The World's Ten Poorer - A Dozen Of Microcredit Countries

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1 Landscapes of microfinance: data sources of access to finance By Hans Dieter Seibel August 2013 Major efforts have been made since the 1990s to collect broad data on microfinance and to include microfinance in financial landscapes. Historically financial institutions have reported to their national networks and in the case of formal institutions, to their central bank or another supervisory authority. Global data are collected on the basis of national data, of selfselected reporting by individual institutions and, more recently, of global surveys. This chapter presents nine major data sets, some of which are available to the public for analysis. They fall into three categories: 1) Self-selected reporting by individual institutions: Microfinance Information exchange (MIX), an affiliate of CGAP, and the Microcredit Summit Campaign 2) reporting by global networks: savings and postal banks, credit unions and cooperative banks, and village savings and loan associations 3) global surveys: the Financial Access Survey (FAS) of the IMF, the World Bank s Global Financial Inclusion survey (Global Findex), the Bill & Melinda Gates Foundation s Geospatial Mapping of Access, and the IFC s study of access to finance for formal and informal MSMEs. The data sets vary widely in terms of completeness. This is obvious in the case of selfselected reporting, but pertains also to national and global networks as well as to the IMF- FAS. Not only small and recently established institutions refrain from reporting, but also wellestablished institutions and national banks. In a spectacular case this has led to the discontinuation of data collection by the FAO from 75 agricultural development banks, which are major providers of rural microfinance, but reluctant to report; the latest presentation of the data set and analysis covers data up to around , after which data collection stopped (Seibel, Giehler and Karduck, 2005: 17-31, 58-59). There is no data sub-set on inclusive rural and agricultural finance, though one could probably be constructed from existing data sets banks reported data on accounts, totaling 24 million loan accounts and 87 million deposit accounts. 1

2 Self-reporting by individual institutions Microfinance Information Exchange (MIX) 2. All microfinance reporting systems, at least the earlier ones, are biased one way or the other; MIX is perhaps the one with the highest reputation. It basically comprises self-identified MFIs, its main implicit selection criterion being a high standard of reporting quality including certified audits of outreach, cost and financial performance. Many MIVs and donors supporting MFIs request them to report to the MIX; MFIs without such a backing may not be able or willing to annually submit to that standard. This has resulted in a reported non-random sample of 1,334 MFIs of banks, financial cooperatives, non-profits and others (out of about 2,000 which have reported to MIX), with total assets of $ billion, or $86.8 million per MFI on average (2011 data) (Table 1). Table 1: MIX microfinance data by region, 2011 Av. ROA*) Billion US$ Millions Av. MFI (mn US$) Region MFIs Wt Unwt Assets Deposits Loans Borr s Dep s Loans Deposits Africa E. Asia + Pacific E. Eur. + C.. Asia Latin America M. East + N. Afr South Asia Total 1, *) Wt = weighted by assets, Unwt = unweighted Source: By comparison, the Indonesian sample of MIX for 2011 comprises 75 MFIs; this includes 36 rural banks (BPR, regulated by the central bank) out of a total of 1669 (with total assets of $6.2 billion, loans outstanding of $4.5 billion, deposits of $4.2 billion, ROA = 3.3%, ROE = 29.5% as reported by Bank Indonesia), their number alone exceeding the total number of MFIs in the MIX. The sample also includes 15 village banks on Bali (LPD, under provincial legislation, with data up to 2007 after which GIZ closed its support project in Indonesia) out of a total of 1418 LPD. Out of some 40,000-odd financial cooperatives (many nonperforming) only 3 are included. The sample does include BRI s network of 5,000 microbanking units (loan portfolio of $9.9 billion). In Laos, with an emerging microfinance sector, the sample for 2011 comprises 20 out of a total of 42 licensed MFI, many of them new; understandingly, it includes none of the 4,500 village banks which are registered with local authorities, but not licensed by the central bank. It does include ACLEDA (a bank newly established from 2 2

