FINANCE & MARKETS GLOBAL PRACTICE Enhancing Financial Capability and Inclusion in Zambia A Demand-side Assessment ZAMBIA, November 2017 ii © 2017 International Bank for Reconstruction and Development / The World Bank Group 1818 H Street NW Washington DC 20433 Telephone: 202-473-1000 Internet: www.worldbank.org This work is a product of the staff of The World Bank with external contributions. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive Directors, or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. Rights and Permissions The material in this work is subject to copyright. Because The World Bank encourages dissemination of its knowledge, this work may be reproduced, in whole or in part, for noncommercial purposes as long as full attribution to this work is given. Any queries on rights and licenses, including subsidiary rights, should be addressed to the Office of the Publisher, The World Bank, 1818 H Street NW, Washington, DC 20433, USA; fax: 202-522-2422; e-mail: pubrights@worldbank.org. Cover photos: © Étude Économique Conseil (EEC Canada). Used with the permission of EEC Canada. Further permission required for reuse. Acknowledgements This Financial Capability and Inclusion Survey Report was prepared by a team led by Siegfried Zottel (Senior Financial Sector Specialist) 1 from the World Bank Group’s (WBG) Finance & Markets Global Practice and included Clement Jean Edouard Joubert (Economist, DECHD), and Fares Khoury (Economist and President of Étude Économique Conseil, EEC Canada). The Survey Report was produced under the WBG’s Zambia Financial Inclusion Support Framework (FISF) Program led by Uzma Khalil and Siegfried Zottel (Senior Financial Sector Specialists). The team is grateful to the peer reviewers of this report – Vincenzo Di Maro (Senior Economist, DECIE) and Gregory Smith (Senior Economist, GMF13). The team benefited from the valuable inputs provided by Shaun Mundy (Senior Financial Capability Consultant). Research assistance and design inputs provided to the team by Minah Je (Consultant, GFMDR) and Lina Wedefort (Economist, EEC Canada) are also gratefully acknowledged. The team expresses its deepest appreciation to the Zambian authorities, including the Ministry of Finance (MoF), the Bank of Zambia (BoZ), the Pensions and Insurance Authority (PIA), the Security Exchange Commission (SEC), and the Competition and Consumer Protection Commission (CCPC) for their cooperation and collaboration during the preparation and implementation of the survey. In particular, the team wants to extend its sincere gratitude to the following officials and experts who provided invaluable support and strategic guidance throughout the project: Dr. Denny Kalyalya (Governor, BoZ), Mr. Mukuli Chikuba (Permanent Secretary, Budget and Economic Affairs, MoF), Mr. Chisha Mwanakatwe (Senior Director, Supervisory Policy, BoZ), Mr. Martin Libinga (Chief Executive Officer, PIA), Mr. Philipp K. Chitalu (Chief Executive Officer, SEC), Dr. Remmy Kampamba (Assistant Director, Economic Management, MoF), Mr. Musapenda J. Phiri (Head, Financial Sector Development Unit, BoZ), Mrs. Namakau Ntini (Manager, Analysis & Policy, Insurance Supervision, PIA), Mr. Goodson Kapaso (Manager, Analysis & Policy, Pension Supervision, PIA), Ms. Mutumboi Mundia (Director, Market Supervision & Development, SEC), Brian Lingela (Director, Consumer Protection, CCPC), Moses Musantu (Chief Investigator, Consumer Protection, CCPC), and Mr. Michael Mbulo (Program Coordinator, Rural Finance Expansion Program, MoF). The team would also like to express its gratitude to EEC Canada’s core and field team, led by Isabelle Leyder (Deputy Project Director of the survey). We are grateful to Nicolas Megelas, (Country Manager at EEC Canada), as well as all supervisors and enumerators whose efforts and commitments made this project possible. Finally, the team wishes to express sincere appreciation to all Zambian women and men who patiently responded to the survey. 1 The corresponding lead author can be contacted at: szottel@worldbank.org i Contents Acknowledgements..................................................................................................................................... i Abbreviations and Acronyms ....................................................................................................................vii Preface....................................................................................................................................................... 1 Key Findings .............................................................................................................................................. 2 Summary of Key Recommendations ......................................................................................................... 3 Financial Inclusion ............................................................................................................................ 4 Recommendations ........................................................................................................................... 5 Financial Capability and Its Relationship with Financial Inclusion ................................................... 7 Recommendations ........................................................................................................................... 7 Financial Consumer Protection ...................................................................................................... 10 Recommendations ......................................................................................................................... 10 Background on Zambia Survey ............................................................................................................... 12 1. Financial Inclusion .............................................................................................................................. 14 1.1. Introduction .............................................................................................................................. 14 1.2. Headline Measures for Financial Inclusion ............................................................................. 15 1.3. Financial Product Usage ......................................................................................................... 19 1.3.1. Commercial Banks, National Saving and Credit Institutions........................................ 20 1.3.2. Payment Providers ....................................................................................................... 21 1.3.3. Microfinance Institutions............................................................................................... 24 1.3.4. Insurance Companies .................................................................................................. 26 1.3.5. Brokerage Houses or Unit Trusts ................................................................................. 27 1.3.6. Patterns of Formality and Informality in Savings and Credit ........................................ 28 1.4. The Unbanked and Barriers to Owning a Formal Account ..................................................... 31 2. Financial Capability ............................................................................................................................. 32 2.1. Knowledge of Financial Concepts ........................................................................................... 32 2.2. Knowledge of Financial Products ............................................................................................ 39 2.3. Financial Behavior and Attitudes ............................................................................................. 43 3. Relationship Between Financial Inclusion and Financial Capability ................................................... 53 3.1. Financial Literacy and Financial Inclusion .............................................................................. 53 3.2. Knowledge about Financial Products and Financial Inclusion ................................................ 55 3.3. Financial Attitudes/Behavior and Financial Inclusion .............................................................. 57 4. Financial Consumer Protection ........................................................................................................... 59 4.1. Consumers’ Satisfaction with Financial Products ................................................................... 60 4.2. Consumers’ Approaches in Dealing with Provider Conflicts ................................................... 62 References............................................................................................................................................... 67 ii Appendix .................................................................................................................................................. 69 A. Cross-tabulation of Financial Inclusion ...................................................................................... 69 B. Background on Zambian Financial Survey ................................................................................ 71 C. Regression Tables ..................................................................................................................... 74 Figures Figure 1. Evolution of Financial Inclusion 2005 - 2016 ............................................................................ 16 Figure 2. Financial Inclusion by Gender, Urban/Rural, and Income ........................................................ 17 Figure 3. Financial Inclusion by Household Size and Income Stability .................................................... 18 Figure 4. Knowledge and Usage of Banks, National Saving and Credit Institutions by Individual Characteristics........................................................................................................................... 20 Figure 5. Knowledge and Usage of Money Transfer Services by Individual Characteristics................... 21 Figure 6. Knowledge and Usage of E-money Agents by Individual Characteristics ................................ 22 Figure 7. Number of Mobile Money Accounts per 1,000 Adults ............................................................... 23 Figure 8. Consumer Taxes as a Proportion of Total Cost of Mobile Ownership 2014 ............................. 24 Figure 9. Knowledge and Usage of Microfinance Organizations by Individual Characteristics ............... 25 Figure 10. Knowledge and Usage of Microfinance Organizations, Banks, National Saving and Credit Institutions by Individual Characteristics ................................................................................... 25 Figure 11. MFI and Bank Usage ................................................................................................................ 26 Figure 12. Knowledge and Usage of Insurance Companies by Individual Characteristics ........................ 27 Figure 13. Formal and Informal Savings .................................................................................................... 28 Figure 14. Formal and Informal Credit ....................................................................................................... 29 Figure 15. Reasons for Not having a Formal Account (% of Unbanked Zambians Without an Account) .. 31 Figure 16. Financial Literacy Distribution ................................................................................................... 34 Figure 17. Financial Literacy Quiz Overview .............................................................................................. 34 Figure 18. Low (0 to 2), Medium (3 to 4) or High (5 to 7) Financial Literacy Scores by Income and Education Level ......................................................................................................................... 35 Figure 19. Awareness on Financial Concepts and Products ..................................................................... 37 Figure 20. Reported vs. Actual Financial Literacy ...................................................................................... 37 Figure 21. Characteristics of Indebted Zambian Households .................................................................... 38 Figure 22. Distribution of Financial Product Awareness Scores ................................................................ 39 Figure 23. Overview of Financial Product Awareness by Financial Institutions ......................................... 40 iii Figure 24. Fraction of Zambians who Know About Financial Products of Different Providers by Urban/Rural and Income ........................................................................................................... 40 Figure 25. Fraction of Zambians who Know About Financial Products of Different Providers by Urban/Rural and Income ........................................................................................................... 41 Figure 26. Media Consumption by Social and Demographic Groups ........................................................ 42 Figure 27. Average Financial Capability Scores ........................................................................................ 44 Figure 28. Correlates of Having Saving Capacity ...................................................................................... 45 Figure 29. Average Financial Capability Scores by Urban/Rural and Income Level ................................. 48 Figure 30. Average Financial Capability Scores by Financial Literacy Level............................................. 49 Figure 31. Average Financial Capability Scores by Media......................................................................... 49 Figure 32. Average Financial Capability Scores by Child Saving Behavior ............................................... 50 Figure 33. Expected Sources of Economic Support in Old Age................................................................. 51 Figure 34. Knowledge about Regulatory Financial Institutions (BoZ) ........................................................ 52 Figure 35. Knowledge about Regulatory Financial Institutions (PIA and SEC) ......................................... 53 Figure 36. Distribution of Financial Literacy Score by Formal/Informal Financial Products and Services Ownership ................................................................................................................................. 54 Figure 37. Distribution of Financial Product Awareness Score by Reasons for not having a Formal Account ..................................................................................................................................... 55 Figure 38. Distribution of Financial Product Awareness Score by Formal/Informal Financial Products and Services Ownership ........................................................................................................... 56 Figure 39. Financial Product Awareness by Financial Inclusion and Services Ownership ........................ 57 Figure 40. Distribution of Financial Attitudes and Behaviors by Financial Inclusion................................... 58 Figure 41. Usage of Financial Products by ‘Running Short of Money’ Behavior ........................................ 58 Figure 42. Clients’ Satisfaction with Services Provided by Common Types of Financial Institutions......... 60 Figure 43. Clients’ Satisfaction with Services Provided by Commercial or Postal Banks .......................... 60 Figure 44. Approaches in Dealing with Financial Services Provider Conflicts ........................................... 63 Figure 45. Overview of Disputes by Social and Demographics Factors ..................................................... 63 Figure 46. Action Taken to Redress Conflicts with Financial Service Providers ........................................ 64 Figure 47. Reasons for Not Solving the Conflicts with Financial Service Providers ................................... 65 Figure 48. Characterization of Zambian Adults Who Did Not Take Any Actions to Solve a Dispute ......... 66 Figure 49. Estimated Population Break-down by Urban/Rural ................................................................... 71 iv Figure 50. Estimated Population Break-down by Province......................................................................... 71 Figure 51. Estimated Population Break-down by Gender........................................................................... 72 Figure 52. Estimated Population Break-down by Age Groups ................................................................... 72 Figure 53. Estimated Population Break-down by Household Size ............................................................. 72 Figure 54. Estimated Population Break-down by Education Groups .......................................................... 73 Figure 55. Estimated Population Break-down by Stable/Unstable Income Groups ................................... 73 Figure 56. Estimated Population Break-down by Different Income Groups ............................................... 73 Tables Table 1. Comparison between Census Key Characteristics and Financial Capability Survey Profile ..... 13 Table 2. Measures of Financial Inclusion and Development across Economies ..................................... 15 Table 3. Poverty Level vs Financial Inclusion Level ................................................................................. 17 Table 4. Measures of Mobile Financial Service Penetration across Economies ...................................... 23 Table 5. Cross-country Comparison of Different Financial Literacy Scores ............................................. 36 Table 6. Main Identified Financial Components from PCA Analysis ........................................................ 43 Table 7. Cross-country Comparison of Different Financial Capability Scores.......................................... 47 Table 8. Financial Inclusion Summary by Social and Demographic Factors ........................................... 69 Table 9. Financial Inclusion by Social and Demographic Factors ............................................................ 74 Table 10. Probability of Having a Bank Account and Having Ever Used Bank/NSCI Products by Social and Demographic Factors .......................................................................................................... 75 Table 11. Probability of Currently Having a Bank Account or Having Ever Used Bank/NSCI Products by Village Factors ....................................................................................................................... 76 Table 12. Probability of Using and Having Ever Used Money Transfer Products by Social and Demographic Factors ................................................................................................................. 78 Table 13. Probability of Using and Having Ever Used E-money Products by Social and Demographic Factors ........................................................................................................................................ 79 Table 14. Probability of Having Ever Used MFI Products by Social and Demographic Factors ................ 80 Table 15. Probability of Having Ever Used and Knowing about Insurance Products by Social and Demographic Factors ................................................................................................................. 81 Table 16. Financial Literacy Score by Social and Demographic Factors ................................................... 83 Table 17. Financial Knowledge Score by Social and Demographic Factors .............................................. 84 Table 18. Financial Literacy Score by Village Factors ................................................................................ 86 v Table 19. Financial Knowledge Score by Village Factors .......................................................................... 88 Table 20. Financial Capabilities by Social and Demographic Factors (I) ................................................... 90 Table 21. Financial Capabilities by Social and Demographic Factors (II) .................................................. 91 Table 22. Probability of Financial Inclusion by Financial Literacy Score, Financial Product Awareness, Social and Demographic Factors................................................................................................ 94 Table 23. Probability of Using Financial Instruments on Financial Capability Scores (I) ........................... 95 Table 24. Probability of Using Financial Instruments on Financial Capability Scores (II) .......................... 97 Table 25. Probability of Encountering a Financial Conflict by Social and Demographic Factors ............... 99 Boxes Box 1. Financial Literacy Quiz .................................................................................................................... 33 Box 2. Debt Level and Financial Knowledge .............................................................................................. 38 Box 3. Media Consumption Overview ......................................................................................................... 42 Box 4. Topics Associated with each Component or Dimension (I) ............................................................. 46 Box 5. Topics Associated with each Component or Dimension (II) ............................................................ 47 Box 6. Planning for Old Age and Financial Literacy ................................................................................... 51 Box 7. Knowledge about Regulatory Financial Institutions (I) .................................................................... 52 Box 8. Knowledge about Regulatory Financial Institutions (II) ................................................................... 53 Box 9. ‘Running Short of Money’ Behavior and Financial Inclusion ........................................................... 58 Maps Map 1. Financial Inclusion by Province (%) vs Regional Poverty Level (I)................................................. 18 Map 2. Financial Inclusion by Province (%) vs Regional Poverty Level (II)................................................ 19 Map 3. Spatial Distribution of Formal Borrowing (% of Adults with Formal Credit) .................................... 