The Level of the Financial Inclusion in the African Countries and in the World Group Regions. Kokou Adalessossi. Akdeniz University, Antalya, Turkey

Transcription

1 China-USA Business Review, March 2015, Vol. 14, No. 3, doi: / / D DAVID PUBLISHING The Level of the Financial Inclusion in the African Countries and in the World Group Regions Kokou Adalessossi Akdeniz University, Antalya, Turkey One key component of inclusive development is financial inclusion, an area in which Africa has been lagging behind unlike other continents. At most, one adult out of four in Africa has access to an account in a formal financial institution. The objective of this study is to find out the level of the financial inclusion among 41 African countries on one hand and the level of the financial inclusion among the world six group regions on the other hand. To find out which country or which group region has a higher level or a lower level in the financial inclusion, according to some indicators, such as account at a formal financial institution, access to formal accounts, use of formal accounts, mobile payments, savings, credits patterns, and insurance decision as underlined in the literature review that the latter constituted the principal indicators for inclusive financing, an appropriate and reliable statistical method has been used, such as cluster analysis. The data set was the secondary data taken from the World Bank website; the first data published by the World Bank in 2012 on the global financial inclusion concerning 148 countries in the world. The empirical results from this study reveal that most of African countries with lower levels are low-income countries and those with higher levels remain largely of middle-income countries. Among the world group regions, only Sub-Saharan African region has the low level in five of the seven indicators used in this research, when compared with the other group regions. This study will awaken most African countries including the Sub-Saharan African region to develop strategies to enhance their level in the future in order to reduce poverty and to strengthen their financial system which leads to economic growth. Keywords: African countries, financial inclusion, World Bank, indicators, cluster analysis Introduction Africa is now the world s second fastest growing region after Asia, with annual GDP growth rates in excess of 5% over the last decade (Thouraya & Faye, 2013). Despite this growth, the Arab Spring events showed that good economic growth in the continent has not translated into shared prosperity and better livelihoods for the majority. Growth has to be inclusive to be socially and politically sustainable. One key component of inclusive development is financial inclusion, an area in which Africa has been lagging behind other continents. Less than one adult out of four in Africa has access to an account at a formal financial institution. Broadening access to financial services will mobilize greater household savings, marshal capital for investment, expand the class of entrepreneurs, and enable more people to invest in themselves and their families. Kokou Adalessossi, Ph.D. student researcher in finance, Faculty of Economics and Business Administration Sciences, Business Administration Department, Akdeniz University, Antalya, Turkey. Correspondence concerning this article should be addressed to Kokou Adalessossi, Akdeniz University, Dumlupinar Bulvari, Kampus, Antalya, Turkey. Tel: pascaladalessossi@yahoo.fr.

2 130 FINANCIAL INCLUSION IN THE AFRICAN COUNTRIES In recent decades, access to financial services has been dramatically improved in African countries (Thouraya & Faye, 2013). More financial services, especially credit, are now provided to individuals and enterprises. New technologies, such as mobile money, have also helped broaden access to financial services, including savings and payment products. Yet, until recently, in Africa and elsewhere, little was known about the reach of the financial sector the extent of financial inclusion and the degree to which disadvantaged groups, such as the poor, women, and youth, are excluded from formal financial systems. Financial services are increasingly being seen as important to poverty reduction and achievement of the millennium development goals. By borrowing, saving, or buying insurance, the poor can plan for their future beyond the short term. They can build up assets and invest in education and health. Financial services can help them cope in times of need and hardship. Beyond this, access to financial services can promote social inclusion and build self-confidence and empowerment, in particular among women. Access to financial services plays a critical part in development by facilitating economic growth and reducing income inequality. Inclusive financial systems allow poor people to smooth their consumption and insure themselves against economic vulnerabilities, from illness and accidents to theft and unemployment. Financial access enables poor people to save and borrow allowing them to build their assets, to invest in education and entrepreneurial ventures, and thus to improve their livelihoods. While significant progress has been made in expanding access to financial services by the poor, there is still more to be done. It is estimated that more than 2.7 billion people in developing countries (World Bank, 2008), particularly Africa countries the majority of adults are still excluded from the financial services market. Inclusive financing is especially likely to benefit disadvantaged groups, such as women, youth, and rural communities. For all these reasons, financial inclusion has gained prominence in recent years as a policy objective to improve the lives of the poor. Financial inclusion or inclusive financing is the delivery of financial services at affordable costs to sections of disadvantaged and low-income segments of society, in contrast to financial exclusion where those services are not available or affordable. Adults of an estimated 2.5 billion working-age globally have no access to the types of formal financial services delivered by regulated financial institutions (World Bank, 2012), for example, in Sub-Saharan Africa, only 24% of adults have a bank account even though African formal financial sector has grown in recent years. It is argued that as banking services are in the nature of public good, the availability of banking and payment services to the entire population without discrimination is the prime objective of financial inclusion public policy. The aim of this study is to find out their level in the inclusive financing in one side among 41 African countries and measure the level of the financial inclusion among the world six group regions in the second side. This is to show that, according to some indicators, which country and group region has a high level in financing inclusion. After touching by finger which the literature review has said about in the second section, this paper will move on the data and methodology of the research in the third section. The empirical results analysis and discussions are in the fourth section before concluding at the end. Literature Review Conceptual Framework of Financial Inclusion Committee on financial inclusion defines financial inclusion as delivery of financial services at an affordable cost to vast sections of disadvantaged and low-income groups (Government of India, 2008). Unrestrained access to public goods and services is the essential condition of an open and efficient society. This