3 Cambodia, with a loan portfolio of $35.8 million, accounting for 83% of the total portfolio reported for Laos), but not Nayoby Bank, the state s policy bank for the poor, in contrast to Vietnam which does include VBSP. In a number of countries data is heavily skewed by the preponderance of a single large institution (like BRI in Indonesia and VBSP in Vietnam), and generally by an absence of data from homegrown smaller institutions. Along the same line, Javoy and Rozas (2013: 18) noted similar discrepancies, comparing Global Findex and MIX data. Thailand for instance, which has a high penetration rate (on Findex), has no microfinance activity reported to the MIX ; both Thailand and Laos have large homegrown lending programs to the poor and minimal participation from the international microfinance ecosystem. Despite the data bank s limitations it is widely used in econometric dissertations on microfinance and treated as representative of the microfinance sector. Nevertheless, the MIX is an important and reliable source of information on a variety of licensed institutions, but requires some knowledge of the selection of these institutions before valid conclusions can be drawn. MIX also provides a wider set of sectoral data on countries which permit detailed analyses. On sub-saharan Africa MIX has established a dataset Mapping Africa Financial Inclusion with maps and country data as well as raw data for download. 3 The data set covers 23,000 institutions in 45 countries across sub-saharan Africa including commercial, savings and postal banks, regulated MFIs, mostly unregulated financial cooperatives (reported by WOCCU) and informal savings and credit groups (reported by the Savings Group Information Exchange); in that region it has much broader coverage than the IMF s FAS 4. According to this data set total outreach is 71 million accounts, including 20 million loan accounts, mostly from banks and regulated MFIs, and 44 million savings accounts: 18 million from financial cooperatives and 4 to 6 million each from savings, commercial and postal savings banks, regulated MFIs and savings groups. (Figure 1) Mobile banking, concentrated in a few flagship markets, reaches more than 18 million. Vast numbers of informal providers outside reporting networks are not included. Figure 1: Financial access by data source for sub-saharan Africa Correlation coefficients of MIX-FAS in sub-saharan Africa for 2010 were 0.22 for number of providers, 0.50 for loans per 1000 adults and 0.25 for deposits per 1000 adults. 3

4 Source: also in Ardic et al. 2012: 14 The Microcredit Summit Campaign ( is an American non-profit organized by RESULTS, a public relations and advocacy firm, and RESULTS Educational Fund, focused on ending poverty ( Since 1997 annual Microcredit Summits are held around the world, attended by thousands of practitioners and others. The Campaign aims at (1) reaching 175 million poorest families with microcredit for selfemployment and other services by 2013 and (2) helping 100 million families lift themselves out of extreme poverty, rising above the $1.25 income a day threshold (adjusted for purchasing power parity) between 1990 and The results, published in Microcredit Summit Campaign Reports, are based on self-reported action plans of a wide variety of MFIs and other institutions, including banks and international organizations. 6 The Campaign reports that during ,652 microfinance institutions (reporting to the Campaign) had reached million clients million were among the poorest when they took their first loan; 39.5% were reported by NABARD SHG-Bank linkage program. 7 The data is available for public use. 8 Figure 2: Access of the poorest to finance compared to World Bank data by region, The Economist (June 1 st 2013: 11, 21-24) reports that between 1990 and 2010 the number of people living in extreme poverty fell by almost 1 billion. Two-thirds of that reduction is attributed to economic growth, one-third to income distribution. In some countries conditional cash transfer schemes played a role. 6 Among them is NABARD in India, in charge of supervising and refinancing rural financial institutions, without retail services of its own. In 2012 it reported to the Campaign 67.9 million clients, including 54.3 million poorest, 54.3 million women and 43.5 million poorest women. These are members of self-help groups in NABARD s bank-shg linkage program, initially developed under a regional program of GTZ and APRACA and closely monitored.. Beyond such special cases, it is surprising that all reporting institutions including banks provide data on the number of women and the poorest as requested, even though banks do not normally distinguish between accounts of men and women, poorest, poor and nonpoor. 7 The reported numbers declined in 2011 to 195 million and 124 million, respectively. The drop is attributed to the microfinance crisis in Andhra Pradesh, India. (State of the Microcredit Summit Campaign Report 2012 and 2013)