29 Map 4. Spatial Distribution of Informal Borrowing (% of Adults with Informal Credit) ................................. 30 Map 5. Historical Usage of Banks, National Saving and Credit Institutions by Region (%) ....................... 61 Map 6. Clients’ Satisfaction with Banks, National Savings or Credit Institutions by Province (%) ............. 62 Map 7. Regional Overview of Disputes with Financial Providers (%) ......................................................... 64 vi Abbreviations and Acronyms AML/CFT Anti-Money Laundering/Combating the Financing of Terrorism ATM Automated Teller Machine BoZ Bank of Zambia CAPI Computer-assisted Personal Interview EA Enumeration Area EEC Étude Économique Conseil FCPD Financial Consumer Protection Department FSDP Financial Sector Development Plan GSMA GSM Association IFAS Inclusive Finance Advocacy Staff KYC Know Your Customer MFI Microfinance Institution MFS Mobile Financial Services MTO Money Transfer Operator NSCI National Saving and Credit Institution NSFE National Strategy on Financial Education PCA Principal Component Analysis PIA Pension and Insurance Authority PPS Probability Proportional to Size PSU Probability Sampling Unit SEC Securities and Exchange Commission WBG The World Bank Group vii Preface Financial capability, as defined by the World Bank Group (WBG) and in this report, is the capacity to act in one’s best financial interest, given socioeconomic and environmental conditions. It encompasses knowledge (literacy), attitudes, skills and behavior of consumers with respect to understanding, selecting, and using financial services that fit their needs (World Bank 2013d). Financial capability has become a priority for policy makers seeking to promote beneficial financial inclusion and to ensure financial stability and functioning financial markets. Today people are required to take increasing responsibility for managing a variety of risks over their life cycle. Those who make sound financial decisions and who effectively interact with financial services providers are more likely to achieve their financial goals, hedge against financial and economic risks, improve their household’s welfare, and support economic growth. Boosting financial capability has therefore emerged as a policy objective that complements governments’ financial inclusion and consumer protection agendas. To this end, policy makers are increasingly using surveys as diagnostic tools to identify financial capability areas that need improvement and vulnerable segments of the population that could be targeted with specific interventions. The Zambian authorities have implemented the Financial Sector Development Plan (FSDP) (phase I and II) to seek a stable and market-based financial sector that supports the “efficient mobilization and allocation of resources necessary for economic diversification, sustainable growth and poverty reduction”. 2 As part of this plan, financial inclusion, financial capability and consumer protection (FCCP) are important priorities for the Zambian government. FCCP are critical elements in building a trusted formal inclusive financial system and the Zambian authorities are seeking to identify sustainable methods of delivering financial education through effective partnerships. As the Zambian government’s financial inclusion initiatives allow more Zambians to access a wider range of financial services from a variety of formal financial institutions, the population will need to acquire knowledge and develop skills in order to make better financial decisions. In response to a request from the Bank of Zambia (BoZ), the World Bank has implemented a financial capability survey. This survey constitutes a key diagnostic tool that aims to guide the authorities in developing a detailed implementation action plan for the National Strategy on Financial Education for Zambia (NSFE). 3 Moreover, it will help the authorities set quantifiable and concrete targets, and assess the effectiveness of future financial capability enhancing programs. The key findings and recommendations presented in this report cover three main areas: 1. Financial Inclusion, 2. Financial Capability, and 3. Financial Consumer Protection. The remaining chapters are structured as follows. Chapter 1 explores the financial inclusion landscape in Zambia. Chapter 2 gives an overview of Zambian levels of financial capability, specifically financial knowledge, attitudes, and behaviors of respondents. Chapter 3 explores the relationship between financial inclusion and financial capability. The last chapter investigates whether the products used by financially included individuals are effectively meeting their needs. 2 BoZ, Progress Report on the implementation of the Financial Sector Development Plan (FSDP) (January 2010 – June 2015). 3 Financial Education Fund, Finmark, BoZ, PIA, SEC, The National Strategy on Financial Education for Zambia, 2012. 1 Key Findings How Financially Included are the Zambians? 53% of high income earners use a formal account compared to 40 29% of low income earners. 46% of Zambian adults living in 40 % of surveyed urban areas use a formal account compared to 36% of their Zambian adults have rural counterparts. PERCENT a formal account in a 29% 53% 36% 46% financial institution. Not enough money, high account fees, long distances to financial institutions and lack of Zambian adults mostly use products from money transfer providers trust were cited as the main reasons for not (53%), banks or national saving and credit institutions (36%), having a formal account. e-money agents (15%) and insurance companies (5%). Banks, National 31% 17% 15% 15% 14% Money Saving and Credit E-money Other Institutions reasons transfer agents Insurance I don’t Cost is It’s too have money too high far away I don’t trust I don’t need it 53 PERCENT 36 15 PERCENT 5 PERCENT them PERCENT How Financially Capable On average, are the Zambians? Respondents scored low in behaviors related to saving capacity, responsibility On average, adults and choosing financial products, but adults were able showed strengths in living within one’s to answer 3.7 out are familiar with 4.1 Financial 3.6/ 9 means, planning for unexpected of 7 financial Knowledge products from 5.8 expenses and controlled budgeting: literacy-related providers. questions 3.7/ 7 Banks, NSCI Living within one’s (87) correctly. Money means 99% transfer Simple 90% E-money Planning for (67) Inflation agents unexpected division 76% Controlled (51) MFIs budgeting 65 Brokerage 91 PERCENT PERCENT 14% houses 9% Planning for old age (46) expenses Self-discipline (44) Respondents are familiar with banks 90% were able to perform simple and NSCIs (99%), money transfer divisions and 65% understand institutions (97%) and E-money Choosing financial (43) inflation. Only 28% were able to agents (76%). Only 9% are familiar products correctly estimate compound interest. with brokerage houses. Responsibility (42) Saving capacity (24) How Financially Protected are the Zambians? Main action taken by adults who tried Financial 13% of respondents to solve a conflict with a provider: providers experienced a conflict with a are too Stopped using service financial service provider in the before 97% I’m not powerful contract expiration aware of past 3 years. Government Only a quarter of them (25%) Submitted claim to government authorities the company which sold 41% agencies I don’t work took action to resolve it. the product can properly approach Approached the courts 13% 13% Approached provider The three main causes for inertia are due to 25% through friends or family 1% lack of familiarity with government agencies that can help (85%), the perception that To redress a dispute, social circles providers are too powerful (64%) and the and courts were barely sought out. lack of trust in authorities (29%). 2 Summary of Key Recommendations Recommendations Responsible Priority Financial Consider policies that encourage provisions for basic financial MoF Medium inclusion services, with transaction accounts at no or low costs, including cooperation with ZamPost, the national postal operator Promote the development and provision of financial services BoZ, MoF, ZICTA High geared towards specific needs of customers, including through providing cheaper avenues for low income consumers to obtain mobile phones Encourage development of MFIs, national credit institutions and MCTI, BoZ Medium other non-bank credit institutions in order to enhance access to formal credit instruments Further develop insurance services, including agricultural and RUFEP, PIA, High micro-insurance Insurance Association Financial Refresh the action plan set out in the National Strategy on BoZ, SEC, PIA Medium capability Financial Education (NSFE) and implement it to address the challenges revealed by this financial capability survey Develop a monitoring and evaluation (M&E) framework to BoZ, SEC, PIA Medium measure progress in implementing the NSFE Design and use a wider range of programs, including mass BoZ, SEC, PIA, Medium media channels, text messages, mobile based delivery channels, Industry etc. to enhance financial knowledge and change attitudes and financial behaviors Combine financial-capability-enhancing programs with available BoZ, SEC, PIA, Medium financial products, which most people can access, to promote FSDZ beneficial participation in the financial market Fully embed appropriate financial education into primary, Ministry of Medium secondary, vocational, and tertiary school curriculum Education, BoZ, SEC, PIA, CCPC Consumer Issue internal complaints handling requirements for FIs to ensure BoZ, SEC, PIA High protection that adequate and fair mechanisms are put in place Create a dedicated section about regulations that BoZ, SEC, PIA Medium ensure/address responsible lending practices, cooling off periods, collection practices, sales practices, and treatment of dormant accounts on the website of the main regulatory institutions Deploy an adequate range of supervisory tools to ensure BoZ, SEC, PIA, High compliance of FIs with consumer protection requirements, CCPC, Industry including but not limited to issuing Key Facts Statements (KFS), other disclosure requirements for core retail financial products, and complaints handling mechanisms Decide on the establishment of an independent alternative BoZ, SEC, PIA, High dispute resolution mechanism such as a financial ombudsman CCPC 3 Executive Summary Financial Inclusion About 40 percent of the surveyed adults in Zambia own an account at a formal financial institution (a bank, a microfinance institution (MFI), or an e-money agent), a commonly used metric for international comparisons. Financial inclusion in Zambia has nearly doubled in the last ten years. During this period, formal financial inclusion has risen steadily from 21.3 percent in 2005 to 40.2 percent in 2016. However, compared to other lower-middle income countries, Zambia fares less favorably on average in terms of financial inclusion, commercial bank branches’ accessibility and domestic credit provided by the financial sector. Across the main socioeconomic and demographic characteristics, income level was found to have the most significant impact on financial inclusion, followed by whether or not adults were located in rural areas and their gender differences. Only 29.4 percent of the lowest income quartile are financially included compared to 52.5 percent of the highest income quartile. Moreover, 35.5 percent of rural people are financially included as opposed to 46.1 percent for urban residents. In terms of gender differences, 37.2 percent of women were found to be financially included compared to 43.1 percent for men. Zambia’s banking sector accounts for over 90 percent of financial system assets. Its strength is matched by high awareness of these institutions. Almost everybody knows about services offered by banks and by national saving and credit institutions. 93 percent of adults currently use, or have in the past used, their services, but only 36 percent currently have an account, which may suggest a low satisfaction among past (but not current) users. Bank usage exhibited the same pattern across the main socioeconomic and demographic characteristics as for financial inclusion more generally. The biggest disparity is a 17-percentage point difference between adults in the highest income quartile and those in the lowest quartile. There is a 6-percentage point difference between urban and rural residents and a 3-percentage point difference between men and women. Nine out of ten adults know about services offered by Money Transfer Operators (MTOs), 76 percent have used their services in the past and 53 percent currently utilize them. Zambia is among the top 10 remittance receivers among Sub-Saharan economies, with remittances representing about 0.3 percent of GDP (USD 0.1 billion). Although 76 percent of adults know about e-money services, only 29 percent have used them in the past and 15 percent continue to utilize them, suggesting a possible lack of trust in this type of service; such services are mostly employed by rich men living in urban areas. 22 percent more rich adults make use of e-money services than the poor, 15 percent more urban people rely on such methods in comparison to their rural peers and 6 percent more men than women utilize such instruments. The usage rate may be associated to the fact that compared to other African countries, Zambia has a low cellular penetration rate (75 percent compared to the regional average of 91 percent) and doesn’t fare well as far as the level of taxes associated to mobile services is concerned, which can be an important barrier to increasing digital inclusion. Very few Zambians utilize insurance products, especially poor and rural adults. Knowledge of insurance products is quite low in Zambia: only 18 percent of adults are familiar with these products. Only 5 percent of the population have purchased an insurance product. About 1 percent of the poorest Zambians currently use insurance, a striking difference with the richest category (8 percent). Moreover, only 2 percent of the rural population is protected by insurance, as opposed to 8 percent for urban people. MFI products are known and used by very few people (4 percent). People utilizing MFI services are predominantly poor rural men. Very few Zambians, especially poor and rural adults, use MFI products. Only 14 percent of adults are familiar with these products and only 4% currently use them. About two-thirds of adults currently have debts, mostly as a result of informal instruments only (82 percent) compared with about 8 percent having taken only formal credits and 18 percent having a mix of formal and informal credits. Most of the informal debt is used by rural residents and the poorest segments of the population. 4 Half of adults have a financial product for saving or save money and most of them are rich and from urban areas. Furthermore, most people report using formal products. Among 50 percent of the adults who save money, 52 percent use only formal products, 28 percent utilize only informal ones and the balance (20 percent) have a combination of formal and informal savings. Propensity to save is predominantly higher first among the rich (29% more than the poor in absolute terms) and secondly among people living in urban areas (19% more than rural in absolute terms). The approximately 3.8 million financially excluded adults – those who use no formal financial products or services – in Zambia are disproportionately female, poor, and living in rural areas. The main reason given by unbanked adults for not owning a formal account is the lack of sufficient funds (31 percent), followed by high account fees (17 percent), institutions being too far away (15 percent) and lack of trust (15 percent). More men than women said that the main barriers were lack of sufficient money and institutions being too far away, with more women than men citing high account fees and lack of trust. Recommendations4 Develop policies that encourage the provision of basic financial services, with transaction accounts at no or low cost, including through cooperation with ZamPost, the national postal operator. 48 percent of unbanked respondents report that high costs are a main barrier to owning formal accounts. This suggests that the costs associated with having these accounts remain considerably high for a significant portion of the population or that the availability of accounts at no or low costs are not widely known. A recent survey5 found that almost all countries that provided information stated that a form of basic account was offered in their jurisdiction. The survey also found that, although a number of countries have introduced or are considering introducing legislation that gives citizens a right to a basic bank account, in the majority of countries the provision of basic accounts is a market initiative. In most of these cases, basic accounts are being offered via banks. In some countries, post offices are also involved in the provision of such basic accounts, suggesting that in Zambia, cooperation with ZamPost on the provision of basic accounts should be expanded. To mitigate the risk that the uptake and usage of basic accounts may be very low, international experience in countries such as India or the Philippines shows that the introduction of basic accounts needs to be complemented with public awareness campaigns about the benefits of accounts. Promote the development and provision of financial services geared toward specific needs of customers, including through providing cheaper avenues for low income consumers to obtain mobile phones. Mobile or agent banking can dramatically reduce the costs of delivering financial services, particularly in low-density and remote areas. Moreover, it can not only reduce explicit costs but also opportunity cost of time lost to traveling and waiting (a survey result that emphasizes the importance of this last advantage is that 15 percent of unbanked adults cited the distance to financial institution as the main reason for their exclusion). The success of mobile financial services (MFS) rests on the vast pool of agents (often small retailers) who connect clients in remote areas to urban centers, allowing them to make transactions. Three out of four adults in Zambia have a mobile phone which indicates that mobile money has a potential usage of 75 percent. To achieve this potential, mobile money regulations should encourage inclusiveness, while minimizing fraud and other risks. Notably, regulations should allow agents outside of bank branches to handle financial transactions and should make provision for risk-based anti-money-laundering and know-your-customer requirements. Given the very low usage of MFIs, national saving and credit institutions and other non-bank credit institutions, there is a strong need to encourage their development in order to enhance access to formal credit instruments. Compared to its African peers, Zambia is lagging in terms of the use of formal credit instruments: 82 percent of Zambian adults use exclusively informal credit instruments while MFI usage is only 4 It should be noted that the recommendations provided in this report arise mainly from this demand-side survey and can therefore not be understood as being exhaustive. 5 Bank for International Settlements and World Bank Group. 2015. Consultative report. “Payment aspects of financial inclusion.” 5 4 percent. The government of Zambia should encourage the strengthening and development of MFIs in the provision of appropriate formal credit instruments which are tailor-made to customers’ needs. Develop insurance services further, including life, property and liability insurance, and specific insurance for rural areas. Insurance is a useful instrument for managing expenses related to unexpected events such as medical emergencies, a death in the family, theft or natural disasters. The insurance sector in Zambia accounts for about 1.4 percent of GDP. 6 With only 5 percent of the adult population using insurance products, there is potential for much greater take-up. In recognition of the importance of this market, the Pensions and Insurance Authority has led several reforms or initiatives (including developing a legal framework for micro-insurance, strategic planning for the industry, identification of insurance key areas to be improved and awareness campaigns). However, there is still much work to be done to encourage competition among insurance companies as well as on product innovation and improvement with a view to enhancing service quality and reducing costs. It is particularly important to develop customer centric insurance services and products which are geared towards the needs of people living in rural areas with low and irregular incomes. For example, micro-insurance products could help to meet these needs. Given the lack of granular data on customer and market needs, providers need to invest in the capacity to source customer understanding systematically through market research and mining data available within the institution or within its partners. Collecting data and information is, however, not sufficient. Specific staff and units should be responsible for deriving insights from the data to customize the value proposition for specific market segments. 6 PRNewswire, Synopsis, The Insurance Industry in Zambia, Key Trends and Opportunities to 2020, 2016. 