3 FINANCIAL INCLUSION IN THE AFRICAN COUNTRIES 131 view is reiterated in the definition the process of ensuring access to timely and adequate credit and financial services to vulnerable groups at an affordable cost (Kamath, 2007, pp ). As banking services are in the nature of public good, it is essential that availability of banking and payment services to the entire population without discrimination should be the prime objective of the public policy. The international definitions of financial inclusion have been viewed in much wider perspective (Leeladhar, 2005). The definitions of financial inclusion emphasize several dimensions (Sharma, 2008), e.g., accessibility, suitability, availability, and usage of the financial system. These dimensions together build an inclusive financial system. Another issue that needs to be taken care of is whether to measure access or usage. Because in transaction banking and insurance, it can be found that people do not use it, even if they have access to it. Access dimension implies mere access to services, while usage dimension is a broader term requiring examination of aspects like access, suitability, availability, and actual usage. World Bank World Bank also distinguishes between those who are formally served (have access to financial services from a bank and/or other formal providers) and those who are financially served (include people who use informal providers). In contrast to the other work described above, the term financially excluded is only used to describe those who have no access at all (World Bank, 2005). This study considers only the formal sector which includes all legally endorsed financial services. The definitions of financial inclusion vary across the geographic regions decided by the concomitant economic development. This study focuses on financial inclusion with respect to the poorest of the poor and emphasizing a wider connotation of the term financial services than defining it in a narrow perspective of owning a savings account with a bank. The definition of several aspects of the term propounded by several authors, committees, and commissions is reviewed here to arrive at an acceptable working definition. Definitions of financial inclusion in literature tend to vary on dimensions, such as breadth, focus, and degree of exclusion (Reserve Bank of India, 2009). The breadth dimension is the broadest of all definitions which defines financial inclusion, as a consequence of social inclusion which prevents the poor and the disadvantaged from gaining access to the mainstream financial system. Some of the definitions of financial inclusion reiterating this view are as follows. Financial inclusion infers accessibility and usage of financial services from formal service providers. United Nations (2006) defined financially inclusion as the financial sector that provides access to credit for all bankable people and firms, to insurance for all insurable people and firms, and to savings and payments services for everyone. Inclusive finance does not require that everyone who is eligible uses each of the services, but he should be able to choose to use them if desired. The degree dimension is the narrowest of all and defines financial exclusion as exclusion from usage of particular sources of credit and other financial services, including insurance, bill payment services, and accessible and appropriate deposit accounts. World Bank (2005) described exclusion as a phenomenon with access to key areas, such as transaction banking, savings, credit, and insurance. For the purpose of the study, this definition has been accepted as the bench mark. Though all services including credit, savings, and insurance offered by the banks and other financial institutions are taken as the benchmark, more weight age is given to credit segment. Financial inclusion may be interpreted as the ability of every individual to access basic financial services which include savings, loans, and insurance in a manner that is reasonably convenient and flexible in terms of access and design; and reliable in the sense that savings will