5 Of the reporting institutions, 27% are in sub-saharan Africa, 48% in Asia and the Pacific and 18% in Latin America and the Caribbean. In Asia and the Pacific the number of poorest identified by institutions reporting to the Campaign accounts for 64.2% of the number of poorest in the World Bank s World Development Indicators (2010) dataset. In Africa, with the second-largest number of poorest, coverage, at 9.8%, is negligible. Reporting cumulative outreach data is a misleading practice. Current numbers submitted to the Campaign in 2011 by 609 MFIs cover 78 million poorest. The Campaign was able to verify data of 328 MFIs, with microloans to 72 million poorest families. 9 These figures are around half the target of 175 million aimed at by The second target, ensuring that 100 million families rise above the extreme poverty threshold between 1990 and 2015, is difficult to verify in the absence of a baseline survey; based on commissioned studies in India and Bangladesh 10, the Microcredit Summit Campaign Report 2012 (p. 4) concludes by extrapolation that the second goal will almost certainly not be reached by Even if it did, the implicit presumption being that the rise above the $1.25 a day threshold is due to microcredit, attribution in a highly complex development situation would be difficult; no evidence is presented; an increasing number of randomized control trials (RCTs) is coming up with no impact, though one may question whether it is realistic to expect impact in months, the usual period under study. Global reporting by networks of financial institutions 9 About 90% of the poorest are served by the 85 largest reporting institutions. 10 In Bangladesh 1.8 million microcredit clients, representing 9.43 million family members, were found to have crossed the $1.25/day poverty line during (Microcredit Summit Campaign Report 2011: 7) 5

6 The World Savings Banks Institute (WSBI) in Brussels reports on savings and postal banks in 88 countries: 33 in Europe, the US, and 57 in developing countries: 30 in Africa, 16 in Asia (Japan is not among them) and 11 in Latin America. This includes national banks as well as networks of independent savings banks reporting aggregated data, such as DSGV in Germany with 600 institutions including 426 retail savings banks, and ICBA in the US with 6,922 independent member community banks. In developing countries large numbers of clients of savings banks are low-income. 11. Information on developing countries is encumbered by very uneven reporting on the various parameters, particularly in Africa. Two outreach indicators are reported: outlets and clients. Of the total number of outlets worldwide (184,315) as of 2011, 42 % (78,273) are in developing countries, the majority in Asia (64,723), followed by Africa (8,399) and Latin America (5,151). Of the total number of clients, which comprises individuals and corporate entities (751 million), 62% (468 million) are in developing countries, again most of them in Asia (363 million), followed by Latin America (89 million) and Africa (25 million). Total assets worldwide as of 2011 amount to US$16.8 trillion, 21% ($3.6 trillion) in developing countries, most of that in Asia ($3.2 trillion), followed by Latin America ($368 billion) and Africa ($42 billion). Data on loans and deposits are divided by WSBI into interbank transactions and non-bank financial intermediation with clients. The following data pertain only to the latter, ie, retail banking. Total loans outstanding amount to $9.5 trillion, 23% ($2.2 trillion) of that amount in developing countries: $1.2 trillion in Asia, $0.9 trillion in Latin America and only $7 billion in Africa. Total deposits are $8.2 trillion, 27% of that amount ($2.2 trillion) in developing countries: $2.0 trillion in Asia, $192 billion in Latin America and $28 billion in Africa. In Europe loans outstanding exceed deposits, with a deposit-to-loan ratio (DLR) of In developing countries loans and deposits are balanced overall, with a DLR of 1.01, but there are marked differences between continents: The institutions in Latin America are credit-led, lending almost five times the amount of deposits. In contrast, in Asia deposits exceed loans outstanding by a factor of 1.6, and in Africa by a factor of 4.0, evidently financing the state with savings mobilized rather than individuals and MSMEs. 11 In a special study of savings banks in India, Mexico, Tanzania and Thailand, WSBI (2008) found that they are large providers of financial services, with significant outreach among the poorest households. Cf. 6