6 Financial Capability and Its Relationship with Financial Inclusion Knowledge of basic financial concepts is a challenge in Zambia, which is exemplified by the fact that, on average, respondents were able to correctly answer only 3.7 out of 7 questions on the financial literacy quiz.7 Adults in Zambia can perform simple numerical calculations, yet most of them struggle to solve more complex financial numeracy tasks and to identify better bargains. Adults from the lowest income quartile and from rural areas were the worst performers on the quiz. Respondents are, on average, familiar with financial products offered by 4.1 different types of providers. Almost all respondents were found to be aware of banks and saving/credit institutions and a high proportion knew about MTOs and e-money agents. Insurance products are known about by 18 percent of adults, unit trusts and MFIs are both known about by 15 percent. and 9 percent are familiar with products offered by brokerage houses. Only 0.8 percent of respondents knew of fewer than 2 types of financial products providers and 1.5 percent were familiar with more than 6. Financial capability scores from 15 different countries show that Zambia compares favorably in terms of living within one’s means (the best score from the 15 countries) and planning for the unexpected. However, it fares poorly for choosing financial products, controlled budgeting and planning for old age. Urban adults had higher financial capability scores than their rural counterparts except for controlled budgeting. The same is true when comparing the richest and poorest segments of the population. Adults who saved as children outscored others in almost every financial capability topic, especially in planning for the unexpected, but also in saving capacity, planning for old age and in living within one’s means. Adults who did not save as children got slightly higher scores on topics of self-discipline, choosing financial products and controlled budgeting. Adults who saved when they were children are more likely to avoid over-borrowing. Zambians with low financial literacy8 tend to be less financially included and to utilize more informal products than those with higher levels of financial literacy. The analysis of the relationship between financial inclusion and financial capability reveals that there is a strong correlation between financial inclusion and financial knowledge (financial literacy level and product awareness). Moreover, there is also a strong correlation between product awareness and the extent to which people use formal financial products. There are no substantial differences in the financial behaviors and attitudes of Zambian respondents between financially included and excluded. Recommendations The National Strategy on Financial Education (NSFE) for Zambia continues to provide a firm foundation to strengthen the financial capability of the population, though it needs to be updated. The NSFE, which was published in 2012, considered the following: information and views expressed during stakeholder workshops held in October 2010 and November 2011, an analysis of the FinScope Zambia 2009 survey findings9 and a stock-take study.10 Much of the NSFE remains relevant and it is important to build on this Strategy, rather than to start afresh in order to avoid wasteful duplication of effort and unnecessary delay. 7 To assess adults’ financial knowledge and their basic numeric skills, the Zambian financial literacy quiz covered basic computation and financial concepts such as interest rates, inflation, compound interest, risk diversification, and the main purpose of insurance products. 8 Low financial literacy level: adults who correctly answered 1 or 2 questions of the financial literacy quiz or those who incorrectly answered all questions. Medium financial literacy level: 3 to 4 correct answers. High financial literacy level: 5 to 7 correct answers. 9 Financial Access Matters Focus Note No. 6, Financial Education in Zambia: What does FinScope tell us?, FinMark Trust, 2011. 10 Stock-take of Financial Education in Zambia: A Review of Financial Education Initiatives and Opportunities, M&N Associates, 2011. 7 However, given the passage of time since the Strategy was published, the action plan will need to be reviewed and updated. The action plan should outline a set of priority programs to enhance the financial capability of the overall population and specific subgroups such a rural dwellers, low-income segments, and youth. These priorities should consider a range of criteria, including needs, likely reach and impact, as well as costs and availability of resources. As part of the review and updating of the action plan, discussions should be held with stakeholders (identified in the action plan) to establish whether they remain willing and able to undertake the specified actions and whether any other modifications should be made; and timelines will need to be revised. Consideration should also be given to whether changes should be made to the content of the action plan to account for the findings of the 2016 Zambia Financial Capability Survey. The National Strategy on Financial Education can provide a good fit with the Zambia’s National Financial Inclusion Strategy 2017-2022. Based on an analysis of 17 publicly available NFISs, a recent WBG publication 11 concluded that 15 countries included a dedicated financial capability section in their broader NFIS. Experience has shown that in countries which have developed and begun to implement a national financial capability strategy this can help to promote co-operation between relevant stakeholders, avoid duplication of resources, and minimize gaps and overlaps. Develop a monitoring and evaluation (M&E) framework to measure progress in implementing the NSFE. As envisaged in the NSFE, the framework should provide guidance to stakeholders on how to test programs before they are rolled out, how to monitor and evaluate programs which are being implemented, how to report the results and should explain how the results will be disseminated to stakeholders generally. Design and use a broad range of programs, including mass media channels, text messages, mobile phone applications, etc., to enhance financial knowledge and change attitudes and financial behaviors. People who use different types of media on a regular basis are substantially more likely than less active media consumers to demonstrate more familiarity with financial products and to get higher financial capabilities score. Research12 shows that conveying financial messages through new and traditional media can be effective not only in improving knowledge but also in altering behavior. Edutainment programs are more effective if messages are delivered in an engaging and entertaining manner through appealing stories that are memorable, and if they are repeated and reinforced over time. The survey results indicate that, in Zambia, mobile phones, radio and TV are the most used type of media, which suggests that these channels can be used to reach large numbers of individuals and households. For example, a mobile phone application could be developed to facilitate budget planning. To enable financially included Zambian to benefit from the products they use, financial knowledge and capability-enhancing programs could be provided in parallel with financial products, which most people can access. For example, people could be offered financial education when they open a bank account, take out a loan or take out an insurance policy. Research13 shows that financial education works best when delivered to adults during teachable moments, when they are more likely to be receptive to new information. These educational programs should not only help to close gaps in customers’ understanding of financial concepts but also inform them about (for example) the need to build up a savings cushion for unexpected financial shocks and old age expenses, how best to budget and to avoid overspending and how to choose financial products. Educational materials should be informative, clear, impartial, and free of marketing. 11 Template for the Design of a National Financial Inclusion Strategy, The WBG, 2016. Online available at: http://pubdocs.worldbank.org/pubdocs/publicdoc/2016/1/379031452203008464/WBG-FMGP-Template-for-Designing-a-NFIS-Jan- 2016-FINAL.pdf 12 Berg, Gunhild and Bilal Zia. 2013. “Financial Literacy through Mainstream Media: Evaluating the Impact of Financial Messages in a South African Soap Opera.” World Bank Working Paper, Washington, DC. Di Maro, Vincenzo, Aidan Coville, Siegfried Zottel and Felipe Alexander Dunsch. 2013. “The Impact of Financial Literacy through Feature Films: Evidence from a randomized experiment in Nigeria.” Financial Literacy & Education, Russia Trust Fund. 13 Yoko et al 2012 8 Financial capability content should be fully embedded into primary, secondary, vocational, and tertiary school curriculum. If people form sound habits on how to manage their money from a young age, they are more likely to adhere to these throughout their lives. The survey shows that adults who saved as children outperformed others in almost every financial capability topic and are more likely to avoid over- borrowing. High quality resources will need to be developed and teachers will need to be well-trained on how to provide effective financial education. There are several websites containing links to teaching resources. 14 It is more realistic to integrate financial education into one or two existing subjects, such as mathematics, economics or social studies, rather than to seek to add a new subject into the curriculum. 15 Among the prerequisites for the successful implementation of the National Strategy on Financial Education are a well-publicized commitment from the Governor of the Bank of Zambia to lead this work; and dedicated staff, with relevant skills and experience, within BoZ to drive forward the work. International experience strongly suggests that a national strategy on financial education will not be successfully implemented in the absence of an effective lead organization. This in turn requires both staff of the lead organization and other stakeholders to be clear that the most senior officer of the lead organization – in the case of Zambia, this is the Governor of the Bank of Zambia – takes a close personal interest in securing the effective implementation of the strategy. It is also essential that dedicated staff within the lead organization are identified and given a mandate to co-ordinate and drive forward work in implementing the strategy and to provide support to other stakeholders – for example, by developing simple, clear and persuasive communication; and by providing a source of expertise on the testing, monitoring and evaluation of financial capability programs. This staff can include secondees from other organizations, but they should all come under the direction of BoZ management. National Financial Inclusion Working Group 6, on Financial Consumer Protection and Financial Capability, should subsume the role of the Financial Education Steering Committee, which was described in paragraph 135 of the National Strategy on Financial Education for Zambia. Technical groups, reporting to the Working Group, should be appointed as and when required to guide work on key financial capability initiatives. Chapter 4 of Zambia's National Financial Inclusion Strategy 2017-2022 sets out the co-ordination structure for the implementation of this Strategy. This structure includes the establishment of six working groups, including one dedicated to financial consumer protection and financial capability. The appointment of a separate Steering Committee to oversee the implementation of the National Strategy on Financial Education would create an unnecessary additional layer and would be a recipe for confusion: instead, National Financial Inclusion Working Group 6 should subsume the role which the National Strategy on Financial Education had envisaged for a Steering Committee. 14 These include the Australian Securities and Investments Commission (ASIC) MoneySmart Teaching website (which lists a range of educational materials, each of which has been vetted by a quality assurance process); the US Jump$tart Coalition Clearinghouse and the UK Personal Finance Education Group (PFEG) website. Some resources are available free of charge and others are available for purchase. The Citigroup Financial Education Curriculum contains interactive lessons, facilitator tips and printable lesson plans (which are available in several languages) for use from kindergarten level upwards. 15 An evidence of inclusion of financial capability content in school curriculum is documented in Bruhn, Miriam, Luciana de Souza Leão, Arianna Legovini, Rogelio Marchetti and Bilal Zia. 2016. "The Impact of High School Financial Education: Evidence from a Large-Scale Evaluation in Brazil." American Economic Journal: Applied Economics, 8(4): 256-95. 9 Financial Consumer Protection In general, users of financial services have expressed satisfaction with the services offered by financial services providers, especially MTOs and insurance companies. Consumers are less satisfied with banks, national savings and credit institutions: the satisfaction level is nevertheless 79 percent, though less than this for people who live in rural areas and for younger adults. Around 13 percent of adults had a problem with a financial services provider but only 25 percent of them tried to solve it. Men were more likely than women, and younger adults were more likely than older adults, to have a problem. The most frequent action taken by adults who tried to resolve a problem was to stop using the service before the contract ended. Other measures included submitting a complaint to the provider or a claim to a government authority. The main cause for inertia by adults who did not try to resolve a problem with financial services providers is the lack of awareness of the proper government institution to contact. Other believed that financial institutions are too powerful or that government authorities or the law do not work properly. Adults who did not take any action to settle a dispute with a financial services provider were disproportionately male, younger adults, from a rural area, from the highest income quartile, with primary education only, and either informally employed or self-employed. Recommendations Internal complaints handling requirements should be issued for financial institutions to ensure adequate and fair mechanisms are in place for providers to handle complaints, and the procedures should be well publicized. Survey results shows than Zambian adults avoid using complaint procedures because they are not familiar with the complaint system or they prefer to abandon the financial product rather than go through the complaint process. In line with the WBG’s Good Practices for Financial Consumer Protection, legal or regulatory provisions should require financial institutions to provide customers with information on their complaint handling procedures (including contact information and time limits). This information should not only be disclosed in products’ terms and conditions, but should also be prominently posted in branches and online. In addition, customers should be informed about formal redress systems or legal remedies. Create a dedicated section about regulations that ensure/address responsible lending practices, cooling off periods, collection practices, sales practices, and treatment of dormant accounts on the website of main regulatory institutions. In addition to the introduction of minimum complaints handling requirements, it is recommended that the BoZ, the SEC, and the PIA expand the contents of their websites to include detailed information on consumers’ rights and complaint handling procedures for each type of entity under their supervision. Deploy an adequate range of supervisory tools to promote sound business practices and ensure compliance of FIs with consumer protection requirements, including but not limited to issuing Key Facts Statements (KFS), other disclosure requirements for core retail financial products, and complaints handling mechanisms. Market monitoring, offsite and onsite inspections, mystery shopping, and research can be useful tools in the overall market conduct supervisory toolbox to assess the compliance of financial institutions with regulatory requirements. To optimize the use of scarce resources, financial consumer protection supervision should be risk-based, with prioritization of riskier consumer issues and institutions. Decide whether to establish an independent alternative dispute resolution mechanism, such as a financial ombudsman. A financial ombudsman is a third party who deals independently with complaints from 10 consumers that the financial services provider has not been able to resolve to the satisfaction of the consumer. An ombudsman service is more accessible and cheaper than the courts and reduces the burden on the courts. A financial ombudsman is well-positioned to analyze trends in financial consumer complaints and propose ways of securing improved practices by financial institutions. The principles underpinning financial ombudsmen have been summarized by the WBG16, and include: independence; fairness; clarity of scope and powers; effectiveness and efficiency; accessibility; transparency; and accountability.17 To identify the most effective institutional set-up, further analysis may be needed. The financial ombudsman scheme could be fully or partly paid for by the government (out of taxation) or it could be paid for by charging the cost to the financial industry. Because of the many other pressures on public finances, it is more common for the cost of such a scheme to be borne by the industry from which the ombudsman's work arises – though perhaps with some upfront contribution from public funds to help in establishing it. The harmonization of financial consumer protection provisions would be a key starting point to ensure that financial service providers have some common framework as it relates to servicing of customers. The reason being that currently, financial consumers are subjected to different recourse mechanisms depending on which financial regulator they are interacting with, largely because of the divergent protection provisions in the different pieces of legislation. 16 For more information and guidance see WBG, 2012: Resolving Disputes between Consumers and Financial Business: Fundamentals for a Financial Ombudsman - A Practical Guide Based on Experience in Western Europe. Online available at: http://siteresources.worldbank.org/EXTFINANCIALSECTOR/Resources/ Financial_Ombudsmen_Vol1_Fundamentals.pdf 17 See also International Network of Financial Services Ombudsman Schemes: Fundamental Principles. Online available at: http://www.networkfso.org/principles.html 11 Background on Zambia Survey The financial capability questionnaire used for this survey has been extensively tested in the context of middle- and low-income countries. The survey instrument used is based on a questionnaire developed with support by the Russia Financial Literacy and Education Trust Fund and is tailored to measure financial capability in low- and middle-income countries, although it can also be used in high-income countries. Extensive qualitative research techniques were used to develop this survey instrument, including about 70 focus groups and more than 200 cognitive interviews in eight countries. These research techniques were used to identify the concepts that are relevant in middle- and low- income settings, and to test and adapt the questions to ensure that they are well understood and meaningful across income and education levels. The instrument is currently used or planned to be used in 14 countries in Latin America, Africa, Middle East and East Asia and the Pacific. The survey instrument used allows financial capability, financial inclusion, and consumer protection issues to be assessed and measured. Financial capability is measured by knowledge of financial concepts and products, and by attitudes, skills and behavior related to day-to-day money management, planning for the future, choosing financial products and staying informed. In order to jointly analyze financial capability and inclusion, the survey instrument captures information on the usage of different kinds of financial products and providers. The financial consumer protection section gathers information on the incidence of conflicts with financial services providers and levels of satisfaction with financial products offered by different financial institutions. The survey instrument has been further customized to the Zambian context, through the addition of specific questions like those, for example, relating to knowledge about Zambian financial regulatory institutions. The Zambian survey is representative of the financially active population and is comprised of a total sample of 2,505 adults.18 To fulfill the requirements of a scientifically sound survey which allows inferences to the whole universe of financially active adults in Zambia, probability sampling techniques were used to select a sample of 2,505 adults. As such, the results of the World Bank report entitled Mapping Subnational Poverty in Zambia in 2015, 19 that uses results from Zambia’s Living Conditions Monitoring Survey (LCMS) 2010, as well as the 2010 Census of Population and Housing were used as a sampling frame. The population was divided into 8 strata: wards were characterized as rural or urban. Then, they were distributed into four poverty levels (low, medium low, medium high and high), using poverty headcounts for each ward taken from the report on Mapping Subnational Poverty in Zambia. The sample of individual respondents within households was selected through three-stage cluster sampling. The wards were randomly selected as primary sampling units (PSUs) with probability proportional to size (PPS) (number of households) at the first stage, and consisted in selecting 167 primary sampling units to reach the sample target. In each selected PSU, 15 households were randomly drawn and targeted for surveying at the second stage. This choice of having 15 randomly drawn respondents instead of 20 per EA reduced the possible clustering effect even further. Finally, within each selected household, eligible adults either responsible for personal or household finances were randomly drawn by means of the Kish grid. Individual weights were calculated and used in the ensuing analysis to adjust for varying probabilities of selection (design weights). Between February and September 2016, a Canadian survey firm implemented the survey using computer-assisted personal interview methods (CAPI). Étude Économique Conseil (EEC Canada), a Montreal based consulting firm, was hired to conduct the Financial Capability Survey in Zambia. To ensure highest data quality and avoid common errors associated with paper-and-pencil surveys, an electronic version of the questionnaire including internal consistency tests were programmed and the survey was administered 18 Population aged 18 and older 19 Mapping Subnational Poverty in Zambia - Report Number 95276, March 2015. 