4 132 FINANCIAL INCLUSION IN THE AFRICAN COUNTRIES be safe and that insurance claim will be paid with certainty (Mor & Ananth, 2007). Indeed, having a current account/savings account on its own cannot be regarded as an accurate indicator of financial inclusion (Chatrath & Vallabh, 2006). Financial inclusion is characterized primarily as either general access to loans or access to savings accounts (Arunachalam, 2008). Very few risk management and vulnerability reducing products are available to small holder producers. Financial inclusion cannot only be restricted merely to opening savings accounts and/or providing credit for consumption/consumer spending, but should also encompass delivering financial products tailor-made to cope with the fluctuating earning pattern of the poor. Rogaly (1999) defined financial exclusion in the perspective of exclusion from particular sources of credit and other financial services (including insurance, bill payment services, and accessible and appropriate deposit accounts). The review of literature suggests that most of the definitions are context specific, originating from country specific problems related to financial exclusion with regard to the respective of socio-economic dimensions which assumes importance in the public policy perspective. On the basis of the above review, the following working definition has been accepted with regard to financial inclusion throughout the study Financial inclusion may be interpreted through poor households access to basic financial services from formal and semiformal service providers which include savings, loans, insurance, and other financial services in a manner that is reasonably convenient and flexible in terms of access and design. In this perspective, the study attempts to measure financial inclusion as a composite one that takes into consideration access to transaction banking, savings, credit, and insurance: Transaction banking: It refers to access to bank s financial services other than savings, credit, and insurance; Savings: Lesser savings leads to lesser capital formation implying lesser development. Not having a savings account can lead to financial exclusion; Credit: It is the most valid indicator for assessing the status of financial inclusion. Though other indicators are measured, credit access and indebtedness of a family determine the level of well being achieved. Credit measured as a sole measure of financial inclusion can also be useful, because it may provide status of the stakeholder considering aspects like source, cost of borrowing, adequacy, proximity, and etc.; Insurance: Insurance provides coverage to the accidents/emergencies arising in a society affecting human lives, assets, or livelihoods. Recent developments have increased popularity and access to insurance. Also government has enacted insurance policies for the benefit of sea faring fishers. Insurance inclusion is measured as sub element in the financial inclusion designating appropriate weights. Data and Research Methods Data The data set of this study was taken from the global index database covering 148 economies that includes 41 African countries (Demirgüç-Kunt & Klapper, 2012). This data was published in 2012 by the World Bank on its website titled The Global Financial Inclusion using indicators, such as formal bank accounts, payments behavior, savings patterns, credit patterns, and insurance decisions. This data provides country-level indicators of financial inclusion summarized for all adults and disaggregated by key demographic characteristics gender, age, education, income, and rural or urban residence. This research chose 41 African countries, according to the World Bank s available data for countries and

5 FINANCIAL INCLUSION IN THE AFRICAN COUNTRIES 133 the six regions: East Asia and Pacific (grouping nine countries), Europe and Central Asia (grouping 24 countries), Latin America and the Caribbean (grouping 19 countries), Middle East and North Africa (grouping 12 countries), South Asia (grouping six countries), and Sub-Saharan Africa (grouping 36 country). Research Methods To perform this study, the appropriate and reliable statistical method used is the method of two-step clusters analysis. It enables identifying groups of individual or objects that are similar to each other, but different from individuals in other group. This method will help to classify the countries into two groups and will show which of them belongs to first group and the second group. The limit of this study is that all the African countries (54) did not take part in this study. Indeed, it will be very good that all the African countries took part with a view to gauging the level of all countries in inclusive financing. But due to the World Bank group classification, only 41 African countries data were accounted for. Method of Cluster Classification and clustering have become an increasingly popular method of multivariate analysis over the past two decades and they have become a vast amount of published material. Since there is no journal devoted exclusively to cluster analysis as a general topic and it has been used in many (Scoltock, 1982) fields of study, the novice user is faced with the daunting prospect of searching through a multitude of journals for appropriate references. It has already been suggested that cluster analysis techniques have been applied to data from numerous and diverse fields of study. In his review, Anderberg (1973) attributed the diversity to a mixture of professional jealousy, relative isolation among the fields and genuine differences of viewpoint. Porter (1998), who is the most frequently cited advocate and analyst of cluster policy, defined clusters as geographic concentrations of interconnected companies and institutions in a particular field, linked by commonalities and complementarities. Cluster analysis classifies a set of observations into two or more mutually exclusive unknown groups based on combinations of interval variables. The purpose of cluster analysis is to discover a system of organizing observations, usually people and objects into groups where members of the groups share properties in common. It is cognitively easier for people to predict behavior or properties of people or objects based on group membership, all of whom share similar properties. It is generally cognitively difficult to deal with individuals and predict behavior or properties based on observations of other behaviors or properties. Cluster analysis classifies unknown groups, while discriminant function analysis classifies known groups. The procedure for doing a discriminant function analysis is well established. There are few options, other than type of output, that need to be specified, when doing a discriminant function analysis. Cluster analysis, while, allows many choices about the nature of the algorithm for combining groups. Each choice may result in a different grouping structure. There are three types of clusters: two-step cluster analysis, hierarchical cluster, and non-hierarchical clusters (k-means cluster). In this research, two-step cluster analysis is used to classify the countries in two groups using SPSS 13. Definition of Variables Variables used for this research are all continuous ones (independents variables). These variables are recapitulated in the Table 1.

