
correlated with the attitude index. Finally, we find that, ceteris paribus, a household‘s awareness
of insurance positively influences the household likelihood of insurance uptake.
19
Table 17: Determinants of Awareness of Insurance and Insurance Uptake
VARIABLES
Age of household head
Female head
Rural
Junior secondary
Senior secondary
Formal wage employment
High socio-economic status
Medium socio-economic status
Attitude index
Knowledge index
Insurance Uptake
-0.000297
(0.00044)
0.0191*
(0.011)
-0.00057
(0.0107)
0.0135
(0.0139)
0.0377**
(0.0154)
0.00827
(0.0122)
0.0368*
(0.0187)
0.0190*
-0.0115
-0.00014
-0.00105
-0.0441*
-0.0263
0.00579
-0.0255
0.042
-0.0332
0.104***
-0.0367
-0.00418
-0.0292
0.0792*
-0.0448
0.0181
-0.0274
-0.0300*
-0.0155
-0.0161
-0.0147
-0.00931
-0.0179
0.724***
-0.0277
0.084
283
-0.0108
-0.0372
0.0636*
-0.0352
0.0443
-0.0428
0.597***
-0.0662
0.1
283
0.0117*
-0.00701
0.187
-0.174
0.00503
-0.167
0.414*
-0.213
0.844***
-0.247
0.333*
-0.195
0.148
-0.311
0.0977
-0.18
2.301***
-0.704
-0.313
-0.253
-0.602**
-0.241
-0.700**
-0.286
-2.060***
-0.655
0.13
283
Insurance awareness index
Greater Accra region
Ashanti region
Northern region
Constant
R-squared
Observations
Source: Authors‘ calculations.
Notes: * significant at 10%; ** significant at 5%; *** significant at 1%.
7. Conclusion and Recommendations
This study investigates the level of insurance literacy and awareness in Ghana. A number of
interesting findings emerged from the study. The results show that many people have heard of
the word insurance. The mean insurance awareness score is 0.65. Male respondents scored better
than females on the awareness index. Stakeholders should increase insurance awareness
campaigns among females particularly. There are also regional heterogeneities – respondents in
the Ashanti and Northern regions scored better on the literacy index. Surprisingly, Greater Accra
respondents have the lowest score. They, thus, have the greatest need for insurance education.
20
The determinants of awareness are age, gender and educational status of respondents. Age is a
statistically significant variable and positively predicts insurance literacy and attitude towards
insurance. Older individuals are generally more knowledgeable in insurance. Higher literacy
scores coincide with respondents being male and enjoying a better education.
The FGDs revealed that the vast majority of Ghanaians are generally aware of insurance,
particularly stemming from the information dissemination on the NHIS. Yet there was the
general feeling that beyond awareness, Ghanaians generally do not know about the operations of
insurance schemes nor understand how they operate. The all too-familiar Susu concept of saving
worsens this as it has permeated the views of most Ghanaians about insurance—wrongly about
instant and automatic benefits. This is coupled with the fact that it was felt that the Ghanaian
culture does not support the need to acquire insurance—planning for misfortune would trigger it,
God protects Ghanaians and will prevent catastrophe from befalling us, and also, the social
protection system takes care of some of the reasons for which we would acquire insurance.
The qualitative and quantitative results have some agreements but also, very interesting
disagreements. Among the agreements are that 1) most Ghanaians are aware of/have heard about
insurance, and 2) that the knowledge about health insurance is mostly due to the pervasiveness of
the information on the NHIS. Some critical disagreements between the qualitative and
quantitative studies are that first, the survey respondents indicated that they have high level of
confidence in insurance providers, and can trust them to be fair to them while the qualitative
study said otherwise: most of the respondents felt that they themselves as well as Ghanaians in
general are distrustful, even suspicious of insurance companies. Second, while the respondents
from the FGDs felt that most Ghanaians do not understand the concept of insurance (and even
the insurance clients we interviewed themselves felt that they do not fully understand how to
make claims and some key concepts in insurance, such as premium), the survey found otherwise:
most of the survey interviewees said they have complete knowledge about how insurance works
than otherwise. Some of this mistrust generally point to micro-credit schemes in Ghana, probably
rather than insurance schemes.
The overarching mistrust for insurance for insurance schemes/companies, however, is greatly
enhanced by the reported fallout from the NHIS. The beneficiaries of the latter were reported /are
perceived as being disadvantaged when they go for health care, compared to those without the
NHIS registration. A likely explanation for the discrepancies in the findings between the
qualitative and quantitative methods may be that respondents have favorable perception of the
insurance concept, but not the way it is provided in Ghana. More generally however, we sway
more to the findings from the qualitative studies, when it comes to these disagreements in the
findings. It is easier for respondents in the individual survey situations to give socially desirable
responses3, than it is with group simulated situations, as in the FGDs. Furthermore, we
understand the findings from the FGDs when it comes to the mistrust for the insurance
companies, yet the affinity for insurance agents as a dependency relationship, as it were, between
clients and the insurance agents, where as the latter mentioned, a typical client may not even
have time to read his or her policy, and thus leaves better room for the clients to depend on the
agents for most of the transactions. In this scenario, the distrust for the insurance companies, yet
the trust for the agents makes sense.
3
Babbie, E. R. (2010)
21
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