12 using power PCs. Due to extensive efforts and different strategies used (e.g. training of enumerators on refusal conversion strategies, communication with respondents to inform them of the coming survey as well as explaining the surveys’ objectives, up to 5 contact attempts at different moments during the period of the survey, etc.) the total non-response rate was around 3.31% percent of the total sampled households. The adult population for which the results of this survey are meant to be extrapolated has the following key characteristics: 41 percent of the population lives in urban areas, while the remaining 59 percent live in rural settings (see Figure 49). Slightly less than half of the population is female (48 percent, see Figure 51). Ranking all individuals by their reported household income and dividing them into four groups, 28 percent of the population fall in the lowest income segment (up to 2,000 ZMW per month), 24 percent in the second lowest quartile (between 2,001 ZMW and 7,000 ZMW), 23 percent in the second highest (between 7,001 ZMW and 20,300 ZMW), and 25 percent in the highest income quartile (more than 20,300 ZMW, see Figure 56). Fifty-two percent of the population is younger than 35, 35 percent is between 35 and 55, and 13 percent of the population is older than 55 (see Figure 52). In terms of the education attained, less than 1 percent of the population has some or completed tertiary education including university or other higher education, 7 percent has some or completed senior secondary schooling, 75 percent has some or completed junior secondary schooling, while around 9 percent of the population has no schooling at all (see Figure 54). Irregular and uncertain income flows characterize 49 percent of the population, while the remaining 51 percent is characterized as earning a stable income (see Figure 55). The average number of adults per household is three, whereas an average sized household is comprised of six people. As shown in Figure 53 of the Appendix, 28 percent of the respondents live in households with one to three members, 44 percent in households comprised of four to six members, and 28 percent live in households with 7 or more members. The profile of Financial Capability Survey matches with key characteristics of Zambia’s general census. As Table 1 presents, there are minor differences between Zambia population distribution and the surveyed population. Table 1. Comparison between Census Key Characteristics and Financial Capability Survey Profile Financial Capability Country Census Survey Population distribution Less than 15 years old 45.4% 44.4% Between 15 and 64 years old 52.0% 53.3% More than 64 years old 2.6% 2.4% Gender distribution Male 49.3% 49.2% Female 50.7% 50.8% Area distribution Rural 54.8% 57.0% Urban 45.2% 43.0% Area – gender distribution Rural – female 50.6% 50.9% Urban – female 50.7% 50.6% Source: Republic of Zambia, Central Statistical Office, National Analytical Report 2010 Census of Population and Housing. WBG Financial Capability Survey, Zambia 2016. 13 1 Financial Inclusion 1.1 Introduction Increasing the access, usage and quality of financial products and services has become a priority in Zambia. Over the past years, Zambian authorities have made considerable efforts to develop strategies to improve the operational and legal environment of the financial sector. In particular, the Zambian government formulated and implemented the Financial Sector Development Plan (FSDP) that focused during its first phase (2004 – 2009) on (i) “the establishment of an institutional framework to develop the FSDP and a regulatory framework for a credit reference bureau, (ii) the revision of the financial sector legislation (revision of Banking and Financial Services act, draft of the legislation about non-banking institutions, rural finance, house finance and development finance, and harmonization of law governing financial institutions), (iii) the identification and resolution of weakness in the insolvent state-owned institutions and (iv) the measurement and analysis of financial services evolution (demand and supply side)”.20 The Zambian government ratified its commitment to financial inclusion with an extension of FSDP known as phase II (2010 – 2015). The priorities of this second phase were to (i) “enhance market infrastructure, (ii) increase competition in the financial sector and (iii) increase access to finance”. 21 As part of authorities and stakeholders’ commitment, Zambia also became a member of the Alliance for Financial Inclusion (AFI). It signed the Maya Declaration in 2011. The country aimed to increase its financial inclusion level from 37.3 percent (2009) to 50 percent or more, provide affordable and convenient financial services in all districts and develop a system to evaluate the progress and achievements of financial inclusion strategies. 22 The consolidation of all these policies has brought positive results (as exposed in section 1.2). However, Zambian authorities recognize that a majority of Zambians are not financially included. They are preparing a reviewed National Financial Inclusion Strategy (2017 – 2022) whose main objective is “universal access and usage of a broad range of quality and affordable financial services”.23 The information provided in this chapter will enable to fully understand the state of financial inclusion in Zambia and provide valuable input for interpreting the findings on financial capability. Collecting survey data from individuals – that is, from the demand side – can provide valuable insight into the usage, value and limitations of existing financial services. Demand-side survey data also facilitates analysis of how patterns of financial inclusion may vary across different population segments, and the degree to which different financial behaviors – such as saving, borrowing, and making payments – overlap. The data and analysis presented below can be used to expand financial inclusion in Zambia by identifying population segments, setting national financial inclusion targets, and designing reforms and projects. Finally, the data can provide a baseline survey that can be used to measure the progress of reforms and initiatives. 20 BoZ, Progress report on the implementation of the Financial Sector Development Plan (FSDP) (January 2010 – June 2015). 21 BoZ, Progress report on the implementation of the Financial Sector Development Plan (FSDP) (January 2010 – June 2015). 22 The Maya Declaration and Alliance for Financial Inclusion, Commitment made by the Bank of Zambia, September 2011. 23 Republic of Zambia, National Financial Inclusion Strategy 2017 – 2022, Draft Conceptual Framework, September 2016. 14 1.2 Headline Measures for Financial Inclusion About 40 percent of the surveyed adults in Zambia own an account at a formal financial institution. Compared to other lower-middle income countries, Zambia has some catching up to do on the banking industry’s supply side. As shown in Table 2, Zambia fares less favorably on average in terms of financial inclusion,24 commercial bank branches’ accessibility and domestic credit provided by the financial sector. Even when compared to its African peers, Zambia is lagging behind in terms of domestic credit. It should be noted that the progression shown in financial inclusion from 35.6 percent in 2014 to 40.2 percent in 2016 may be somewhat overstated since the Survey captures people aged 18 and above, whereas Findex includes adolescents (15-17 years old) who are typically less financially included. When investments, private pensions, and insurance are included as formal financial products, the Survey finds that 46.8 percent of Zambian adults use some formal financial product. Table 2. Measures of Financial Inclusion and Development across Economies Financial Commercial Automated Firms using Domestic GDP per account bank teller banks to credit capita ownership branches machines finance provided by (constant (% of adults) (per 100,000 (ATMs) investment financial 2010 US$) adults) (per 100,000 (% of firms) sector adults) (% of GDP) Zambia 40.2 (FinCap 5.0 (2014) 9.6 (2013) 12.2 (2013) 29.4 (2015) 1,619 (2015) 2016) 35.6 (Findex 2014) Cameroon 12.2 (2014) 1.9 (2014) 3.5 (2014) 14.8 (2015) 1,309 (2015) Côte d'Ivoire 34.3 (2014) 4.7 (2013) 5.9 (2013) 31.5 (2015) 1,492 (2015) Ghana 40.5 (2014) 6.1 (2014) 8.2 (2014) 21.2 (2013) 35.1 (2015) 1,696 (2015) Kenya 74.7 (2014) 5.8 (2014) 10.2 (2014) 43.2 (2013) 45.2 (2015) 1,133 (2015) Lesotho 18.5 (2011) 3.6 (2014) 11.2 (2014) 0.7 (2014) 1,227 (2014) Mauritania 22.9 (2014) 6.9 (2014) 7.7 (2014) 12.8 (2014) 1,338 (2014) Sudan 15.3 (2014) 3.1 (2014) 4.2 (2014) 6.7 (2014) 20.9 (2015) 1,723 (2015) Swaziland 28.6 (2011) 5.8 (2014) 32.1 (2014) 16.8 (2015) 3,068 (2015) All lower- 42.7 (2014) 8.0 (2014) 18.1 (2014) 20.2 (2015) 67.8 (2015) 2,047 (2015) middle income Sub-Saharan 34.2 (2014) 3.9 (2014) 5.3 (2014) 19.1 (2015) 57.9 (2014) 1,652 (2015) Africa Source: Data on formal account ownership is drawn from 2016 WBG Financial Capabilities Survey (Zambia), and 2011 and 2014 Global Findex (other economies); data on commercial bank branch penetration, data on firm finance is drawn from Enterprise Survey data (latest available year by country); data on domestic credit to GDP and GDP per capita are drawn from the World Development Indicators. Financial inclusion in Zambia has nearly doubled in the last ten years. Figure 1 shows the evolution of financial inclusion between 2005 and 2016. During this period, formal financial inclusion has risen steadily from 21.3 percent in 2005 to 40.2 percent in 2016. Percentage of individuals using banks has also increased from 14.6 to 35.6 percent. However, there was a drop from 31.3 percent in 2014 to 24.8 percent in 2015, suggesting that people may have migrated away from financial institutions and switched to informal methods. Users of e-money services were accounted for starting only in 2014 at 12.1 percent and rose to 14.7 percent in 2016. 24 Formal account ownership (“financially included”) is defined in the Zambian financial capability study as the percentage of respondents who reported having an account (by themselves or together with someone else) at a bank or another type of financial institution (formal credit, mortgage, credit from microfinance organizations or from the decentralized financial system, debit or credit card, formal savings, current or savings accounts), or having personally used a mobile money service in the past 12 months. 15 Figure 1. Evolution of Financial Inclusion 2005 - 2016 Note: E-money indicator wasn’t measured in 2005, 2009 and 2011. WB Findex Banked proportion isn’t available for 2011. This last percentage in 2014 includes bank and MFI usage. 2016 Zambian financial inclusion index can’t be directly compared to Finscope headline indicator (59.3% (2015), 37.3% (2009) and 33.7% (2005)). In fact, while this last measure includes the usage level of informal and formal financial products, FCCP index only aggregates formal financial usage. The comparison presented above only highlights formal evolution because of this situation. Source: 2005 and 2009 data is drawn from FinScope Zambia 2009. 2011 data is drawn from 2011 Global Findex. 2014 data is drawn from 2014 Global Findex. 2015 data is drawn from FinScope Zambia 2015. 2016 data is drawn from 2016 WBG Financial Capabilities Survey (Zambia). Across the main socioeconomic and demographic characteristics, income level was found to have the most significant impact on financial inclusion, followed by whether or not adults were located in rural areas and were from the female group. In fact, Figure 2 shows that only 29.4 percent of the first income quartile are financially included compared to 52.5 percent for the fourth income quartile, which represents a 23.1 percent increase between these two categories. Moreover, 35.5 percent of rural inhabitants are financially included as opposed to 46.1 percent for urban dwellers, corresponding to a 10.6 percent difference between sectors. Finally, 37.2 percent of women were found to be financially included compared to 43.1 percent for men, representing a difference of 6 percent. These differences remain statistically significant even after controlling for income, education, and a range of other individual characteristic (see Table 9). 25 25 The multivariate regression model includes the following control variables: age, gender, education, urban/rural, income, household head status, employment, whether saved as a child, and media consumption. 16 Figure 2. Financial Inclusion by Gender, Urban/Rural, and Income Source: WBG Financial Capability Survey, Zambia 2016. There is a strong negative correlation between financial inclusion and regional poverty. Copperbelt and Lusaka are the most financially included provinces whereas Eastern and Western are the least. As Table 3 summarizes and, Map 1 and Map 2 detail, provinces at the top of the range (Copperbelt and Lusaka) have a financial inclusion rate averaging 48.5 percent, which is about 19 percent more than the average for the provinces of Eastern and Western, sitting at the bottom of this range. Table 3. Poverty Level vs Financial Inclusion Level Region Ranking financial inclusion Ranking poverty level Copperbelt 1 8 Lusaka 1 8 Central 3 7 North Western 4 5 Northern & Muchinga 5 4 Southern 6 5 Luapula 7 3 Eastern 8 1 Western 8 1 Source: Financial inclusion by region is drawn from WBG Financial Capability Survey, Zambia 2016. Regional poverty level is drawn from WBG Mapping Subnational Poverty in Zambia - Report Number 95276, March 2015. There seems to be a correlation between financial inclusion and the size of household or stability of income. Figure 3 shows that financial inclusion increases from 35.5 to 40.8 and 42.1 percent for households of 1 to 3, 4 to 6 and 7 to 9 members, respectively. Furthermore, financial inclusion averages 38.7 percent for people with an unstable income as opposed to 41.6 percent for those with a stable income. 17 Figure 3. Financial Inclusion by Household Size and Income Stability Source: WBG Financial Capability Survey, Zambia 2016. Map 1. Financial Inclusion by Province (%) vs Regional Poverty Level (I) Financial Inclusion by Province 18 Map 2. Financial Inclusion by Province (%) vs Regional Poverty Level (II) Regional Poverty Level Source: Financial inclusion by province is drawn from WBG Financial Capability Survey, Zambia 2016. Regional poverty level is drawn from WBG Mapping Subnational Poverty in Zambia - Report Number 95276, March 2015. 1.3 Financial Product Usage The following sections dig deeper into the types of institutions and specific products used by Zambian adults, both within and outside the formal financial system. The analysis is organized by type of financial institution. Each section documents overall awareness of a given institution among respondents, explores patterns of historical usage, i.e. whether a respondent has ever used that institution, and their current usage. 19 1.3.1 Commercial Banks, National Saving and Credit Institutions The banking sector accounts for over 90 percent of financial system assets.26 “The top five bank’s assets account for about 63.6 percent of total banking sector assets. The banking sector comprises 19 commercial banks, which are made up of two local and 17 foreign owned banks, based on the revised classification of commercial banks under the new capital adequacy regulations. Out of the 17 foreign banks, 13 are subsidiaries of foreign banks while the remaining four are not affiliated to foreign banking groups. The foreign banks include subsidiaries of South African banks, UK-based banks and other pan-African banks.”27 There is, however, only one savings and credit institution, the National Savings and Credit Bank. The strength of Zambia’s banking sector is matched by high awareness of these institutions. Almost everybody knows about services offered by banks, and its national saving and credit institution. 93 percent of the sampled population have or have used such services in the past, but only 36 percent currently have an account, which may suggest a low satisfaction among past (but not actual) users. As the regression analysis suggests (Table 10), and Figure 4 exposes, bank usage exhibited the same pattern across the main socioeconomic and demographic characteristics as explained in section 1.2 (Headline Measures for Financial Inclusion). The biggest disparity exists between adults in the fourth quartile who currently have 17 percent more accounts than those in the first quartile. The next level of inequity resides with urban dwellers who presently have more accounts, in the order of 6 percent, than their rural counterparts. Finally, in terms of gender, 3 percent more men than women currently have such account. Figure 4. Knowledge and Usage of Banks, National Saving and Credit Institutions by Individual Characteristics Source: WBG Financial Capability Survey, Zambia 2016. 26 2014. 27 WBG, Finance and Markets Global Practice, Financial Inclusion Support Framework, Zambia Country Support Program, October 2015. 20 After bank accounts, loans, followed by mortgage and then credit cards, are the other banking products that Zambian adults currently use. As Appendix A indicates, a mere 4.5 percent of adults report having formal credit from a bank. Socioeconomic groups with the highest percentage of formal credit are the wealthy (6.3 percent), the urban population (5.4 percent) and men (4.6 percent). Moreover, only 4.1 percent of Zambian adults currently have a mortgage. One possible factor that may influence the mortgage index is the high interest rates in Zambia. The comparison of mortgage rates among 46 African nations reveals that Zambia is at the top of the list (interest rates higher than 25 percent) after Malawi and Ghana. 28 While Zambia’s urbanization rate29 (4.1 percent) is not low compared to other low-middle income economies such as Kenya (4.2 percent), Mauritania (3.4 percent) and Lesotho (3.1 percent), Zambia’s housing affordability level30 (3.8 percent) is far behind that of other previously mentioned nations. In fact, the most recent index is 29.4 percent for Kenya, 20.3 percent for Lesotho and 5 percent for Mauritania. Finally, credit cards are the most uncommon banking product. These are used by only 1 percent of the Zambian population. 1.3.2 Payment Providers Money Transfer Operators Nine out of ten adults know about services offered by MTOs but only about 53 percent use such services, mainly the rich population living in urban districts. As shown in Figure 5, 90 percent of respondents know about services offered by MTOs, 76 percent have already used such services in the past and 53 percent currently utilize these. MTOs are used by 19 percent more urban inhabitants than rural dwellers, and 19 percent more individuals belonging to the fourth income quartile than those from the first quartile. There is no difference between men and women. MTO usage is linked to the remittances trend in Zambia. In fact, Zambia is one of the top 10 remittance senders among Sub-Saharan economies. Such remittances represent about 0.3 percent of GDP (0.1 US billions). Figure 5. Knowledge and Usage of Money Transfer Services by Individual Characteristics Source: WBG Financial Capability Survey, Zambia 2016. 28 HOUSING FINANCE IN AFRICA: A review of some of Africa’s housing finance markets. Africa Housing Finance Yearbook 2016. Centre for Affordable Housing Finance in Africa. 2016. 29 Ibid. 30 % of urban households that can afford the cheapest newly built house by a formal developer in 2016. 21 E-money Agents Electronic money (e-money)-based instruments: In general terms, these instruments involve the payer maintaining a pre-funded transaction account with a PSP [Payment Service Provider], often a non-banking entity. Specific products include online money when the payment instruction is initiated via the internet, and mobile money when initiated via mobile phones and prepaid cards. Although 76 percent of adults know about e-money services, only 29 percent have used them in the past and 15 percent utilize these presently, suggesting a possible lack of trust for this type of service; such services are mostly utilized by rich men living in urban areas. As depicted in Figure 6, 22 percent more rich adults than poor ones make use of e-money services, 15 percent more urban dwellers rely on such methods than their rural counterparts, and 6 percent more men than women utilize such instruments. Figure 6. Knowledge and Usage of E-money Agents by Individual Characteristics Source: WBG Financial Capability Survey, Zambia 2016. Compared to other African countries, Zambia has a low cellular penetration rate as well as low usage of mobile financial services. As shown in Table 3 and Figure 7, Zambia’s mobile penetration rate is 74.5 percent compared to the average rate (90.8 percent), and strikingly low when compared to Ghana (129.7 percent) and Côte d’Ivoire (119.3 percent). Zambia’s e-money usage rate among adults (14.7 percent) is also lower than the average rate (19.8 percent). 22 Table 4. Measures of Mobile Financial Service Penetration across Economies Mobile cellular Mobile financial Use of mobile subscriptions services MFS products financial services (per 100 people) penetration available (GSMA) (%) (% per cellular) Zambia 14.7 74.5 19.73 3 or more mobile money services Cameroon 1.8 71.8 2.51 3 or more mobile money services Côte d'Ivoire 24.3 119.3 20.37 3 or more mobile money services Ghana 13.0 129.7 10.02 3 or more mobile money services Kenya 58.4 80.7 72.37 3 or more mobile money services Mauritania 6.5 89.3 7.28 2 mobile money services Sudan 70.5 1 mobile money services Average 19.8 90.8 22.05 Source: Data on the use of mobile financial services and formal account ownership is drawn from 2016 Financial Capabilities Survey (Zambia) and 2014 Global Findex (other economies). Mobile cellular subscriptions (per 100 people) is drawn from the 2015 World Development Indicators. Data on MFS products available is drawn from the GSMA Mobile Money for the Unbanked Deployment Tracker (2014 State of the Industry Mobile Financial services for the Unbanked). Figure 7. Number of Mobile Money Accounts per 1,000 Adults Source: Data on registered mobile money accounts per 1,000 adults for other countries in Sub-Saharan Africa is drawn from GSMA, “The mobile Economy. Sub-Saharan Africa 2015” / World Bank Global Findex. 