7 Table 2: WSBI retail savings bank data, 2011 (clients in millions, amounts in billion US$) Outlets Clients Assets (interbank + retail) loans deposits Retail Retail Region DLR Europe 75, ,650 5,848 4, Germany: 20, ,572 1,708 1, USA (ICBA + Wells Fargo) 30, ,514 1,500 1, Africa 8, Asia 64, ,192 1,242 1, Latin America 5, Total developing countries 78, ,602 2,177 2, Global total 184, ,766 9,526 8, In percent: Europe 41% 28% 64% 61% 61% USA 16% 9% 15% 16% 12% Africa 5% 2% 0% 0% 0% Asia 35% 48% 19% 13% 24% Latin America 3% 12% 2% 10% 2% Total developing countries 42% 62% 21% 23% 27% Global total 100% 100% 100% 100% 100% Notes: Data existing for 2010 are inserted where none are reported for *) Data of Independent Community Bankers of America (ICBA) member institutions are taken from 6,922 banks, 24,000 outlets, $750 billion in loans and $1 trillion in deposits; there is no information on clients. The World Council of Cooperative Unions (WOCCU) and the European Association of Cooperative Banks (EACB) report on cooperative financial institutions. Terminology is not unified: there are credit unions, savings and credit cooperatives, financial cooperatives and cooperative banks, and tiered systems of cooperatives; definitions overlap. Rural and urban credit cooperatives, predominantly of microentrepreneurs and small farmers, tend to go back to origins in Germany, with an equal emphasis on savings and credit. Credit unions tend to be of Anglo-Saxon origins, with an emphasis on saving for the rainy day, initially among factory workers. While there are remnants of these origins (such as the prevalence of company-based credit unions in the US), distinctions are not systematically maintained. Cooperative banks are usually a category apart, but may also be subsumed under financial cooperatives, as Birchall (2013a) does. In terms of reporting there are two main worlds of cooperative finance: credit unions on which WOCCU reports and cooperative banks in Europe on which EACB reports. Credit unions serve only members, while the banks may serve members and nonmembers. In addition there are two non-reporting worlds of cooperative finance: credit unions and cooperative banks which do not belong, or report, to any of these two networks; and independent local 7

8 cooperatives, informal cooperatives including indigenous ROSCAs, semiformal pre-cooperatives and other member-owned financial institutions. This section is limited to reporting institutions; that means that actual numbers exceed those reported by a wide margin. Indonesia for example contributes 930 credit unions with 1.8 million members to the WOCCU figures (2010); official figures of savings and credit cooperatives (including credit unions), most of doubtful standing, exceed 40,000, with 11 million members (2000) (ADB 2003). India contributes1,645 credit unions with 20 million members to the WOCCU data; Nabard reports 95,000 primary agricultural credit cooperatives with 126 million members as of 2010, which are not included in the WOCCU data (Seibel 2012). China, with vast numbers of credit cooperatives, is also not included. We may conclude that the number of registered non-credit union financial cooperatives exceeds that of credit unions. Table 3: Financial cooperatives: credit unions (2011) and European cooperative banks (2010) Credit Unions Number 51,013 (100 countries) European Cooperative Banks 3,874 banks (20 countries) Members million 50 million Assets US$ Deposits billion US$ Loans billion US$ Source: Birchall 2013a: 13 billion billion billion billion WOCCU reports on 51,000 credit unions in 100 countries 12, with a total membership of almost 200 million and total assets of $1.56 trillion. EACB reports on almost 3,900 local cooperative banks in 20 European countries, belonging to 24 national networks each topped by an apex bank, with 181 million customers including 50 million members, total assets of 5.65 trillion (roughly $7.5 trillion), and a market share of 21% of deposits and 19% of loans. Credit unions globally have a market penetration (not share!) of 7.8% as reported by WOCCU, defined as the ratio of the number of members to the total economically active population between 18 and 64 years of age; the penetration rate might be around three times higher if calculated on the basis of the population represented by cooperative members. Credit unions are reported for 14 developed countries (USA, Canada and 12 European countries), numbering about some 11,000 credit unions with almost 105 million members. In most Eastern and Central European countries financial cooperatives took a fresh start after the dissolution of the Soviet Union, and coverage is still low. The average size of a credit union in terms of membership is 12,804 in North America and 3,502 in Europe. The US is the global market leader, with 7,351 credit unions, 94 million members and a market penetration of 45%. 8