6 134 FINANCIAL INCLUSION IN THE AFRICAN COUNTRIES Table 1 Variables (Independents) A Account at a formal financial institution A1 All adults (%, age 15+) A2 Adults with a primary education or less (%, age 15+) A3 Adults with a secondary education or more (%, age 15+) A4 Adults living in a rural area (%, age 15+) A5 Adults living in an urban area (%, age 15+) B Access to formal accounts (%, age 15+) B4 3+ deposits in a typical month (% with an account) B7 3+ withdrawals in a typical month (% with an account) B3 ATM is the main mode of deposit (% with an account) B4 ATM is the main mode of withdrawal (% with an account) B5 Has debit card C Use of formal accounts (%, age 15+) C1 Use an account for business purposes C2 Use an account to receive wages C3 Use an account to receive government payments C4 Use an account to receive remittances C5 Use an account to send remittances D Mobile payments (%, age 15+) D1 Use a mobile phone to pay bills D2 Use a mobile phone to send money D3 Use a mobile phone to receive money E Savings (%, age 15+) E1 Saved any money in the past year E2 Saved at a formal financial institution in the past year E3 Saved using a savings club in the past year E4 Saved for future expenses in the past year E5 Saved for emergencies in the past year F Credit (%, age 15+) F1 Loan from a formal financial institution in the past year F5 Outstanding loan for home construction F6 Outstanding loan to pay school fees G Insurance (%, age 15+) G1 Personally paid for health insurance Source: Author s compilations. Empirical Results Analysis and Discussion To get reliable results and to reach the objective of this study, it is necessary that an appropriate statistical method like two-step cluster analysis be used. Financing inclusive variables were taken from the global index database. All the variables used in these studies were all independent. To judge or check out if the two-step cluster analysis has perfectly discriminated the countries and world group regions, the within cluster variation in the SPSS was examined. For all the variables, it has been shown that two groups were correctly separated from each other. The first group was above the horizontal line and the second group was at the bottom of the horizontal line. This shows that two-step cluster analysis was successfully performed for this analysis.

7 FINANCIAL INCLUSION IN THE AFRICAN COUNTRIES 135 Table 2 Cluster Distribution/Account at Formal Financial Institution No. % of combined % of total Cluster % 40.4% % 59.6% Combined % 100.0% Total % In Table 2, the cluster distribution, when based on account at formal financial institution, shows that out of the 47 countries and world group regions, 19 were classified in the first group (high level), whereas 28 of them are classified in the second group (low level). It means that eight countries and world group regions have the high level in account at formal financial institution. Table 3 Cluster Profiles Centroids/Account at Formal Financial Institution Cluster All adults (%, age 15+) Adults with a primary education or less (%, age 15+) Adults with a secondary education or more (%, age 15+) Adults living in a rural area (%, age 15+) Adults living in an urban area (%, age 15+) Mean Deviation Mean Deviation Mean Deviation Mean Deviation Mean Deviation Combined Observing the cluster profiles in Table 3, when based on account at formal financial institution, it is shown that countries and world group regions of the first group (high level) have accounted for higher value in mean and standard deviation than those in the second group. Table 4 Cluster Distribution/Access to Formal Account No. % of Combined % of Total % 46.8% Cluster % 53.2% Combined % 100.0% Total % The results in Table 4 show that, when based on access to formal account, out of the 47 countries and world group regions, 19 (46.8%) were classified in the first group (high level), whereas 28 of them are classified in the second group (low level). It means that eight countries and world group region have a high level in account at formal financial institution. The results from Table 5 show that the first group (high level) of countries and world group regions compared to the second when based on access to formal account has the high value in mean and standard deviation.