23 On the other hand, Zambia does not fare well as far as the mobile services’ tax rate is concerned, which can be an important barrier to increasing digital inclusion.31 As Figure 8 illustrates, Zambia is in the top 5 Sub-Saharan economies that have the highest mobile consumer tax rate. While mobile phone users in Kenya and Zimbabwe have to pay consumer taxes representing 21 percent of the total cost of mobile ownership, Zambian mobile-users pay 26 percent, which is 6 percent above the Sub-Saharan average level (20 percent). Figure 8. Consumer Taxes as a Proportion of Total Cost of Mobile Ownership 2014 Source: GSMA, “The mobile Economy. Sub-Saharan Africa 2015”. 1.3.3 Microfinance Institutions Banks continue to represent the largest portion of the financial sector in terms of assets, MFIs still play a relatively small role in Zambia and are primarily focused on payday lending. There are 33 MFIs licensed by the Bank of Zambia as of September 2014, an increase of 29 from four at the time the regulations were passed in 2006. Regulation divides Zambia’s MFIs into two categories – deposit-taking MFIs (development MFIs) and non-deposit-taking MFIs (credit companies, or payroll-based MFI). According to a WBG survey, the microfinance sector in Zambia, as of 2012, recorded K 214 million in assets and a gross loan portfolio of K 168 million. Development MFIs are required to have a minimum regulatory capital of K 250 million and an additional K 25 millions of payroll-based regulatory capital. 32 Recently, the growth in the MFI loan book for all enterprise categories fell markedly after the imposition of the cap in 2013; the objective was to reduce the cost of borrowing, increase access to finance for SMEs and reduce over-indebtedness. In fact, the volume of loans for medium sized enterprises shrank, while the growth rate for small and micro enterprises reduced by more than 50 percent. 33 31 GSMA, “The mobile Economy. Sub-Saharan Africa 2015”. 32 WBG, Finance and Markets Global Practice, Financial Inclusion Support Framework, Zambia Country Support Program, October 2015. 33 Ibid. 24 MFI products are known and used by very few people (4 percent). Data from Figure 9 shows that knowledge and usage of MFI products remains low: 14 percent of the adult population is familiar with them and only 4 percent currently use these. There are 3 percent more rural than urban dwellers utilizing such products. Finally, 2 percent more men than women subscribe to such services. Figure 9. Knowledge and Usage of Microfinance Organizations by Individual Characteristics Source: WBG Financial Capability Survey, Zambia 2016. MFIs target a different set of clients than do banks or national saving and credit institutions. People who use MFI credit the most are poor rural men. With respect to banks (see Figure 10 and Figure 12), the richest Zambian adults are 4 percent more likely to have a bank loan than an MFI loan. MFI usage is inversely correlated with income levels: usage is 3 percent more for lower income groups as opposed to higher income ones. Lower income groups are almost 2 percent more likely to have an MFI loan than a bank loan. Figure 10. Knowledge and Usage of Microfinance Organizations, Banks, National Saving and Credit Institutions by Individual Characteristics Source: WBG Financial Capability Survey, Zambia 2016. 25 Figure 11. MFI and Bank Usage Source: WBG Financial Capability Survey, Zambia 2016. 1.3.4 Insurance Companies The insurance industry has been steadily growing. There are 27 licensed insurance companies, 18 general insurance and nine life insurance companies as of July 31, 2014. The insurance industry is regulated by the Pensions Insurance Authority. The Insurance Act, 1997 as amended in 2005, prohibited insurance companies from conducting both life and non-life insurance business. Significant growth has also been recorded in volume of business underwritten and as of 31 December 2013, the volume of general insurance stood at K 1.022 billion and a total of K 330 million was paid out in claims. This is in comparison to GWP of K 96,485 in 2002 and K 27,167 that was paid out in claims. Regarding the long term, the GWP turnover as of 31 December 2014, stood at K 450 million and K 137 million was paid out in claims in comparison to GWP of K 26,431 and claims amounting to K 9,665 recorded in 2002. 34 There is still room for potential growth of insurance products. Very few Zambians utilize insurance products especially poor and rural adults. In fact, Figure 12 proves that the knowledge of insurance products is quite low in Zambia: only 18 percent of adults are familiar with such services. Overall historical usage of insurance products by the population is 13 percent, however, current usage is only 5 percent. This underscores the lack of trust in such instruments. Only 1 percent of the poorest Zambians currently use insurance, a striking difference with the richest category (8 percent). Moreover, only 2 percent of the rural population is protected by insurance, as opposed to 8 percent for its urban counterpart. 34 WBG, Finance and Markets Global Practice, Financial Inclusion Support Framework, Zambia Country Support Program, October 2015. 26 Figure 12. Knowledge and Usage of Insurance Companies by Individual Characteristics Source: WBG Financial Capability Survey, Zambia 2016. 1.3.5 Brokerage Houses or Unit Trusts A very small fraction of Zambian adults currently have investments, whether male or female, urban or rural, rich or poor, which may highlight the lack of knowledge or interest in such products. More than three quarters of Zambian adults are not aware of brokerage houses or unit trust products and services, and 13 percent35 have used investments products in the past. Only a mere 0.1 percent currently hold a form of investment. High income earners seem to know more about such products (29 percent) compared to low income groups (19 percent). The richest earners currently possess twice as many investment products than the poorest earners. These results may be associated to the fact that “the main capital market in Zambia, the Lusaka Stock Exchange (LuSE) is not well-developed. Specifically, the Lusaka Stock Exchange (LUSE) has 24 listed companies with a market capitalization of 22 percent of the GDP. The debt market is relatively underdeveloped and so is the Zambia Agricultural Commodity Exchange (ZAMACE), which was established in 2007. There is, however, a recent ongoing effort to revitalize the ZAMACE. It currently provides four types of services: (i) commodity trading; (ii) secured transactions; (iii) setting of grades and standards for maize, wheat, soya beans and sunflower; and (iv) a certified warehouse receipt system.” 36 35 This historical rate and its decline over the time have been influenced and explained by two facts. (i) The services and products of brokerage houses or unit trust aren’t limited to stock market. In fact, it is possible for Zambians adults to make investments outside the stock market through these firms by way of pension funds, life insurance, private equity, venture capital and certain types of unit trusts, such as money market fund, bond fund, property fund, gratuity investment fund, education investment fund and microfinance fund. This means that the historical rate covers a variety of products with different trends and patterns. On the other hand, (ii) Lusaka Stock Exchange (LuSE) showed the worst performance (-39.8% in terms of USD) across the African nations over the past five years. This performance was even lower (-51.1%) in the last three years. In terms of local currency, this index was -24.4% in the last year and - 20.4% during the past three years. 36 WBG, Finance and Markets Global Practice, Financial Inclusion Support Framework, Zambia Country Support Program, October 2015. 27 1.3.6 Patterns of Formality and Informality in Savings and Credit Half of adults save money37 and most of them are rich and from urban areas. Furthermore, most people report using formal products. In fact, Figure 13 shows that, among 50 percent of the adults who save money, 52 percent use only formal products, 28 percent utilize only informal ones and the balance (20 percent) have a combination of formal and informal savings. Propensity to save is predominantly higher first among the rich (29% more than the poor in absolute terms) and secondly among people living in urban areas (19% more than rural in absolute terms). The difference between women and men who save is only 5 percent in favor of the former. Figure 13. Formal and Informal Savings Source: WBG Financial Capability Survey, Zambia 2016. About two-thirds of adults currently have debts, contracted mostly using only informal instruments (82 percent) compared to about 8 percent through formal credits only. Furthermore, most of the informal debt is incurred by the poorest and rural segments of the population. Figure 14 demonstrates that among the 66 percent of the population who are in debt, less than 8 percent have taken out loans exclusively from formal providers, more than 82 percent have used only informal credit and the balance (10 percent) holds a combination of formal and informal debt. Informal credit is used more, first, by the lowest income group (76 percent versus 27 percent for higher income) and second, by rural dwellers (69 percent versus 33 percent for urban residents). The variance between women and men is less significantly in favor of the former (56 percent versus 52 percent). Formal credit is used more by higher income groups (9 percent versus 1 percent for lower income) and urban dwellers (8 percent versus 2 percent for rural residents). 37 They save money or they have a financial product for saving. 28 Figure 14. Formal and Informal Credit Note: “Formal only” includes adults that report currently using a mortgage product, formal loan from a bank/national saving and credit institution/MFI or credit card, but do not borrow from money lenders or family/friends. “Informal only” includes adults that report borrowing from money lenders or family/friends but do not use a mortgage product, formal loan from a bank/national saving and credit institution/MFI or credit card. Source: WBG Financial Capability Survey, Zambia 2016. There is a strong formal credit pattern differentiation across provinces in Zambia, with Southern and Luapula displaying the highest levels and Western and Lusaka the lowest ones. As Map 3 illustrates, at the top of the range we have Luapala and Southern with formal borrowing averaging 7.8 percent, which is more than 5 times that of Western and Lusaka (1.5 percent). Map 3. Spatial Distribution of Formal Borrowing (% of Adults with Formal Credit) Source: WBG Financial Capability Survey, Zambia 2016. 29 There is a strong informal credit pattern differentiation across provinces in Zambia, with Northern & Muchinga and Lusaka displaying the highest levels and Western and Southern the lowest ones. As Map 4 exhibits, at the top of the range we have Northern & Muchinga and Lusaka with informal borrowing averaging 65.6 percent, which is more than 4 times that of Western and Southern (14.5 percent). Map 4. Spatial Distribution of Informal Borrowing (% of Adults with Informal Credit) Source: WBG Financial Capability Survey, Zambia 2016. 30 1.4 The Unbanked and Barriers to Owning a Formal Account In Zambia, the approximately 3.8 million financially excluded adults – those who use no formal financial products or services - are disproportionately female, poor, and living in rural areas. Almost 63 percent of Zambian women do not currently use a formal financial product nor service. Nor do 71 percent of the poorest quartile of Zambian adults, or 65 percent of adults living in rural areas. Yet, as stated in the Global Financial Development Report 2014 (World Bank, 2013a), lack of usage of financial products does not necessarily mean lack of access. While some people may have access to financial services at affordable prices, and may decide not to use these, others may lack access because of constraints such as excessively high costs or unavailability of services due to regulatory barriers or other factors. The Financial Capability Survey asked respondents who do not have a formal account to report the reason. The main reason given by unbanked adults for not owning a formal account is the lack of enough money, followed by high account fees. As illustrated in Figure 15, 31 percent of respondents reported the lack of enough money as the main obstacle to formal account ownership, almost twice as much as those who mentioned high account fees (17 percent), institutions being too far away (15 percent) and lack of trust (15 percent). More men than women said that the main barriers were lack of enough money and institutions being too far away, and the inverse (more men than women) was found for high account fees and lack of trust. Figure 15. Reasons for Not having a Formal Account (% of Unbanked Zambians Without an Account) Source: WBG Financial Capability Survey, Zambia 2016. 31 2 Financial Capability Financial Capability is the internal capacity to act in one’s best financial interest, given socioeconomic and environmental conditions. It therefore encompasses the knowledge, attitudes, skills, and behaviors of consumers with regards to managing their resources and understanding, selecting, and making use of financial services that fit their needs. 2.1 Knowledge of Financial Concepts Financial knowledge and skills are especially important in an environment where financial products and services are becoming available to people who have little or no experience of using the formal financial system. While these products and services provide potential benefits, they also give rise to risks that may be unfamiliar to existing, as well as to new customers. To be able to benefit from these new opportunities without being exposed to undue risks, a certain level of financial knowledge and skills is required. Financial knowledge and skills are a key element in Zambia’s financial inclusion goals. The Zambian authorities recognize the importance of financial literacy in enabling people to take informed financial decisions and to take full advantage of financial products and services. As part of FSDP Phase II (see section 1.1), the Zambian authorities formulated the National Strategy on Financial Education for Zambia, whose main objective is that “people in Zambia have improved knowledge, understanding, skills, motivation and confidence to help them to secure positive financial outcomes for themselves and their families by 2017.”38 To assess respondents’ financial knowledge and their basic numeracy skills, seven questions were included in the 2016 Zambia Financial Capability Survey. These covered basic computation and financial concepts such as interest rates, inflation, compound interest, risk diversification, and the main purpose of insurance products. The questions were asked because they capture financial concepts and skills that are considered as being crucial for informed savings and borrowing decisions as well as for being able to manage risks more effectively and/or to take advantage of investment opportunities. A financial literacy index is obtained based on the number of correct responses provided by each survey participant to the seven financial literacy questions. This index ranges from 0 to 7, whereby 0 indicates respondents who incorrectly answered all the questions, while a score of 7 indicates survey participants who answered all of them correctly. Box 1 details questions from the financial literacy quiz. 38 Financial Education Fund, Finmark, BoZ, PIA, SEC, The National Strategy on Financial Education for Zambia, 2012. 32 Box 1. Financial Literacy Quiz Question 1. Imagine that five brothers are given a gift of K 100,000. If the brothers have to divide the money equally, how much does each one get? Question 2. Now, imagine that the five brothers have to wait one year to get their part of the K 100,000 and inflation stays at 10%. In one year’s time will they be able to buy: • More with their share of money than they could today • The same amount • Less than they could buy today • It depends on the types of things that they want to buy (do not read out this option) Question 3. Suppose you put K 1,000,000 into a savings account with a guaranteed interest rate of 2% per year. You don’t make any further payments into this account and you don’t withdraw any money. How much would be in the account at the end of the first year, based on the interest payment made? Question 4. How much would be in the account at the end of five years? Would it be: • More than K 1,100,000 (ZMW) • Exactly K 1,100,000 (ZMW) • Less than K 1,100,000 (ZMW) • It is impossible to tell from the information given Question 5. Let’s assume that you saw a TV-set of the same model on sale in two different shops. The initial retail price you saw was K 5,000 (ZMW). One shop offered a discount of K 500 (ZMW), while the other one offered a 10% discount. Which one is a better bargain, a discount of K 500 (ZMW) or 10%? • A discount of K 500 • They are the same • A 10% discount Question 6. Which of the following statements best describes the primary purpose of insurance products? • To accumulate savings • To protect against risks • To make payments or send money • Other Question 7. Suppose you have money to invest. Is it safer to buy stocks of just one company or to buy stocks of many companies? • Buy stocks of one company • Buy stocks of many companies. Source: WBG Financial Capability Survey, Zambia 2016. 33 The survey results show that, on average, respondents were able to correctly answer 3.7 out of the 7 financial literacy questions. Figure 16 reveals that very few (0.6 percent) had correct responses to either none or all of the questions. 53 percent of Zambian adults were able to provide between 3 and 4 correct answers, with the median being 4 correct answers (30.7 percent). 21 and 8 percent of the respondents were able to answer 5 and 6 correct questions respectively. Figure 16. Financial Literacy Distribution Source: WBG Financial Capability Survey, Zambia 2016. Adults in Zambia are able to perform simple numerical calculations, yet most of them struggle to solve financial numeracy tasks and identify better bargains. As demonstrated in Figure 17, 91 percent of adults were able to perform simple divisions. Moreover, about 60 to 65 percent of respondents understood the concept of inflation and were familiar with the purpose of insurance, but for the concept of risk diversification, the answers were split more or less evenly between right and wrong answers. 66 percent of adults were unable to identify better bargains and 72 percent and 54 percent could not perform compound interest and simple interest calculations, respectively. Figure 17. Financial Literacy Quiz Overview Source: WBG Financial Capability Survey, Zambia 2016. 34 Adults from the lowest income quartile and rural areas performed the worst on the quiz. As shown in Figure 18, 91 percent of respondents who obtained a low score (0 to 2 correct answers) came from rural areas. Furthermore, 67 percent of adults registering a low score were from the first income quartile compared to 2 per cent from the fourth quartile. 59 percent of people who had a high score (5 to 7 correct answers) live in urban areas, and 48 percent of respondents of the same group are from the fourth income quartile compared to 21 percent from the first quartile. Figure 18. Low (0 to 2), Medium (3 to 4) or High (5 to 7) Financial Literacy Scores by Income and Education Level Area Income Level Source: WBG Financial Capability Survey, Zambia 2016. An international comparison of respondents in 23 countries confirms that Zambians fall below the international average for interest rate calculations. As shown in Table 5, Zambia fares comparatively well in terms of understanding inflation and simple division, as the national average is higher than that of all 23 countries. However, the opposite applies to the calculation of both simple and compound interest. 35 Table 5.Cross-country Comparison of Different Financial Literacy Scores Simple Compound Simple Country Year Inflation Interest Interest Division Albania 2011 61 40 10 89 Armenia 2010 83 53 18 86 Azerbaijan 2015 67 35 46 90 Colombia 2012 69 19 26 86 Czech Rep. 2010 80 60 32 93 Estonia 2010 86 64 31 93 Germany 2010 61 64 47 84 Hungary 2010 78 61 46 96 Ireland 2010 58 76 29 93 Lebanon 2012 69 66 23 88 Malaysia 2010 62 54 30 93 Mexico 2012 55 30 31 80 Mongolia 2012 39 69 58 97 Morocco 2012 43 50 31 90 Mozambique 2013 28 78 28 93 Philippines 2014 49 51 29 77 Peru 2010 63 40 14 90 Poland 2010 77 60 27 91 Senegal 2015 47 45 28 92 South Africa 2010 49 44 21 79 Turkey 2012 46 28 18 84 Uruguay 2012 82 50 N/A 86 Zambia 2016 65 46 28 91 Average 2010-2016 62 51 30 88 Source: WBG Financial Capability Survey, Zambia 2016. Financial awareness, as reported by the respondents themselves, gave mixed results. Inflation, shares, collective investment schemes, and dividends have the lowest awareness levels, while interest and exchange rate have the highest levels. As can be seen in Figure 19, more than 60 percent of respondents have never heard about inflation, shares, collective investment schemes, and dividends. Less than 23 percent report that they know the meaning of these terms. 97 and 72 percent of people have heard about and report knowing the meaning of interest and exchange rates, respectively. 44 percent of adults have never heard about insurance and 18 percent have heard about it but do not know the meaning. 36 Figure 19. Awareness on Financial Concepts and Products Source: WBG Financial Capability Survey, Zambia 2016. There is a strong discrepancy between self-reported financial knowledge (literacy) and actual proficiency as measured by the quiz, especially for inflation and interest. As shown in Figure 19, 52 percent of the respondents claimed to have understood the meaning of interest rates yet gave wrong answers in the quiz on this topic. Furthermore, 50 percent of the adults who said they did not know the meaning of inflation, answered correctly in the quiz on this concept. Figure 20. Reported vs. Actual Financial Literacy Source: WBG Financial Capability Survey, Zambia 2016. 