9 Credit unions are reported in 86 developing countries, with approximately 40,500 societies and 84 million members. Asia has almost 20,000 credit unions with 40 million members; Africa has more than 18,000 credit unions with 18 million members; Latin America has only 1,750 credit unions, but about the same number of members as Africa. Market penetration is highest in Oceania (23.6%) and the Caribbean (17.5%), much lower in Africa (7.2%) and Latin America (5.7%), and lowest in Asia (2.7%). Average credit union size is lowest in Africa (985 members) and Asia (2006), medium in the Caribbean (6,804) and Latin America (10,335) and largest in Oceania (15,706). Table 4: Credit unions by market penetration of region Region Countries Market pene- Credit Members tration in % unions (in millions) North America Oceania Caribbean Africa Latin America Europe Asia World Developing countries Developed countries 14 10, Source: Adapted from Birchall 2013a: 17, Birchall 2013b: 46 based on data by WOCCU How did financial cooperatives perform before and after the global crisis? Studies and the existing datasets give some information about cooperative banks in Europe and about credit unions globally. Studies comparing cooperative and investor-owned banks in Europe before the crisis, , found better loan quality, higher cost efficiency, higher returns on equity and markedly higher stability among cooperative banks; assets increased by 23%. They went into the crisis with a strong capital base which they subsequently strengthened. With limited exposure to sub-prime mortgages and fewer investment activities, losses were lower than those of investor-owned banks. After the crisis they continued to be stable and more efficient; lower write-downs and losses were lower than those of investor-owned banks, though some of their centrals took a beating was a difficult year, but overall, between 2007 and 2010, assets grew by nearly 10%, customers by 14%. In general, cooperative banks in Europe have survived the crisis very well. Seven of them are in the top 50 safest banks in the world. At an average of about 9% across Europe, they exceed the minimum capital requirement set at 8%. (Birchall 2013a: 19-28) 9

10 Similarly, growth and resilience have been observed among WOCCU credit unions before and after the crisis. During the two-year period , savings increased by 29%, loans by 39%, reserves by 26%, assets by 32%, membership by 13%; market penetration grew from 6.65% to 7.5%. The global picture from 2007 to 2010 has been one of strong growth. Again, 2008 was a difficult year; but over the three-year period savings increased by 24%, loans by 13%, reserves by 14%. The most impressive growth rates of savings and loans were found in the Caribbean, at 50% and 57%, respectively, and in Oceania, both at 49%. In Latin America savings grew by 48%,while loans experienced a slight decrease. In sub-saharan Africa savings grew by 34%, and loans by 37%. (Birchall 2013a: 22-23, 28-32) Figure 3: Credit unions, during and after the crisis (World totals in million US$) Source: Birchall 2013a: 28 Birchall (2013a: 32, 53) concludes that financial cooperatives are not just weathering the financial downturn but taking a lot of business from the investor-owned banks There must be something about the customer-owned business model that makes it so resilient in a downturn. The main explanatory factor is that financial cooperatives are not just about financial deepening. Like other types of cooperatives, they are people-centered businesses, owned by the people they serve. The Savings Groups Information Exchange (SAVIX) reports on self-help groups organized as village savings and loan associations (VSLAs) which are members of national VSLA networks. (Table 5) SAVIX also tracks the long-term performance of a randomized sample of 332 independent savings groups established by 33 projects in Asia and Africa. SAVIX is supported by the Bill & Melinda Gates Foundation. 13 Table 5: VSLA member outreach (Feb. 2013) Region Countries Members Percent 10