8 136 FINANCIAL INCLUSION IN THE AFRICAN COUNTRIES Table 5 Cluster Profiles Centroids/Access to Formal Account Cluster 3+ deposits in a typical month (% with an account) Mean 3+ withdrawals in a typical month (% with an account) ATM is the main mode of deposit (% with an account) ATM is the main mode of withdrawal (% with an account) Has debit card Deviation Mean Deviation Mean Deviation Mean Deviation Mean Deviation Combined Table 6 Cluster Distribution Use a Formal Account No. % of Combined % of Total % 23.4% Cluster % 76.6% Combined % 100.0% Total % The results in Table 6 show that, when based on access to formal account, out of the 47 countries and world group regions, 11 (23.4%) were classified in the first group (high level), whereas 28 of them were classified in the second group (low level). It means that 11 countries and world group regions have the highest level in a formal account. Table 7 Cluster Profiles Centroids/Use a Formal Account Use an account for business purposes Use an account to receive wages Use an account to receive government payments Use an account to receive remittances Use an account to send remittances Mean Deviation Mean Deviation Mean Deviation Mean Deviation Mean Cluster Combined Deviation In Table 7, it is shown that the first group has the higher value than the second group when based on a formal account. Table 8 Cluster Distribution in Mobile Payments No. % of Combined % of Total Cluster % 17.0% % 83.0% Combined % 100.0% Total %

9 FINANCIAL INCLUSION IN THE AFRICAN COUNTRIES 137 The cluster distribution in Table 8 shows that out of the 47 countries and world group regions, eight were classified in the first group, whereas 39 of them were classified in the second group. It means that eight countries and world group regions have a high level in mobile payment (use a mobile phone to pay bills, send money, and receive money). Table 9 Cluster Profiles Centroids in Mobile Payments Use a mobile phone to send Use a mobile phone to receive Use a mobile phone to pay bills money money Mean Deviation Mean Deviation Mean Deviation Cluster Combined Table 9 shows that, trough mobile payments, the first group (high level) has the higher value in mean and standard deviation than the second group. Table 10 Cluster Distribution Savings No. % of Combined % of Total % 38.3% Cluster % 61.7% Combined % 100,0% Total % The cluster distribution shown in Table 10 indicates that out of the 47 countries and world group regions, 18 (38.3%) were classified in the first group, whereas 29 (61.7%) of them were classified in the second group. It shows that 18 countries and world group regions have the high level in savings patterns. Table 11 Cluster Profile Centroids in Savings Cluster Saved at a formal financial institution in the Saved for emergencies in the past year past year Mean Deviation Mean Deviation Combined Table 11 shows that the countries and world group regions belonging to the first group have accounted to higher value in mean and standard deviation, when based on savings patterns than those belonging to the second group. Also, the examination of the within cluster variation in the SPSS shows that the two groups were correctly separated from each other. The first group was above the horizontal line and the second group was at the bottom of the horizontal line. This indicates that the two-step cluster analysis has successfully discriminated the countries and world regions in two groups.

10 138 FINANCIAL INCLUSION IN THE AFRICAN COUNTRIES Table 12 Cluster Distribution in Credits Patterns No. % of Combined % of Total Cluster % s % 51.1% Combined % 100.0% Total % The results in Table 12 show that, when based on credits patterns, out of the 47 countries and world group regions, 23 (48.9%) were classified in the first group (high level), whereas 24 of them are classified in the second group (low level). This means that 23 countries and world group regions have the highest level in credits patterns. Table 13 Cluster Profiles Centroids in Credits Patterns Loan from a formal financial institution in the past year Outstanding loan for home construction Outstanding loan to pay school fees Mean Deviation Mean Deviation Mean Deviation Cluster Combined In Table 13, when based on credits patterns, countries and world group regions that belong to the first group account for higher value in mean and standard deviation than those in the second. Table 14 Cluster Distribution in Insurance Decision No. % of Combined % of Total Cluster % 12.8% % 87.2% Combined % 100.0% Total % The cluster distribution shown in Table 14 shows that out of the 47 countries and world group regions, six (12.8%) were classified in the first group, whereas 41 (87.2%) of them are classified in the second group. It explains that only six countries and world group regions have the high level insurance decision. Table 15 Group of Countries and World Group Regions Countries/regions Account at a formal financial institution Access to formal accounts Use of formal Accounts) Mobile payments Savings patterns Credits patterns Algeria Angola Benin Insurance decision