37 Box 2. Debt Level and Financial Knowledge Survey results further suggest that adults with high levels of debt lack specific financial knowledge. The average financial literacy score of Zambian adults with a debt higher than their yearly income is lower than adults with a low level of indebtedness (less than one month of income) or those who do not have any debt at all, a difference that remains statistically significant even after controlling for other demographic and socioeconomic factors. As Figure 21 shows, Zambian adults with relatively high indebtedness are much less likely to have a basic understanding of simple and compound interest rates. Specifically, the proportion of correct answers about simple interest is between 6 and 11 percent lower for indebted adults. This difference is between 5 and 7 percent with regards to compound interest. This knowledge gap makes high indebted populations more vulnerable to economic shocks, such as interest rate increases or inflation periods, and ultimately adversely affects their ability to repay their outstanding debts. 17 percent of Zambian adults have borrowed up to their limit or above what they can really afford. While nine percent of Zambian adults are obliged to repay money and are unable to borrow more, eight percent of the population has already borrowed more than they can really afford. Sixty percent of respondents have a debt between two and twelve months of income and 37 percent of them have a debt higher than their yearly income. Specifically, adults living in rural areas who did not save when they were children are significantly more susceptible to borrow up to their limit or above it (see Figure 21). Figure 21. Characteristics of Indebted Zambian Households Financial Literacy Results by Approximate Household Characterization of Zambian Adults Who Borrow to Debt Measured in Number of Monthly Incomes Their Limit or More Source: WBG Financial Capability Survey, Zambia 2016. 38 2.2 Knowledge of Financial Products In order to assess respondents’ level of awareness of financial products, the financial capability survey asked about their familiarity with financial products offered by different types of formal and informal providers. In particular, survey participants were asked if they were familiar with products offered by banks, national saving and credit institutions, micro finance institutions (MFIs), insurance companies, money changers, money transfer operators (MTOs), brokerage houses, unit trusts and e-money agents. A financial products awareness index was constructed based on the number of financial products known to survey participants. This index ranges from 0 to 9, where 0 indicates respondents who are not familiar with any of these products and 9 represents familiarity with all of them. Respondents are, on average, familiar with financial products offered 4.1 different types of providers. Almost all respondents are aware of banks and saving/credit institutions and a high proportion know about MTOs and e-money agents. As can be seen in Figure 22 and Figure 23, only 0.8 percent of respondents know fewer than 2 types of financial products providers and 1.5 percent were familiar with more than 6. The median of the distribution was found to be 4 providers (35.1 percent). Moreover, respondents were mainly familiar with banks, national savings and credit institutions (99 percent), money transfer services (90 percent), e-money agents (76 percent) and money changers (64 percent). Figure 22. Distribution of Financial Product Awareness Scores Source: WBG Financial Capability Survey, Zambia 2016. 39 Figure 23. Overview of Financial Product Awareness by Financial Institutions Source: WBG Financial Capability Survey, Zambia 2016. Those who know the most numbers of providers predominantly come from urban areas and are members of the highest income quartile. As Figure 24 shows, adults from the fourth income quartile, compared with the first, know more about insurance companies (29 vs. 8 percent), money changers (75 vs. 54 percent) and e-money agents (88 vs. 63 percent). For MTOs, that difference is 7 percentage points. The difference in awareness of insurance companies, money changers, and e-money agents between urban and rural households is around 17 percentage points. These differences remain highly significant as regression analysis shows (see Table 17). Figure 24. Fraction of Zambians who Know About Financial Products of Different Providers by Urban/Rural and Income 40 Note: FKA (Average financial knowledge score). Source: WBG Financial Capability Survey, Zambia 2016. Better financial knowledge of products and services is correlated with regular consumption of different types of media. As regression analysis in Table 17 shows and Figure 23 illustrates, Zambian adults who try to stay informed by using different types of media tend to be more familiar with financial products than adults who do not use media. Banks and MTO services are the exception to this tendency because the knowledge is similar among users and non-media users. To understand media usage of Zambian adults, Box 3 presents a consumption overview. Figure 25. Fraction of Zambians who Know About Financial Products of Different Providers by Urban/Rural and Income Note: FKA (Average financial knowledge score). Source: WBG Financial Capability Survey, Zambia 2016. 41 Box 3. Media Consumption Overview Three out of four adults in Zambia have a mobile phone and less than one out of four uses the Internet or reads the newspaper, 39 percent own a TV, and 60 percent listen to the radio. As shown in Figure 26, media penetration was found to be higher among men, urban dwellers, and the rich. The difference between high income earners and their low-income counterparts regarding mobile phone and Internet usage were reported to be 12 and 11 percent respectively. Between adults living in rural and urban areas, such variances were found to be 12 and 16 percent respectively. Figure 26. Media Consumption by Social and Demographic Groups Source: WBG Financial Capability Survey, Zambia 2016. Media consumption index refers to the number of media sources regularly used by respondents. 42 2.3 Financial Behavior and Attitudes Even if people possess knowledge of basic financial concepts and products they may struggle to translate this knowledge into action. To identify the role that attitudes play in shaping individuals' financial decisions and to see whether, and if so how, attitudes translate into financial behavior, the survey asks questions about different aspects (components) of financial capability that include attitudes, motivations, and behaviors. This chapter gives an overview of strengths and areas for improvements shown by surveyed Zambians regarding relevant financial behavior and attitudes. In the Zambia data set, 8 main components of financial capability can be identified, some of which refer to behavior and others to attitudes or motivations. The Financial Capability and Inclusion Survey in Zambia recorded different financial attitudes, motivations, and behavior through diverse qualitative questions with various measurement levels (nominal and ordinal). To identify the main components of financial capability in Zambia, a statistical procedure was applied to simultaneously quantify categorical variables while reducing the variance of the data. This procedure known as Principal Components Analysis (PCA) reduces the original set of variables to a smaller uncorrelated set of variables (principal components) which aim to account for as much of the variance in the data as possible. The PCA method39 provides a single indicator (or score) for each component. The scores range between 0 (lowest score) and 100 (highest score). Table 6 presents the relevant attitudes that define each component. Table 6. Main Identified Financial Components from PCA Analysis Component or Dimension Topic 1 Controlled budgeting Whether makes a money plan and how often Whether makes a money plan and precision of plan Whether makes a plan and how frequently sticks to the plan 2 Living within one’s means Whether runs short of money and why Whether borrows money to buy food and how often 3 Planning for unexpected expenses Whether could cover unexpected expense tomorrow (or has done something or thought about it) Whether worries about covering unexpected expense tomorrow 4 Saving capacity Whether has money left over and how often Whether has money left over and how the money is used 5 Planning for old age expenses Whether has a strategy for covering old age expenses that provides/will provide full coverage Whether has any strategies in place for covering old age expenses or is worried about covering these expenses 39 The PCA analysis performed in Zambia has focused on 8 main components (or dimensions) that account for 65 percent of the total variance. Other dimensions were ignored because of their lower contribution to total variance. Principal components having eigenvalues greater than one were also prioritized. 43 Component or Dimension Topic 6 Responsibility / Responsible behavior Whether knows amount available for spending and how precisely Whether the following statement describes him/her - I try to save Whether agrees with motivation statement/ Impulsiveness/ I am impulsive 7 Self-discipline Whether/how often buys unessential items Whether agrees that statement describes him/her – I am financially disciplined Whether agrees with motivation statement/ Time preference/Live for the present 8 Choosing financial products Whether considers many alternatives before respondent decides which product to get Whether searches until respondent finds the best product for his/her needs Whether checks the detailed terms and conditions of the product Source: WBG Financial Capability Survey, Zambia 2016. Compared to other aspects of financial capability, survey participants show strengths in areas related to living within one’s means and planning for the unexpected. The biggest weakness was found to be saving capacity. Figure 27 shows that the highest level of strength is “living within one’s means” with a score of 87 percent. The second highest score was found to be “planning for the unexpected” at 67 percent. Figure 27. Average Financial Capability Scores Source: WBG Financial Capability Survey, Zambia 2016. The weakest link in the chain is in terms of “saving capacity” (24 percent), a component that is key for governments that would like to extend the coverage of contributory social protection policies. This low score captures the fact that only about a fourth of respondents have money left after paying for food and essential items. 44 Multivariate analysis allows examination of characteristics that are associated with the capacity to save after controlling for numerous individual and contextual factors. Figure 28 shows the correlates of reporting the fact of having a capacity to put money aside. Having a stable income is more important than having a high income. Informal and self-employed workers are less likely to be able to put money aside, compared to formally salaried individuals. Having high financial literacy (specifically, correctly answering the hardest questions, such as the ones on investment diversification) is also associated with having higher saving capacity. Another characteristic of potential savers is that they are more likely to use a mobile phone. Fewer potential savers reside in poor, rural areas that are far from schools or banks. Figure 28. Correlates of Having Saving Capacity40 Source: WBG Financial Capability Survey, Zambia 2016. Other behavioral attributes scored between 42 and 51 percent, slightly below average with controlled budgeting on the top of this range and responsibility at the lower end. The survey went into greater depth by analyzing all topics associated with each component or dimension. Box 4 and Box 5 present the findings for each component. 40 The marginal correlations are obtained from a linear regression model of a dummy variable for having money left after spending on essentials on age, schooling, gender, marital status, income, employment, financial literacy score, and characteristics of the place of residence. 45 Box 4. Topics Associated with each Component or Dimension (I) Living within one’s means. A majority of Zambians do not run short of money nor do they borrow money to purchase essential items. When people run out of money, it is because they overspend. The survey results show that 72 percent of adults do not as a habit deplete their funds, but when they do, it is because they overspend (19 percent). Finally, 92 percent of Zambians do not borrow money to buy food or other essential items. The result previously exposed that 72 percent of Zambian adults have enough money to meet their food and other essential needs is consistent with the fact that the majority of the Zambian population (93 percent) eats at least two meals per day. In particular, 52 percent eats 3 meals, 41 percent 2 meals and only 3.7 percent one meal (Central Statistical Office, 2015). It is also in line with 2015 Finscope results that found for a similar question that 74.3 percent of adults, do not continuously struggle to keep up with regular expenses. On the other hand, the 2016 FCCP survey indicates that less than 30 percent of Zambian adults don’t have enough money to meet their food and other essential needs, illustrating that a lot has to be done to address the needs of the bottom of the pyramid in Zambia. This result is also consistent with the observations of the 2015 Finscope survey, that indicated that 25.7 percent of adults continuous struggle to keep up with regular expenses. Planning for unexpected expenses. Most adults were able to do something to meet unexpected expenses, but those who could not cover them in full were very concerned. 25 percent of Zambians could cover unexpected major expenses in full without borrowing money. 57 percent of adults would not be able to cover unexpected expenses tomorrow in full but had implemented strategies to do so without borrowing money. 77 percent of the sampled population who could not meet unexpected expenses in full worried greatly about this situation. Controlled budgeting. Although most respondents plan how the money will be used, the sample was evenly distributed between those who do and those who do not stick to a budget. According to the survey results, 69 percent of adults plan the way in which their money will be used (51 percent always plan, 18 percent sometimes plan). Moreover, about half of Zambians adhere to their planned budget (36 percent always and 13 percent sometimes). 21 percent of respondents never maintain a budget. Planning for old age expenses. Zambians are evenly split between those who do and those who do not have a strategy in place for covering old age expenses. Most adults with a strategy do not have full coverage. 49 percent of adults have strategies for covering old age expenses, and, among those who do, 73 percent do not yet have full coverage. 65 percent of respondents without a strategy mentioned that they are worried about having no provisions for old age (45 percent very worried and 20 percent a bit worried). Finally, only 6.3 percent of adults currently have private pension products (personally or jointly). Self-discipline. About half of Zambians regularly buy unessential items, 62 percent lack purchasing discipline, and 52 percent claim they live only in the present. The survey results show that 63 percent of adults buy unessential items (47 percent regularly and 16 percent sometimes). Furthermore, 62 percent of respondents do not consider themselves disciplined. 52 percent of Zambians consider they live more on a daily basis, and do not plan for tomorrow. Choosing financial products. The majority of Zambians neither consider alternatives nor check the detailed terms and conditions before obtaining a financial product. The survey results demonstrate that 77 percent of respondents do not consider many alternatives before deciding which product to get or search until they find the best product for their needs. Such respondents do not check the detailed terms and conditions of the products before purchasing them. 46 Box 5. Topics Associated with each Component or Dimension (II) Responsibility. Most adults are aware of the amount of money available for daily spending and 75 percent do not try to save. More detailed findings show that 71 percent of adults report they know how much money they have available for day-to-day spending (54 percent exactly and 17 percent roughly). However, 75 percent of respondents say they do not try to save. 51 percent of Zambians consider themselves impulsive. Saving capacity. Most Zambians do not have money left over after paying for essential items. However, more than 95 percent of adults who have excess funds either save or spend them on necessities. 74 percent of Zambians do not have additional money after having paid for essential items, and only 19 percent regularly have anything left over, and only 7 percent sometimes. Financial capability scores of 15 different countries show that Zambia compares favorably in terms of living within one’s means (best score) and planning for the unexpected; however, it fares poorly for choosing financial products, controlled budgeting and planning for old age. As shown in Table 7, Zambia scores 12, 10, and 8 percent less than the average for choosing financial products, controlled budgeting and planning for old age expenses, respectively. However, Zambia scores better for living within one’s means by 13 percent and planning for unexpected expenses by 3 percent. Furthermore, it should be noted that Zambia has the highest score of all 15 countries in terms of living within one’s means. Table 7. Cross-country Comparison of Different Financial Capability Scores Planning Planning for Choosing Controlled for Living within old age financial Country budgeting unexpected one’s means expenses products expenses Armenia 74 64 68 100 59 Azerbaijan 35 N/A N/A 21 59 Colombia 80 59 75 67 57 Lebanon 40 73 82 71 63 Mexico 52 64 78 65 59 Mongolia 65 N/A 84 N/A 49 Mozambique 74 45 N/A 40 34 Morocco 38 67 57 6 89 Nigeria 78 71 82 N/A N/A Philippines 44 67 43 29 51 Senegal 66 N/A 73 70 20 Tajikistan 81 N/A 83 N/A N/A Turkey 60 68 68 72 52 Uruguay 71 55 81 60 N/A Zambia 51 67 87 46 43 Average 61 64 74 54 55 Source: WBG Financial Capability Survey, Zambia 2016. In-depth analysis suggests that urban adults obtain higher financial capability scores than their rural counterparts, except in the area of controlled budgeting. The same results apply to the richest and poorest segments of the population. Figure 29 indicates that respondents from urban areas averaged scores between 3 and 15 more points than those from rural sections in all topics except controlled budgeting. Moreover, respondents from the fourth income quartile averaged scores between 5 and 18 points higher than those from the first quartile in all topics except controlled budgeting. 47 Figure 29. Average Financial Capability Scores by Urban/Rural and Income Level Source: WBG Financial Capability Survey, Zambia 2016. Adults with low financial literacy have worse financial capability scores than all others except in the area of controlled budgeting, as presented in Figure 30. Box 6 examines how Zambians with low financial capability might fail to accurately evaluate their future sources of support.41 41 A priori, the patterns documented in Box 6 could also reflect permanent differences between younger and older cohorts. However, in this case, the discrepancy in expected vs. actual family support would likely go in the opposite direction. The differences by financial literacy scores also point towards anticipation/planning errors rather than cohort effects, as well as the fact that age profiles in expected sources of old age support exhibit breaks in old age instead of smooth trends. 48 Figure 30. Average Financial Capability Scores by Financial Literacy Level Source: WBG Financial Capability Survey, Zambia 2016. Adults who are not using any type of media tend to have lower financial capability scores than those who do, except when it comes to self-discipline and planning for old age expenses, as shown in Figure 31. Respondents who do not use any kind of media averaged scores between 2 and 8 points less than those of others in all topics except self-discipline and planning for old age. Figure 31. Average Financial Capability Scores by Media Source: WBG Financial Capability Survey, Zambia 2016. Adults who saved as children outperformed others in almost every financial capability topic, especially planning for the unexpected. As can be seen in Figure 32, respondents who saved as children all scored 100 in planning for the unexpected, which represents an average of 39 points more than the score of others. Furthermore, respondents who saved as children averaged scores between 4 and 9 points higher than that of others with respect to saving capacity, planning for old age, living within one’s means and responsibility. On the remaining topics (self-discipline, choosing financial products, and controlled budgeting), adults who did not save as children scored between 1 and 5 points higher. 49 Figure 32. Average Financial Capability Scores by Child Saving Behavior Source: WBG Financial Capability Survey, Zambia 2016. 50 Box 6. Planning for Old Age and Financial Literacy Zambians are very limited in their capacity to plan for old age when compared to other countries where this score is available. 15.7 percent of survey respondents under the age of 60 report they have not thought about how to meet their expenses in old age and only 25.7 percent expect their income sources to be sufficient. In addition, Zambians might fail to accurately evaluate their future sources of support, particularly among individuals with low financial literacy. The survey data can be used to compare the sources of income that working- age respondents expect to rely on, with the sources of income that old Zambians actually rely on. There are significant discrepancies between the two: the young appear to overestimate the availability of family support and to underestimate the degree to which they will have to work past retirement age. Figure 33. Expected Sources of Economic Support in Old Age Source: WBG Financial Capability Survey, Zambia 2016. The discrepancies are much larger for individuals with low financial literacy who are more likely to incorrectly predict the income sources they will be able to rely on (see Figure 33). For example, 11 percent of young respondents with low financial literacy expect to have to work in old age, but 30 percent of old respondents actually do. The proportion of young respondents with low financial literacy who expect to rely on their family members and on savings are 17.5 percent and 14 percent, respectively. The corresponding numbers for older respondents are only 9 percent and 6 percent. By contrast, individuals with high financial literacy exhibit much smaller discrepancies in identifying actual and future income sources. 