11 Asia , Latin America , Africa 38 6,230, Total members 63 6,942, Source: Allen Hugh on behalf of 27 Feb 2013 Note: The data set includes information on outreach by country and promoting agency. Global data sets In its June 2004 meeting the Group of Eight (G-8) endorsed CGAP s Key Principles of Microfinance, which were formulated in the context of CGAP s newly declared inclusive financial systems approach. Referring explicitly to the integration of microfinance into formal financial systems to ensure permanent access to financial services by significant numbers of poor people (CGAP 2004: viii n. 2), this shifted attention from predominantly unregulated providers of microcredit and microfinance to the formal financial sector as the ultimate provider. At the Pittsburgh Summit in 2009, the G-20 leaders made a commitment of improving access to financial services for the poor, building on the example of micro finance [to] scale up the successful models of small and medium-sized enterprise (SME) financing [and] to launch a G-20 SME Finance Challenge, together with CGAP, IFC and others. 14 This commitment to financial inclusion was reiterated at every subsequent meeting. At their 2010 meeting, the Global Partnership for Financial Inclusion (GPFI) was established to institutionalize and implement the G-20 Financial Action Plan. One of its three subgroups was tasked with identifying the existing financial inclusion data landscape, assessing data gaps, and developing key performance indicators, presented by Ardic, Chen and Latortue (2012: 1) in a study on behalf of CGAP and IFC. They report that: Interest in financial inclusion is at an all-time high. Policy makers and standard-setters, ranging from local central banks to global standard-setting bodies, increasingly view stability and inclusion as complementary, mutually reinforcing goals. They confirm access to formal finance as the objective of inclusion: Financial inclusion refers to a state in which all working-age adults have effective access to credit, savings, payments, and insurance from formal service providers. (Ardic et al. 2012: 3) Measurement is to be guided by a set of seven principles: (1) Build Country-Level Data Capacity, (2) Use Harmonized Definitions and Standardized Methodologies, (3) Proactively Seek Data from a Range of Providers, Beyond Commercial Banks, (4) Use Unique Financial Identity of Users More Systematically, (5) Collect More Detailed Data on Customer Segments,(6) Include More Firm Data, Especially That of MSMEs, (7) Promote Open Access to Data. (Ardic et al.: 16-18) 11

12 Financial inclusion is at the center of two global data sets: (a) the Financial Access Survey (FAS) data base of the IMF, with time series of basic access and usage indicators collected from regulators; (b) the World Bank s Global Financial Inclusion (Global Findex) data base covering over 150,000 people in 148 economies. In this context, the Alliance for Financial Inclusion (AFI) was founded in 2008 with support from the Bill & Melinda Gates Foundation, with the objective of developing policy measures to provide millions of people in developing countries with access to bank accounts and financial services. AFI is a global knowledge sharing network for financial inclusion policymakers, comprising at present more than 100 institutions (mostly central banks) from 87 developing countries ( ; cf. AFI 2013). The IMF s Financial Access Survey (FAS) is the sole global supply-side source of comparable geographic and demographic data on access to and usage of basic consumer financial services by households and enterprises across the world. Launched in October 2009, the results of its fourth annual survey among regulators worldwide went online for public use in September 2012 (available at FAS comprises annual data and metadata on 187 economies, reported by regulated financial institutions to their respective financial authority. 15 The dataset as of mid-2013 covers an eight-year time span, The enhanced 2012 survey, conducted in collaboration with CGAP and IFC, added time series on access indicators from financial cooperatives and MFIs and includes data on SMEs, households, life insurance and non-life insurance. FAS data show a positive trend in financial inclusion since 2005, indicated by increasing numbers of deposit and loan accounts in commercial banks, though with very little growth in 2009 and 2010 due to the global financial crisis, which impacted borrowing slightly more than saving. Ardic et al. (2013:6) note that, in addition to commercial banks, nonbank financial institutions (NBFIs) contribute significantly to reach unserved and underserved clients in many markets. Indeed, deposit-taking NBFIs are playing a more important role in deposit and loan penetration, and NBFI loan penetration increased relative to that of commercial banks everywhere in the (developing) world. At the same time, NBFIs are transforming into commercial banks, and local commercial banks are showing new interest in reaching the base of the pyramid. (Ardic et al. 2013: 5) Overall, the financial landscape has become more complex, and regulators are making efforts to also cover NBFIs in their reporting (Latortue and Ardic, 2013). The World Bank s Global Financial Inclusion survey (Global Findex) is a nationally representative poll covering over 150,000 people in 148 economies, carried out in 2011 by the Gallup Organization and funded by the Bill & Melinda Gates Foundation. It measures how women and men save, borrow, make payments, and manage risks, using regulated, 12