11 FINANCIAL INCLUSION IN THE AFRICAN COUNTRIES 139 Table 15 continued Countries/regions Account at a formal financial institution Access to formal accounts Use of formal Accounts) Mobile payments Savings patterns Credits patterns Botswana Burkina Burundi Cameroun CentAfriRep Chad Comoros CngoRepD CongoRep Djibouti Egypt Gabon Ghana Guinea Kenyan Lesotho Madagascar Malawi Mali Mauritania Mauritius Moroco Mozambique Niger Nigeria Rwanda Senegal Siera Leone Somali South Africa Sudan Swaziland Tanzania Togo Tunisie Uganda Zambia Zimbabwe EAsia&Pacific Eurpe&CntralAsia LtinAmca&Caraibbean Middle East North Africa South Asia SubSaharan Africa Source: Author s compilation. Insurance decision

12 140 FINANCIAL INCLUSION IN THE AFRICAN COUNTRIES The results shown in Table 15 are in the following. According to the indicator account at formal financial institution, 15 African countries (Algeria, Angola, Botswana, Ghana, Kenyan, Mauritius, Morocco, Mozambique, Nigeria, Rwanda, Zimbabwe, South Africa, Swaziland, Tunisia, and Somali) were located in the group of high level, whereas the remaining 26 African countries were in the group of low level. Based on the six world group regions, four world group regions, such as East Asia and Pacific, Europe and Central Asia, Latin America and the Caribbean, and South Asia, have a high level and two of them (Middle East and North Africa and Sub-Saharan Africa) were in the group of the low level. Concerning the indicator access to formal account, 18 countries (Angola, Botswana, Chad, Djibouti, Kenyan, Lesotho, Zimbabwe, Nigeria, Somali, South Africa, Sudan, Swaziland, Tanzania, Tunisia, Zambia, Mauritius, Morocco, and Mozambique) have the high level, whereas 23 counts have the low level in having access to formal account. Concerning the indicators use of formal account (use an account for business purposes, use an account to receive wages, use an account to receive government payments, use an account to receive remittances, and use an account to send remittances), 11 countries (Angola, Botswana, Ghana, Kenyan, Morocco, Mozambique, Nigeria, Somali, South Africa, Swaziland, and Zimbabwe) have a high level in this indicator, whereas 30 countries have low level in this in this indicator, according to the cluster analysis. Concerning the world group regions, all the six groups have the low level in the use of formal account. Based on the use mobile payments indicator (use a mobile phone to pay bills, use a mobile phone to send money, and use a mobile phone to receive money), only eight countries (Algeria, Angola, CongoRep, Gabon, Kenyan, Somali, Sudan, and Uganda) have a high level in it, while 33 Africans countries and the six world group regions have taken place in the low level group. Based on the savings and credits patterns, it is found that 16 countries respectively (Angola, Botswana, Cameroun, Ghana, Kenyan, Mozambique, Mauritius, Nigeria, Rwanda, Sierra Leone, South Africa,Zambia, Tanzania, Uganda, Zimbabwe, and Swaziland) have had a high level in the savings patterns (saved for emergencies in the past year and saved at a formal financial institution in the past year) and 19 countries ( Angola, Botswana, Cameroun, Chad, Comoros, Djibouti, Egypt, Ghana, Kenyan, Malawi, Mauritania, Mauritius, Mozambique, Rwanda, South Africa, Sudan, Uganda, Tanzania, and Swaziland) have had a high level in credits (loan from a formal financial institution in the past year, outstanding loan to pay school fees, and outstanding loan for home construction), while 25 countries have had a low level in savings patterns and 22 countries did not have a high level in credits patterns. Moreover, out of the six world group regions, only two regions (Sub-Saharan Africa and East Asia and Pacific) and five regions (Latin America and the Caribbean, East Asia and Pacific, Europe and Central Asia, South Asia, and Middle East and North Africa) have a high level respectively in savings and credits patterns, while four group regions (Europe and Central Asia, Latin America and the Caribbean, Middle East and North Africa, and South Asia) and only one region group (Sub-Saharan Africa) respectively have a low level in savings and in credits patterns. Concerning the indicator insurance decision, six countries (Benin, Morocco, Swaziland, South Africa, Mauritius, and Mozambique) well classified in this indicator, have a high level in insurance decision (personally paid for health insurance), the remaining 35 countries have a low level in the latter.