51 Box 7. Knowledge about Regulatory Financial Institutions (I) Zambians were found to be familiar with regulatory financial institutions (except the SEC), but fail to grasp the full extent of their mandates. As shown in Figure 35, 92 percent of adults are familiar with the BoZ and only 7 percent could define exactly its mandate. BoZ awareness levels vary significantly between provinces. While less than 4 percent of Zambian adults living in Luapula or Western identifies the BoZ’s mandate, the awareness level increases by about 8 points for those who live in North Western or Central. On the other hand, as Figure 35 illustrates (see Box 8), 73 percent of respondents are unfamiliar with the SEC and only 8 percent could accurately identify its mandate. Finally, familiarity with the PIA is more or less evenly split, but only 12 percent have full knowledge of its mandate. Figure 34. Knowledge about Regulatory Financial Institutions (BoZ) Awareness level of BoZ by provinces Note: R (right answer) and W (wrong answer). About the BoZ’s mandate: (Question 1) Lending to Zambian farmers (W). (Question 2) To ensure appropriate monetary policy formulation and implementation (R). (Question 3) To act as a fiscal agent of the government (R). Source: WBG Financial Capability Survey, Zambia 2016. 52 Box 8. Knowledge about Regulatory Financial Institutions (II) Figure 35. Knowledge about Regulatory Financial Institutions (PIA and SEC) Note: R (right answer) and W (wrong answer). About the PIA’s mandate: (Question 1) Protection of pension scheme members and insurance policy holders (R). (Question 2) Regulate the conduct of pensions and insurance industry (R). (Question 3) Offer loans to finance agricultural projects (W). About the SEC’s mandate: (Question 1) Responsible for the supervision and development of Zambian capital markets (R). (Question 2) Promote insurance products to the elders (W). (Question 3) Registration and authorization of financial intermediaries (R). Source: WBG Financial Capability Survey, Zambia 2016. 3 Relationship Between Financial Inclusion and Financial Capability There is little doubt that financial capability and financial inclusion influence each other. While lack of knowledge about financial products may hinder their use, it is likely that as people begin using financial services, they become more familiarized with and knowledgeable about them through “learning by doing.” While disentangling a causal link between financial inclusion and financial capability is beyond the scope of this report, this chapter presents an overview of who the financially excluded in Zambia are and how their financial knowledge, attitudes, and behaviors compare to financially included segments of the population. 3.1 Financial Literacy and Financial Inclusion A lack of financial literacy is usually cited as an explanation for the limited demand for financial services in developing countries. If people do not understand financial concepts and lack basic numeracy skills, they may not feel comfortable in choosing financial products and hence will not demand them or, perhaps of even greater concern, will choose products that do not meet their needs or use them inappropriately. For instance, in a study in India and Indonesia, Cole et al. (2009) found financial literacy to be an important factor in determining the demand for financial products, especially among uneducated and financially illiterate segments of the population. 53 Zambians with low financial literacy tend to be less financially included and utilize more informal products than other respondents. As Figure 36 shows, there are 6 percent fewer adults with a financial literacy index less than 4 that are financially included than excluded, and 10 percent more adults with a financial literacy index greater than 4 that are included than excluded. Moreover, there are 24 percent more adults with a literacy index score less than 4 who use only informal financial products compared to those utilizing only formal ones, and 15 percent more adults with a literacy index score greater than 4 who use only formal products than those utilizing only informal ones. Figure 36. Distribution of Financial Literacy Score by Formal/Informal Financial Products and Services Ownership Financial Inclusion Type of Products Source: WBG Financial Capability Survey, Zambia 2016. 54 3.2 Knowledge about Financial Products and Financial Inclusion Studies in various settings have also found that enhanced financial awareness may in turn lead to higher product up-take. In the U.S., for instance, information about a retirement plan was randomly provided to a group of university employees. Workers who received the information were substantially more likely to enroll in the retirement plan than those who did not obtain the information, suggesting that individuals are more likely to use a financial product once they learn about it and its benefits (Duflo and Saez, 2003). In a similar vein, Giné et al. (2011) found that in rural India lack of understanding of insurance products is the second most stated reason for households not to purchase rainfall insurance. A lack of awareness can prevent people from using financial products that could potentially benefit them. As detailed in section 1.4, most financially excluded Zambians (63 percent) state they do not have formal accounts because they lack the money to maintain the accounts, because financial fees are too high or because financial institutions are too far away. About 15 percent of Zambian adults report that they do not trust them, initially suggesting that barriers related to lack of knowledge about financial products are not substantial for the majority of Zambian adults. However, when analyzing how informed Zambian adults without formal accounts feel about services of various financial providers, their awareness level appears to be low. Using the financial product awareness index discussed in section 2.2, and categorizing respondents into five groups according to the number of financial services they know, Figure 37 suggests low awareness levels even among non-formal account users who state reasons not related to financial awareness barriers. Figure 37. Distribution of Financial Product Awareness Score by Reasons for not having a Formal Account Source: WBG Financial Capability Survey, Zambia 2016. There is a strong correlation between financial inclusion and product awareness. There is also a strong correlation between product awareness and the degree of formality in financial products being utilized. Regression analysis suggests that even after controlling for socioeconomic and demographic characteristics of Zambian adults, awareness of financial products and the likelihood of owning a formal account are strongly linked (see Table 22). These correlations are shown in Figure 38. There are 13 percent more adults with a product awareness score less than 4 who are financially excluded than included, and 14 percent more adults with a product awareness score greater than 4 who are financially included than excluded. There are 28 percent more adults with a product awareness score less than 4 who only use informal 55 products than those who only use formal ones and 28 percent more adults with a product awareness score greater than 4 who only use formal products than those who only use informal ones. Figure 38. Distribution of Financial Product Awareness Score by Formal/Informal Financial Products and Services Ownership Financial Inclusion Type of Products Source: WBG Financial Capability Survey, Zambia 2016. Financially included individuals tend to be more aware about products than those who are excluded across the whole spectrum of financial services providers. As Figure 36 shows, there are 10, 8, 5, 4, 3, and 2 percent more financially included adults who are aware of e-money agents, MFIs, money changers, MTOs, insurance companies or unit trusts, brokerage houses or banks, and national saving and credit institutions, respectively, compared with financially excluded adults. 56 Figure 39. Financial Product Awareness by Financial Inclusion and Services Ownership Source: WBG Financial Capability Survey, Zambia 2016. 3.3 Financial Attitudes/Behavior and Financial Inclusion Attitudes and behaviors are another relevant dimension when analyzing financial inclusion. In developed and developing countries, households and firms are frequently excluded from accessing financial products because of inadequate credit history, irresponsible financial behavior, or poor business and accounting records. Eight main components of financial capability related to financial attitudes, motivations, and behaviors were assessed in the survey. There are no substantial differences in the financial behavior and attitudes of financially included and financially excluded respondents. Using the same financial capability scores described in section 2.3, Figure 40 shows that slight differences arise between Zambians with a formal account and those without in terms of their financial attitudes and behaviors. The most striking difference is in terms of saving capacity, where financially excluded adults are 3 points behind financially included ones. 57 Figure 40. Distribution of Financial Attitudes and Behaviors by Financial Inclusion Source: WBG Financial Capability Survey, Zambia 2016. Box 9. ‘Running Short of Money’ Behavior and Financial Inclusion Survey results suggest that adults who don’t run short of money for food or other necessary items tend to be slightly more financially included than those who regularly or sporadically run short of money. As Figure 41 presents, while about 41 percent of those who don’t run shot of money own an account in a formal financial institution, this index decreases 2 percent among those who declare having this behavior. On the other hand, the general overview of financial product usage (see also Figure 41) shows that adults who don’t have enough funds for buying food use more informal credit and MFI credit (only a difference of 1 percent) compared to Zambian adults who have funds for covering their basic necessities. This last group comparatively uses more money transfers services, bank and e-money accounts. In terms of bank credit and insurance products, their usage levels are similar. Figure 41. Usage of Financial Products by ‘Running Short of Money’ Behavior Source: WBG Financial Capability Survey, Zambia 2016. 58 4 Financial Consumer Protection In addition to people’s ability to make sound financial decisions, the latest global financial crisis has highlighted the importance of financial consumer protection in safeguarding consumers from abusive sales practices and to level the playing field between providers and consumers of financial services. Financial consumer protection is about ensuring fair interaction between providers and consumers of financial services. An effective financial consumer protection regime is essential in counterbalancing the inherent disadvantage of consumers vis-à-vis the power, information, and resources of providers. Without basic protective measures, consumers may find it difficult or costly to obtain sufficient information, and even those who are financially literate may not be able to adequately understand the financial products they use or are considering to use. Financial consumer protection is necessary to ensure stable financial markets in Zambia while ensuring that expanded access benefits consumers and the overall economy. As outlined in section 1.1, a number of initiatives are planned or already underway to increase financial sector outreach to formally excluded populations. Increased access to finance can result in substantial positive effects, both on the macro and individual levels. However, it can be detrimental if inexperienced consumers are not protected against fraud or unfair business practices. Effective financial consumer protection frameworks can help to instill trust in the formal financial system. A high incidence of conflicts with financial services providers or low levels of satisfaction with financial products used could undermine the trust in the formal financial system. As well as making existing consumers worse off, it can also discourage potential new consumers from entering the market. This chapter assesses the effectiveness of the current financial consumer protection regime from a demand-side perspective, with a focus on consumers’ satisfaction with financial products and services and their experience of handling disputes and seeking redress. In order to measure whether products are effectively meeting the needs of financially included Zambian adults, the financial capability survey sought to capture the overall satisfaction of consumers with the nine most common types of providers and their products and services. To examine the effectiveness of existing consumer redress mechanisms, this survey also asked users of financial services to share their experiences with current internal and external redress mechanisms, and identified segments of the population that are more likely to have encountered a dispute with a financial services provider in the past three years. 59 4.1 Consumers’ Satisfaction with Financial Products In general, users of financial services express satisfaction with the services offered by financial service providers, especially MTOs and insurance companies. Figure 42 provides a more detailed picture. Consumers are least satisfied with banks, national savings, or credit institutions than most other types of financial institutions, although the satisfaction level is still 79 percent. Insurance products and money transfer services have the highest satisfaction rates from consumers, with an approval rating of 91 and 92 percent, respectively. Among those who ever used banks, national savings or credit institutions, low income groups and young adults (less than 35 years old) are less satisfied with their products than other adults. Significant differences also exist in satisfaction levels between different regions with services provided by banks, national savings, or credit institutions. Figure 42. Clients’ Satisfaction with Services Provided by Common Types of Financial Institutions Source: WBG Financial Capability Survey, Zambia 2016. Young adults and low income individuals tend to be less satisfied with services provided by commercial and postal banks. Figure 43 shows that the satisfaction rate for adults under 35 years of age averages 78 percent, which is less than that of people aged between 35 and 54 (80 percent) or aged over 54 (79 percent), and that the satisfaction level for the poorest population (76 percent) is lower than for the richest one (79 percent). Figure 43. Clients’ Satisfaction with Services Provided by Commercial or Postal Banks Source: WBG Financial Capability Survey, Zambia 2016. 60 Historically, the use of banks and national savings or credit institution has been more or less at the same levels across the various regions of Zambia. Map 5 demonstrates that the historical usage rate varies between about 90 and 95 percent across all regions. Provinces with the highest historical usage include Copperbelt and Lusaka. Provinces with the lowest historical usage are Luapula and North Western. Map 5. Historical Usage of Banks, National Saving and Credit Institutions by Region (%) Source: WBG Financial Capability Survey, Zambia 2016. Clients’ satisfaction with banks and national saving and credit institutions does not vary much between regions. As drawn in Map 6, clients’ satisfaction rate is between 75 and about 81 percent across all provinces. Copperbelt and Western were found to have the highest satisfaction level. Central and Southern have the lowest satisfaction rates. 61 Map 6. Clients’ Satisfaction with Banks, National Savings or Credit Institutions by Province (%) Source: WBG Financial Capability Survey, Zambia 2016. 4.2 Consumers’ Approaches in Dealing with Provider Conflicts Around 13 percent of adults encountered a conflict with a financial services provider, but only 25 percent of this group tried to resolve it. As shown in Figure 44, respondents who encountered conflicts (13 percent of respondents) tried to resolve these in one out of four cases. Among people who did not encounter a dispute (87 percent), a higher proportion (38 percent) said that, if they were to have one, they would try to solve it. 62 Figure 44. Approaches in Dealing with Financial Services Provider Conflicts Source: WBG Financial Capability Survey, Zambia 2016. In-depth analysis of socio-demographic factors has shown that more men than women, and fewer young adults than older adults, have had a dispute with a financial services provider. Figure 42 shows that 4 percent more men than women (by 4 percent) have had a dispute with a financial services provider. Also, 2 percent fewer young adults experienced conflicts with such institutions. Figure 45. Overview of Disputes by Social and Demographics Factors Source: WBG Financial Capability Survey, Zambia 2016. There is a wide regional disparity in terms of disputes with financial providers, with North Western and Eastern registering the highest levels and Central and Northern & Muchinga the lowest levels, as shown in Map 7. North Western and Eastern are the regions with the highest proportion of conflicts with financial institutions (15.3 to 17.4 percent) and Central and Northern & Muchinga have the lowest ratio of disputes with providers (10.8 to 11.3 percent). 63 Map 7. Regional Overview of Disputes with Financial Providers (%) Source: WBG Financial Capability Survey, Zambia 2016. The most frequent action taken by adults who tried to solve their dispute with a financial services provider was to stop using the service before the contract ended. Other measures undertaken, as shown in Figure 43, included submitting a grievance to the provider or a claim to the appropriate government authority. Among adults who tried to resolve a conflict with a provider, stopping use of the service before the contract ended was the main action taken (97 percent). The second most frequent action taken was submitting a grievance to the company that sold the product (41 percent). The third most frequent measure taken was delivering a claim to the appropriate government authority. Figure 46. Action Taken to Redress Conflicts with Financial Service Providers Source: WBG Financial Capability Survey, Zambia 2016. 64 The main cause for inertia by adults who did not try to solve disputes with financial services providers is the lack of awareness of the proper government agency to contact. As Figure 44 shows, the rest of the sampled population believe that financial institutions are too powerful or that government authorities or the law do not function adequately. 85 percent of respondents claimed that they do not know which government agency should be approached to resolve a dispute. 64 percent believe that financial organizations are too powerful and 29 percent mention that government authorities do not function competently. Figure 47. Reasons for Not Solving the Conflicts with Financial Service Providers Source: WBG Financial Capability Survey, Zambia 2016. 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Journal of Consumer Affairs 42.2 (2008): 189-205. • Republic of Zambia, Central Statistical Office. “2015 Living Conditions Monitoring Survey – Key Findings”. • Rodríguez, Catherine, and Juan E. Saavedra. 2015. “Nudging Youth to Develop Savings Habits: Experimental Evidence Using SMS Messages.” CESR-SCHAEFFER Working Paper Series Paper No: 2015-018. • Ruiz, C. 2013. “From Pawn Shops to Banks: The Impact of Formal Credit on Informal Households.” Policy Research Working Paper 6643, World Bank, Washington, DC. • Rustamov, H. Tamerlan, et al. “Non-Bank Payment Service Providers and Financial Inclusion: the Case of Azerbaijan.” The Journal of Qafqaz University on Economics and Administration, 2015 Volume 3, Number 2 (UOT: 336.11). • Stix, Helmut. 2013. “Why Do People Save in Cash? Distrust, Memories of Banking Crisis, Weak Institutions and Dollarization.” Journal of Banking and Finance 37: 4087–106. • World Bank Group. 2014a. “Global Financial Development Report 2014: Financial Inclusion.” Washington, DC: World Bank. • World Bank Group, Bill and Melinda Gates Foundation, Better than Cash Alliance. 2014b. “The Opportunities of Digitizing Payments.” Washington, DC: World Bank. • World Bank Group. 2013a. “Global Financial Development Report 2014: Financial Inclusion.” World Bank, Washington, DC. • World Bank Group. 2013d. “Financial Capability Surveys Around the World: Why Financial Capability is Important and How Surveys can Help.” World Bank, Washington, DC. • World Bank Group and Bank for International Settlements. 2015. Consultative report. “Payment Aspects of Financial Inclusion.” • World Bank’s Report No. 89360 “Azerbaijan Economic Diversification and Growth, Access to Finance: Measure to Ease a Binding Constraint.” September 2013. • World Bank’s “Technical Note on Access to Finance.” November 2015. • Yoko Doi, David McKenzie and Bilal Zia. 2012. “Who You Train Matters: Identifying Complementary Effects of Financial Education on Migrant Households.” World Bank Working Paper No. WPS6157, Washington, DC. • Zimmerman, J., K. Bohling, and S. Rotman Parker. 