13 unregulated and informal institutions. It also includes information on the percentage of adults with an account at, and at least one loan outstanding from, a regulated financial institution two of the G-20 basic financial inclusion indicators (endorsed in June 2012). It went online in 2012 and is a widely used demand-side source of data. 16 Its headline result is that half the world is unbanked, about 2.5 billion adults. The gaps in account penetration are considerable: 89% of adults in high-income economies have an account at a formal financial institution, compared to 41% in developing economies (37% of women and 46% of men) and 23% among those living on less than $2 per day. As shown in Figure 4, 82% of adults in the Middle East and North Africa and 76% in sub-saharan Africa lack a formal account, compared to 11% in high-income economies. The share of the unbanked is 67% in South Asia, 61% in Latin America and the Caribbean, 55% in Eastern Europe and Central Asia and 45% in East Asia and the Pacific. Figure 4: Global Findex: Adults (age 15+) without a formal account Source: CGAP 2013: 17 (derived from Demirguc-Kunt and Klapper 2012:12) The percentage of the population (age 15+) with an account, the converse of Figure 4, is given in Table 6, together with the percentage of the population with a loan at a formal institution, ranging from 5% in sub-saharan Africa and the MENA region to 8.6% in East Asia and the Pacific. The table also includes a breakdown by low to high income country group and data on accounts and loans of formal SMEs (see below). Table 6: Access to formal financial institutions (in %) *) % of population age 15+ % formal SMEs (5-99 employees) 13

14 Account Loan Account Loan World High-income OECD East Asia & Pacific Eastern Europe & Central Asia Latin America & Caribbean Middle East & North Africa South Asia Sub-Saharan Africa Income groups: Low Lower middle Upper middle High *) Population data: Global Findex, 148 economies, 2011; SME data: World Bank enterprise surveys, 128 economies, 2011 or latest available The study confirms that in developing economies large numbers of people save and borrow informally, using the services of rotating and non-rotating savings and credit associations 17, community-based institutions, friends and family, rather than commercial banks. Globally 9% of adults reported having taken a loan from a formal financial institution in the previous 12 months: 8% in developing economies and 14% in high-income economies. In developing economies 25% borrowed from friends and family in the previous 12 months as the most common source of new loans, compared to 8% who borrowed from a formal financial institution. 48% of respondents in sub-saharan Africa saved at a community-based savings club or with a person outside the family, compared to 35% who reported saving at a formal financial institution. Mobile money transfer is evolving, using mobile phones to make deposits, pay bills or conduct other transactions. This technology accounts for 5% of money transfers globally, but for 16% in sub-saharan Africa where poor infrastructure hampers access to conventional banking institutions. Worldwide 12 economies have mobile money penetration rates above 20%, ten of them are in Africa. (Demirguc-Kunt & Klapper 2012) Geospatial mapping of access: The Bill & Melinda Gates Foundation has developed an interactive geospatial tool for financial inclusion analysis, which brings access data down from the country level to the lowest local proximity level. Its preferred measure is the percentage of poor people within five kilometers of financial access points such as banks, ATMs, MFIs, SACCOs, post offices, mobile money agents and others. By integrating supplyside data of financial service providers into a Financial Services for the Poor (FSP) web map ( the tool presents a geospatially accurate visual representation of the landscape of financial access points for countries in Africa ( and South Asia ( 18 The interactive platform enables those working to expand financial inclusion to visualize and analyze access; 19 at the same time it allows users to add their own 14