13 FINANCIAL INCLUSION IN THE AFRICAN COUNTRIES 141 According to the world group regions, five group regions (East Asia and Pacific, Europe and Central Asia, Latin America and the Caribbean, Middle East and North Africa, and South Asia) have a high level in personally paid for health insurance, while one group (Sub-Saharan Africa) have a low level in it. Conclusions The aim of this study which is to find out the level in financial inclusion among 41 African countries on one hand and the level in financial inclusion among the six world group regions on the other hand using cluster analysis has led to successful results. The analysis of the results of this study with the use of the two-step cluster analysis, when based on seven variables/indicators (account at a formal financial institution, access to formal accounts, use of formal accounts, mobile payments, savings patterns, credits patterns, and insurance decision), revealed that most African countries with low levels are low-income countries and those with high levels remain largely of middle-income countries. Moreover, Sub-Saharan Africa is the only region that was classified in the second group for five indicators and was the only one classified in the first group for two indicators (access to formal accounts and credits patterns) This research is the first concerning the comparison of level among African countries and among the world group regions in financial inclusion using two-step cluster analysis. This research permits to gauge African countries and six world group regions level in financial inclusion. Furthermore, this will enable to wake up the African countries that have a low level in the financial inclusion in some indicators, to develop strategies to enhance their level in the future, reduce poverty, and also enhance the economic growth. Shortly, this research on global financing inclusion based on developing countries (particularly African countries and the world group regions) enables to categorize the difference among these countries on one hand and the difference among the world group regions on the other hand. This research can contribute largely to the literature review. References Anderberg, M. R. (1973). Cluster analysis for applications. London: Academic Press. Arunachalam, R. S. (2008). Scoping paper on financial inclusion, considerations and recommendations for UNDP. Retrieved from Chatrath, S., & Vallabh, G. (2006). Role of banks in agricultural and rural development. Retrieved from Demirgüç-Kunt, A., & Klapper, L. (2012). Measuring financial inclusion: The global index database (World Bank Policy Research Working Paper 6025, World Bank, Washington, D.C.). Government of India. (2008). Report of the committee on financial inclusion. Retrieved from http// Kamath, R. (2007). Financial inclusion vis-à-vis social banking. Economic and Political Weekly, 42(15), Leeladhar, V. (2005). Taking banking services to common man: Financial inclusion (Commemorative lecture at the Fedbank Hormis Memorial Foundation at Ernakulam on December 2). Mor, N., & Ananth, B. (2007). Inclusive financial systems: Some design principles and a case study. Economic and Political Weekly, 42(13), Porter, M. (1998). Competitive advantage. Creating and sustaining superior performance. New York: Free Press. Reserve Bank of India. (2005). Report of the internal group to examine issues relating to rural credit and microfinance. Retrieved from Rogaly, B. (1999). Poverty and social exclusion in Britain: Where finance fits. In B. Rogaly, T. Fisher, & E. Mayo (Eds.), Poverty, Social exclusion and microfinance in Britain. Oxford: Oxfam GB. Scoltock, J. (1982). A survey of the literature of cluster analysis. The Computer Journal, 25(1),

14 142 FINANCIAL INCLUSION IN THE AFRICAN COUNTRIES Sharma, M. (2008). Index of financial inclusion (Working paper 215, Indian Council for Research on International Economic Relations (ICRIER), Thouraya, T., & Faye, I. (2013). Financial inclusion in Africa. Retrieved from United Nations. (2006). Advisors group on inclusive financial sectors united nations. Retrieved from World Bank. (2005). Indicators of financial access: Household level surveys. Retrieved from ss_household_level_surveys.pdf World Bank. (2008). Finance for all? Policies and pitfalls in expanding access. Retrieved from World Bank. (2012). The little data book on financial inclusion. Retrieved from http/