15 access points to the data base and to exchange information with each other. (Broens Nielsen and Slind, 2013) Access to finance for SMEs in developing countries has been one of the major concerns of the G-20. Given the importance of SMEs to economic growth and employment creation, the Global Partnership for Financial Inclusion (GPFI) has focused on SMEs as one of its four priority topics was the first year that the IMF included data on SME lending in its Financial Access Survey, contributed by 37 out of 187 countries. In low-income countries only a small share of loan accounts at commercial banks are held by SMEs. SME lending as a percentage of GDP varies from a low near 0% in Kenya, Zambia and Madagascar to 7% in India, 10% in Bangladesh, 15% in China and 18% in Malaysia and El Salvador to highs of 33% in Thailand and 39% in Korea. The IFC recently conducted a study on access to finance for formal and informal MSMEs 20 in developed and developing economies, based on data from enterprise surveys of the World Bank. Reportedly there are some million formal SMEs in developing economies. The large majority of SMEs (with 5-99 employees) have an account at a formal financial institutions (80% and above), except in the Middle East and North Africa (36%); the percentage of SMEs with a loan ranges from 6% in the MENA region to 46% in Latin America and the Caribbean. The percentage of SMEs with an account varies from 84% in low-income countries to 92% and 91% in upper-middle and high-income countries, respectively, and the percentage of SMEs with a loan from 20.5% to 50%. (Table 6 above). The credit gap is around $1 trillion; it is greatest in the MENA region and in sub-saharan Africa. The database will be publicly available on References ADB Asian Development Bank, Rural Microfinance Indonesia (TA No INO), Annex 4. Manila, ADB AFI Alliance for Financial Inclusion, Measuring Financial Inclusion: Core Set of Financial Indicators. Bangkok, AFI, Ardic, Oya Pinar, Gregory Chen and Alexia Latortue, Financial Access 2011: An Overview of the Supply-Side Data Landscape. Washington DC, CGAP and IFC Ardic, Oya Pinar, Kathryn Imboden and Alexia Latortue, Financial Access 2012: Getting to a More Comprehensive Picture. Washington DC, CGAP and IFC, Birchall, Johnston, 2013a. Resilience in a downturn: The power of financial cooperatives. Geneva, ILO, 2013b. Finance in an Age of Austerity: The Power of Customer-owned Banks. Cheltenham, Edward Elgar 15

16 Broens Nielsen, Karina, and Todd Slind, The Power of Mapping Financial Services Data. Seattle WA, Bill & Melinda Gates Foundation CGAP Consultative Group to Assist the Poor, Building Inclusive Financial Systems: Donor Guidelines on Good Practice in Microfinance. Washington DC, CGAP, Strategic Directions FY 2014 FY 2018: Advancing Financial Inclusion to Improve the Lives of the Poor. Washington DC, CGAP Demirguc-Kunt, A., and L. Klapper Measuring Financial Inclusion: The Global Findex Database. Policy Research Working Paper World Bank, Washington DC Javoy, Emmanuelle, and Daniel Rozas, MIMOSA: Microfinance Index of Market Outreach and Saturation, Part 1 Total Credit Market Capacity. Paris, Planet Rating, Fondation PlaNet Finance Latortue, Alexia, and Oya Pinar Ardic, Financial Inclusion: Blurred Lines, Sharper Vision July 2013 Microcredit Summit Campaign Report, State of the Microcredit Summit Campaign Report 2011 (by Larry R. Reed). Washington DC, Microcredit Summit Campaign (MCS), State of the Microcredit Summit Campaign Report 2012 (by Larry Reed and Jan Maes). Washington DC, Microcredit Summit Campaign (MCS) Seibel, Hans Dieter, An approach towards self-reliance and sustainability of the SHG sector in India: SHG Sector Own Control. The microfinance Review (Lucknow), IV, 1 Seibel, Hans Dieter, Thorsten Giehler and Stefan Karduck, 2005, Reforming Agricultural Development Banks, Eschborn, GIZ, Agricultural-Banks.pdf WSBI World Savings Banks Institute, Who are the Clients of Savings Banks? A Poverty Assessment of the Clients Reached by Savings Banks in India, Mexico, Tanzania and Thailand. Brussels, WSBI 16