2014. “Electronic G2P Payments: Evidence from Four Lower-Income Countries.” Focus Note 93, CGAP, Washington, DC. 68 Appendix A. Cross-tabulation of Financial Inclusion Table 8. Financial Inclusion Summary by Social and Demographic Factors Formal Banks, National Saving and Credit Insu- Financial Payment Providers MFIs Institut. Institutions rance Formal account General / Bank Credit E-money MFI owner- Loan Mortgage MTOs personal account card account credit insuran. ship 42 Gender Total 40.2% 35.6% 1.0% 4.5% 4.1% 53.0% 14.7% 3.9% 4.8% Male 43.1% 37.5% 1.4% 4.6% 4.4% 53.0% 17.6% 4.6% 5.0% Female 37.2% 33.6% 0.6% 4.4% 3.8% 53.0% 11.8% 3.2% 4.6% Area Urban 46.1% 39.3% 0.6% 5.4% 3.9% 63.8% 23.1% 2.3% 8.1% Rural 35.5% 32.7% 1.3% 3.9% 4.3% 44.5% 8.2% 5.1% 2.2% Income level First quartile 29.4% 27.6% 0.6% 3.9% 4.2% 44.2% 4.5% 5.4% 1.3% Second 37.3% 33.5% 1.7% 3.9% 3.2% 43.3% 7.9% 4.9% 2.7% quartile Third quartile 39.2% 35.1% 1.2% 2.9% 4.4% 59.2% 16.6% 3.2% 6.5% Fourth quartile 52.5% 44.5% 0.8% 6.3% 4.5% 63.4% 27.1% 2.3% 8.4% Employment Out of labor 37.2% 35.1% 0.0% 0.0% 0.0% 74.4% 12.5% 0.0% 6.1% force Unemployed 39.3% 33.4% 3.6% 3.0% 4.3% 55.8% 15.8% 4.1% 6.7% Formally 38.7% 31.6% 0.4% 1.1% 3.8% 55.0% 17.5% 2.6% 6.4% employed Informally 43.1% 38.1% 0.4% 5.6% 5.0% 55.6% 15.7% 3.5% 4.3% employed Self-employed 37.8% 34.4% 1.3% 4.9% 3.5% 48.2% 13.0% 4.8% 4.5% Retired 62.3% 62.3% 0.0% 0.0% 0.0% 62.3% 0.0% 0.0% 0.0% Level of education No schooling 45.9% 42.5% 2.2% 4.6% 4.6% 56.8% 12.4% 6.5% 5.5% Primary and 37.4% 32.8% 0.9% 3.9% 4.2% 49.9% 13.6% 3.1% 4.5% intermediate Secondary and 44.1% 39.3% 0.9% 5.7% 3.9% 58.0% 17.5% 4.8% 5.2% vocational Tertiary 45.9% 42.5% 2.2% 4.6% 4.6% 56.8% 12.4% 6.5% 5.5% 42 Formal account ownership (“financially included”) is defined in this Zambian financial capability study as the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution (formal credit, mortgage, credit from microfinance organizations or from the decentralized financial system, debit or credit card, formal savings, current or savings accounts), or personally using a mobile money service in the past 12 months. 69 Formal Banks, National Saving and Credit Insu- Financial Payment Providers MFIs Institut. Institutions rance Formal account General / Bank Credit E-money MFI owner- Loan Mortgage MTOs personal account card account credit insuran. ship 42 Household Size 1 to 3 members 35.5% 30.6% 0.6% 4.0% 3.6% 54.2% 13.5% 3.5% 7.2% 4 to 6 members 40.8% 36.5% 1.0% 5.0% 4.2% 54.4% 14.9% 3.7% 4.6% 7 to 9 members 42.1% 37.3% 1.2% 4.3% 4.4% 50.5% 15.2% 4.4% 3.6% Media Consumption 0 media 34.7% 33.7% 2.6% 1.7% 6.4% 42.4% 7.9% 2.4% 2.6% 1 media 38.6% 35.0% 0.7% 3.5% 4.3% 44.3% 11.8% 6.7% 3.4% 2 media 35.9% 33.0% 0.9% 4.0% 4.8% 49.4% 10.2% 3.4% 5.0% 3 media 41.6% 37.2% 1.0% 6.0% 3.1% 57.0% 16.9% 3.2% 4.6% 4 media 49.4% 38.8% 1.2% 4.2% 4.2% 66.0% 23.9% 3.5% 7.1% 5 media 38.5% 32.8% 0.6% 4.4% 3.2% 57.2% 19.7% 2.0% 5.6% 6 media 59.9% 52.4% 0.0% 19.6% 0.8% 83.9% 28.0% 0.0% 7.1% Income Stability Stable income 41.6% 36.4% 0.9% 4.2% 3.7% 59.1% 17.7% 3.5% 5.7% Unstable 38.7% 34.7% 1.1% 4.9% 4.7% 46.5% 11.5% 4.3% 3.9% income Provinces Central 41.7% 38.9% 1.8% 5.0% 2.6% 48.3% 11.6% 6.6% 6.4% Copperbelt 49.4% 43.6% 1.2% 1.9% 6.5% 59.4% 21.9% 2.3% 4.4% Eastern 32.2% 28.6% 0.1% 3.5% 5.1% 49.4% 9.4% 5.0% 3.2% Luapula 32.4% 28.2% 0.7% 3.4% 3.3% 43.7% 8.5% 4.1% 4.4% Lusaka 50.3% 41.7% 0.7% 6.9% 2.4% 62.4% 26.4% 1.7% 9.2% Muchinga 36.5% 32.8% 0.0% 5.1% 6.8% 51.4% 9.9% 5.7% 1.2% Northern 34.1% 30.2% 0.5% 4.0% 2.3% 50.8% 10.7% 4.8% 2.5% North Western 37.8% 34.8% 0.0% 7.0% 8.7% 53.2% 17.2% 4.7% 7.4% Southern 37.4% 34.1% 3.1% 4.2% 3.1% 48.9% 9.3% 3.2% 2.9% Western 31.7% 31.1% 0.5% 5.2% 3.7% 46.4% 4.4% 6.0% 2.6% Source: WBG Financial Capability Survey, Zambia 2016. 70 B. Background on Zambian Financial Survey Figure 49. Estimated Population Break-down by Urban/Rural Source: WBG Financial Capability Survey, Zambia 2016. Figure 50. Estimated Population Break-down by Province Source: WBG Financial Capability Survey, Zambia 2016. 71 Figure 51. Estimated Population Break-down by Gender Source: WBG Financial Capability Survey, Zambia 2016. Figure 52. Estimated Population Break-down by Age Groups Source: WBG Financial Capability Survey, Zambia 2016. Figure 53. Estimated Population Break-down by Household Size Source: WBG Financial Capability Survey, Zambia 2016. 72 Figure 54. Estimated Population Break-down by Education Groups Note: “Other education” includes adults that report vocational education (n = 7, 0.3 percent) and university education (n = 2, 0.1 percent). Source: WBG Financial Capability Survey, Zambia 2016. Figure 55. Estimated Population Break-down by Stable/Unstable Income Groups Source: WBG Financial Capability Survey, Zambia 2016. Figure 56. Estimated Population Break-down by Different Income Groups Source: WBG Financial Capability Survey, Zambia 2016. 73 C. Regression Tables Chapter 1. Financial Inclusion Table 9. Financial Inclusion by Social and Demographic Factors Financial Inclusion Variables in the Equation Coefficient Age 0.0033 * (0.0019) Male 0.1305 ** (0.0643) No schooling as the baseline Primary, special and informal -0.2646 ** (0.1142) Secondary, vocational and tertiary -0.1270 (0.1422) Read/write in English or another language 0.0262 (0.0724) HH Head 0.0230 (0.0621) First quartile as the baseline Second quartile 0.2628 *** (0.078) Third quartile 0.4771 *** (0.0945) Fourth quartile 0.9023 *** (0.1058) Out of labor force and retired as the baseline Unemployed 0.0648 (0.2315) Formally employed -0.0503 (0.2237) Informally employed 0.0819 (0.2276) Self-employed -0.0524 (0.2165) Urban village 0.3313 *** (0.0926) 0 – 1 Media as the baseline 2 Media 0.0158 (0.1325) 3 Media 0.1486 (0.1276) 4 Media 0.2683 * (0.1512) 5 – 6 Media -0.0154 (0.1724) HH size 0.0176 (0.0124) 74 Financial Inclusion Variables in the Equation Coefficient Stable income -0.0103 (0.0576) Saved as a child -0.0942 (0.0766) Constant -0.7529 *** (0.2795) Estimates of probit model. Standard error in parentheses *** p<0.01, ** p<0.05, * p<0.1 Table 10. Probability of Having a Bank Account and Having Ever Used Bank/NSCI Products by Social and Demographic Factors Bank/NSCI Bank/NSCI Product Usage account (Currently) Variables in the Equation Coefficient Coefficient Age 0.0069 ** 0.0025 (0.003) (0.0018) Male 0.6197 *** 0.1051 * (0.1011) (0.0614) No schooling as the baseline Primary, special and informal -0.5556 *** -0.2580 ** (0.1802) (0.1125) Secondary, vocational and tertiary -0.4664 ** -0.0779 (0.2091) (0.1309) Read/write in English or another language 0.3603 *** -0.0182 (0.1214) (0.0717) HH Head 0.0663 -0.0039 (0.0996) (0.0621) First quartile as the baseline Second quartile -0.1507 0.2082 *** (0.1025) (0.0761) Third quartile -0.0089 0.4107 *** (0.1281) (0.089) Fourth quartile 0.6136 *** 0.7645 *** (0.1633) (0.102) Out of labor force and retired as the baseline Unemployed -0.0108 -0.0472 (0.3049) (0.2417) Formally employed 0.9337 *** -0.1603 (0.3033) (0.2288) Informally employed 0.8590 *** 0.0231 (0.2815) (0.2324) Self-employed 0.8519 *** -0.0731 (0.2906) (0.2251) Urban village 0.1016 0.3250 *** (0.1288) (0.0867) 75 Bank/NSCI Bank/NSCI Product Usage account (Currently) Variables in the Equation Coefficient Coefficient 0 – 1 Media as the baseline 2 Media 0.0130 -0.0672 (0.0989) (0.0804) 3 Media 0.0139 0.0363 (0.1249) (0.0786) 4 Media -0.3540 ** 0.0132 (0.1627) (0.1118) 5 – 6 Media -0.0047 -0.0482 (0.2686) (0.1496) HH size -0.0004 0.0206 (0.0207) (0.0126) Stable income 0.0389 0.0081 (0.0972) (0.0596) Saved as a child -0.1752 -0.1084 (0.1294) (0.0903) Constant 0.3756 -0.5965 ** (0.3532) (0.2529) Table 11. Probability of Currently Having a Bank Account or Having Ever Used Bank/NSCI Products by Village Factors Bank/NSCI Product Bank/NSCI account Usage (Currently) Variables in the Equation Coefficient Coefficient Inner city as the baseline Urban 0.1904 0.1530 (0.1953) (0.0946) Peri-urban -0.3959 ** 0.1190 (0.1754) (0.0952) Rural (village) -0.1699 0.4937 *** (0.2059) (0.0932) Rural, non-village -0.2444 0.5240 *** (0.2177) (0.1021) Distance in km to primary school 0.0068 -0.0099 (0.0238) (0.0125) Distance in km to secondary school 0.0429 * 0.0093 (0.0254) (0.0159) Distance in km to clinic or hospital -0.0265 -0.0037 (0.0235) (0.0117) Distance in km to bank 0.0104 -0.0400 *** (0.017) (0.0089) Distance in km to MFI -0.0529 ** -0.0726 *** (0.0209) (0.0127) Most of the homes do not have electricity inside property as the baseline 76 Bank/NSCI Product Bank/NSCI account Usage (Currently) Variables in the Equation Coefficient Coefficient Most of the homes have electricity inside property 0.1869 * 0.1953 ** (0.1086) (0.0946) Most of the homes do not have piped water inside property Most of the homes have piped water inside property 0.4444 -0.1249 (0.1235) (0.1423) Water supply is a problem to some extent as the baseline Water supply is not a problem 0.2869 ** 0.0012 (0.1012) (0.0677) Unemployment is a problem as the baseline Unemployment is a problem to some extent 0.1124 0.0118 (0.1235) (0.0677) Unemployment is not a problem 0.2634 ** 0.0110 (0.1302) (0.0779) Crime is a problem as the baseline Crime is a problem to some extent 0.1783 -0.0207 (0.1201) (0.0666) Crime is not a problem 0.0265 0.0464 (0.1196) (0.0671) Life in location is better than 5 years ago as the baseline Life in location has not changed from 5 years ago -0.0837 -0.1016 * (0.1092) (0.0597) Life in location is worse than 5 years ago -0.0288 -0.0585 (0.1713) (0.1004) Normal dress below standards as the baseline Normal dress is standard in location -0.0824 -0.1447 ** (0.1005) (0.0642) Normal dress above standards in location 0.0391 0.0763 (0.169) (0.112) Location is wealthy (perceived) as the baseline Location is middle wealthy (perceived) 0.0293 0.0219 (0.0973) (0.052) Location is poor (perceived) 0.0182 -0.0013 (0.1009) (0.06) Constant 1.3740 *** -0.1704 (0.3492) (0.2162) Estimates of probit model. Standard error in parentheses *** p<0.01, ** p<0.05, * p<0.1 77 Table 12. Probability of Using and Having Ever Used Money Transfer Products by Social and Demographic Factors Money Transfer Money Transfer Product Usage Product Usage (Historical) (Currently) Variables in the Equation Coefficient Coefficient Age -0.0022 0.0015 (0.0022) (0.0019) Male -0.0239 -0.0975 (0.0695) (0.0741) No schooling as the baseline Primary, special and informal -0.2060 -0.1932 (0.1357) (0.1291) Secondary, vocational and tertiary -0.0719 -0.0351 (0.1495) (0.1324) Read/write in English or another language 0.0313 -0.0088 (0.0874) (0.0763) HH Head 0.1512 ** 0.1505 ** (0.0643) (0.0578) First quartile as the baseline Second quartile -0.1099 -0.0300 (0.0761) (0.0768) Third quartile 0.0388 0.2454 ** (0.1045) (0.0961) Fourth quartile 0.0456 0.2178 ** (0.1164) (0.1023) Out of labor force and retired as the baseline Unemployed -0.3214 -0.5149 ** (0.2393) (0.2231) Formally employed -0.3645 -0.6504 *** (0.2412) (0.234) Informally employed -0.3083 -0.5953 *** (0.2219) (0.2216) Self-employed -0.3584 -0.7462 *** (0.2214) (0.2233) Urban village 0.2551 ** 0.1979 ** (0.1025) (0.0806) 0 – 1 Media as the baseline 2 Media 0.2052 ** 0.0738 (0.0837) (0.0685) 3 Media 0.2631 *** 0.2301 *** (0.0831) (0.076) 4 Media 0.3805 *** 0.3761 *** (0.1049) (0.0859) 5 – 6 Media 0.5376 *** 0.2615 ** (0.1817) (0.1318) HH size -0.0176 -0.0133 (0.0153) (0.0129) Stable income 0.2756 *** 0.1338 ** 78 Money Transfer Money Transfer Product Usage Product Usage (Historical) (Currently) Variables in the Equation Coefficient Coefficient (0.068) (0.0593) Saved as a child 0.3565 *** 0.1230 (0.0902) (0.0768) Constant 0.8376 *** 0.4366 (0.3137) (0.2842) Estimates of probit model. Standard error in parentheses *** p<0.01, ** p<0.05, * p<0.1 Table 13. Probability of Using and Having Ever Used E-money Products by Social and Demographic Factors E-money Agent E-money Agent Product Usage Product Usage (Historical) (Currently) Variables in the Equation Coefficient Coefficient Age 0.0003 0.0019 (0.0019) (0.0024) Male 0.0507 0.2165 ** (0.0821) (0.0933) No schooling as the baseline Primary, special and informal -0.0110 -0.0380 (0.118) (0.143) Secondary, vocational and tertiary 0.1530 0.0256 (0.1427) (0.1758) Read/write in English or another language -0.0762 0.0410 (0.092) (0.0938) HH Head -0.0040 0.0234 (0.0684) (0.084) First quartile as the baseline Second quartile 0.2915 *** 0.3386 *** (0.0842) (0.1027) Third quartile 0.5244 *** 0.8480 *** (0.091) (0.1032) Fourth quartile 0.9216 *** 1.2248 *** (0.1059) (0.1104) Out of labor force and retired as the baseline Unemployed 0.1104 0.2712 (0.2881) (0.3388) Formally employed 0.3919 0.2476 (0.2544) (0.3036) Informally employed 0.2607 0.1953 (0.267) (0.3156) Self-employed 0.3190 0.0929 (0.2568) (0.3076) Urban village 0.0899 -0.1932 ** (0.0851) (0.0941) 0 – 1 Media as the baseline 79 E-money Agent E-money Agent Product Usage Product Usage (Historical) (Currently) Variables in the Equation Coefficient Coefficient 2 Media -0.0358 -0.1332 (0.0772) (0.0938) 3 Media 0.1375 0.1256 (0.0949) (0.0973) 4 Media 0.1472 0.2118 * (0.111) (0.1212) 5 – 6 Media 0.1656 0.0453 (0.1287) (0.1559) HH size -0.0008 -0.0091 (0.0127) (0.0194) Stable income 0.1758 ** 0.0997 (0.0735) (0.0789) Saved as a child 0.1145 0.0476 (0.0791) (0.0969) Constant -1.5709 *** -2.1114 *** (0.3114) (0.3906) Estimates of probit model. Standard error in parentheses *** p<0.01, ** p<0.05, * p<0.1 Table 14. Probability of Having Ever Used MFI Products by Social and Demographic Factors MFI Product Usage Variables in the Equation Coefficient Age 0.0065 ** (0.0028) Male 0.1032 (0.0775) No schooling as the baseline Primary, special and informal -0.1169 (0.1618) Secondary, vocational and tertiary 0.0381 (0.1998) Read/write in English or another language 0.0628 (0.1063) HH Head 0.2153 ** (0.0944) First quartile as the baseline Second quartile -0.0530 (0.0999) Third quartile -0.0656 (0.1153) Fourth quartile -0.3478 ** (0.1366) Out of labor force, unemployed and retired as the baseline Formally employed -0.1126 (0.2064) 80 MFI Product Usage Variables in the Equation Coefficient Informally employed -0.0135 (0.1775) Self-employed 0.0755 (0.1751) Urban village 0.0183 (0.1022) 0 – 1 Media as the baseline 2 Media -0.1150 (0.0968) 3 Media -0.1685 (0.1103) 4 Media -0.1011 (0.1405) 5 – 6 Media -0.6417 *** (0.2251) HH size 0.0378 ** (0.0183) Stable income 0.0414 (0.082) Saved as a child 0.0558 (0.1258) Constant -1.9590 *** (0.2555) Estimates of probit model. Standard error in parentheses *** p<0.01, ** p<0.05, * p<0.1 Table 15. Probability of Having Ever Used and Knowing about Insurance Products by Social and Demographic Factors Insurance Insurance Product Usage Awareness Variables in the equation Coefficient Coefficient Age 0.0015 0.0032 (0.0025) (0.0023) Male -0.0061 0.0499 (0.0884) (0.0782) No schooling as the baseline Primary, special and informal 0.0694 0.0580 (0.1583) (0.1406) Secondary, vocational and tertiary -0.0055 0.0944 (0.1945) (0.1711) Read/write in English or another language 0.0598 0.0424 (0.1072) (0.0953) HH Head 0.0886 0.0842 (0.0765) (0.0711) First quartile as the baseline Second quartile 0.3229 *** 0.2119 ** (0.1062) (0.0822) 81 Insurance Insurance Product Usage Awareness Variables in the equation Coefficient Coefficient Third quartile 0.6702 *** 0.5848 *** (0.1248) (0.1073) Fourth quartile 0.8065 *** 0.6697 *** (0.1253) (0.11) Out of labor force as the baseline Unemployed -0.0644 -0.1192 (0.3964) (0.3107) Formally employed 0.0441 -0.1182 (0.369) (0.3065) Informally employed -0.0380 -0.1864 (0.3343) (0.2807) Self-employed -0.1034 -0.1919 (0.3396) (0.2866) Urban village 0.1489 0.1607 (0.0992) (0.0976) 0 – 1 Media as the baseline 2 Media 0.0624 0.1302 (0.1073) (0.0893) 3 Media 0.1243 0.0826 (0.0972) (0.088) 4 Media 0.3882 *** 0.3054 *** (0.1028) (0.1024) 5 – 6 Media 0.1918 0.1363 (0.1512) (0.1567) HH size -0.0449 *** -0.0311 ** (0.0163) (0.0153) Stable income 0.0087 -0.0176 (0.0848) (0.0778) Saved as a child 0.1396 0.1965 ** (0.1148) (0.0911) Constant -1.7464 *** -1.4698 *** (0.3958) (0.3408) Estimates of probit model. Standard error in parentheses *** p<0.01, ** p<0.05, * p<0.1 82 Chapter 2. Financial Capability Table 16. Financial Literacy Score by Social and Demographic Factors Financial Literacy Score Level Low [0] Lower-middle [1 – 3] Middle [4] Upper-middle [5] High [6 – 7] Variables in the Equation Coefficient Age -0.0001 (0.0019) Male -0.0046 (0.0608) No schooling as the baseline Primary, special and informal 0.0065 (0.1007) Secondary, vocational and tertiary -0.0445 (0.1091) Read/write in English or another language 0.0188 (0.0672) HH Head 0.0045 (0.0596) First quartile as the baseline Second quartile 0.2602 *** (0.0616) Third quartile 0.5602 *** (0.0838) Fourth quartile 1.0959 *** (0.0861) Out of labor force and retired as the baseline Unemployed 0.1411 (0.2051) Formally employed 0.0544 (0.1971) Informally employed 0.0401 (0.2007) Self-employed 0.0627 (0.1982) Urban village 0.1724 ** (0.0775) 0 – 1 Media as the baseline 2 Media 0.0547 (0.0643) 3 Media -0.0439 (0.0714) 4 Media -0.0185 (0.0772) 83 Financial Literacy Score Level Low [0] Lower-middle [1 – 3] Middle [4] Upper-middle [5] High [6 – 7] Variables in the Equation Coefficient 5 – 6 Media 0.0934 (0.1015) HH size -0.0133 (0.011) Stable income -0.0045 (0.0564) Saved as a child 0.0449 (0.0721) /cut1 -2.2104 *** (0.2451) /cut2 0.2943 (0.2312) /cut3 1.2175 *** (0.2316) /cut4 2.1352 *** (0.2223) Estimates of ordered probit model. Standard error in parentheses *** p<0.01, ** p<0.05, * p<0.1 Table 17. Financial Knowledge Score by Social and Demographic Factors Financial Product Awareness Score Level Lower-middle [1 – 3] Middle [4] Upper-middle [5 - 6] High [7 – 9] Variables in the Equation Coefficient Age 0.0040 ** (0.0017) Male 0.0652 (0.0542) No schooling as the baseline Primary, special and informal -0.0297 (0.0969) Secondary, vocational and tertiary 0.0536 (0.118) Read/write in English or another language 0.0911 (0.0651) 84 Financial Product Awareness Score Level Lower-middle [1 – 3] Middle [4] Upper-middle [5 - 6] High [7 – 9] Variables in the Equation Coefficient HH Head -0.0404 (0.0476) First quartile as the baseline Second quartile 0.2232 *** (0.0641) Third quartile 0.5618 *** (0.0717) Fourth quartile 0.7395 *** (0.0769) Out of labor force and retired as the baseline Unemployed -0.0076 (0.2289) Formally employed 0.1457 (0.2453) Informally employed 0.1614 (0.2308) Self-employed 0.1149 (0.2336) Urban village 0.1840 *** (0.0652) 0 – 1 Media as the baseline 2 Media 0.1020 * (0.0568) 3 Media 0.1179 * (0.063) 4 Media 0.0119 (0.0927) 5 – 6 Media 0.1177 (0.0964) HH size -0.0074 (0.0107) Stable income 0.1510 *** (0.0507) Save as a child 0.0133 (0.0665) /cut1 0.3217 (0.2508) /cut2 1.3265 *** (0.25) /cut3 3.2685 *** (0.2731) Estimates of ordered probit model. Standard error in parentheses *** p<0.01, ** p<0.05, * p<0.1 85 Table 18. Financial Literacy Score by Village Factors Financial Literacy Score Level Low [0] Lower-middle [1 – 3] Middle [4] Upper-middle [5] High [6 – 7] Variables in the Equation Coefficient Inner city as the baseline Urban 0.2153 ** (0.1018) Peri-urban 0.0979 (0.1175) Rural (village) -0.3719 *** (0.1168) Rural, non-village -0.2553 * (0.1446) Distance in km to primary school -0.0025 (0.0144) Distance in km to secondary school 0.0201 (0.0139) Distance in km to clinic or hospital -0.0534 *** (0.013) Distance in km to bank -0.0136 (0.0088) Distance in km to MFI 0.0003 (0.0121) Most of the homes do not have electricity inside property as the baseline Most of the homes have electricity inside 0.1144 property (0.0741) Most of the homes do not have piped water inside property Most of the homes have piped water inside 0.0655 property (0.0833) Water supply is a problem to some extent as the baseline Water supply is not a problem -0.1742 (0.1262) Unemployment is a problem as the baseline Unemployment is a problem to some extent 0.2494 *** (0.0734) Unemployment is not a problem 0.3644 *** 86 Financial Literacy Score Level Low [0] Lower-middle [1 – 3] Middle [4] Upper-middle [5] High [6 – 7] Variables in the Equation Coefficient (0.0847) Crime is a problem as the baseline Crime is a problem to some extent -0.0744 (0.0724) Crime is not a problem -0.1123 (0.0695) Life in location is better than 5 years ago as the baseline Life in location has not changed from 5 years 0.0813 ago (0.069) Life in location is worse than 5 years ago 0.0332 (0.1102) Normal dress below standards as the baseline Normal dress is standard in location -0.1693 ** (0.0808) Normal dress above standards in location 0.1753 (0.1081) Location is wealthy (perceived) as the baseline Location is middle wealthy (perceived) -0.0720 (0.0706) Location is poor (perceived) -0.0077 (0.0811) /cut1 -2.7523 *** (0.2459) /cut2 -0.2711 (0.2336) /cut3 0.6328 (0.2293) /cut4 1.5304 *** (0.2273) Estimates of ordered probit model. Standard error in parentheses *** p<0.01, ** p<0.05, * p<0.1 87 Table 19. Financial Knowledge Score by Village Factors Financial Product Awareness Score Level Lower-middle [1 – 3] Middle [4] Upper-middle [5 - 6] High [7 – 8] Variables in the Equation Coefficient Inner city as the baseline Urban -0.0054 (0.1316) Peri-urban 0.0563 (0.1072) Rural (village) -0.4185 *** (0.111) Rural, non-village -0.3528 *** (0.1327) Distance in km to primary school -0.0366 *** (0.0128) Distance in km to secondary school 0.0055 (0.0132) Distance in km to clinic or hospital 0.0174 (0.014) Distance in km to bank -0.0267 *** (0.0075) Distance in km to MFI -0.0079 (0.0102) Most of the homes do not have electricity inside property as the baseline Most of the homes have electricity inside 0.1009 property (0.0664) Most of the homes do not have piped water inside property Most of the homes have piped water inside 0.0560 property (0.0732) Water supply is a problem to some extent as the baseline Water supply is not a problem -0.0336 (0.0633) Unemployment is a problem as the baseline Unemployment is a problem to some extent -0.1532 ** (0.0633) Unemployment is not a problem -0.0606 (0.0712) 88 Financial Product Awareness Score Level Lower-middle [1 – 3] Middle [4] Upper-middle [5 - 6] High [7 – 8] Variables in the Equation Coefficient Crime is a problem as the baseline Crime is a problem to some extent -0.0657 (0.0639) Crime is not a problem -0.0434 (0.0653) Life in location is better than 5 years ago as the baseline Life in location has not changed from 5 years -0.0231 ago (0.0493) Life in location is worse than 5 years ago -0.0735 (0.0985) Normal dress below standards as the baseline Normal dress is standard in location -0.1397 * (0.0728) Normal dress above standards in location 0.0959 (0.1372) Location is wealthy (perceived) as the baseline Location is middle wealthy (perceived) -0.0098 (0.0531) Location is poor (perceived) -0.2233 *** (0.0576) /cut1 -1.1973 *** (0.2018) /cut2 -0.2021 (0.2032) /cut3 1.7280 (0.206) Estimates of ordered probit model. Standard error in parentheses *** p<0.01, ** p<0.05, * p<0.1 89 Table 20. Financial Capabilities by Social and Demographic Factors (I) Controlled Saving capacity Planning for old Planning for the budgeting age expenses unexpected Variables in the Coefficient Coefficient Coefficient Coefficient Equation Financial Literacy -1.1908 * 1.5347 ** 0.6264 0.3216 Score (0.6458) (0.6814) (0.6463) (0.3687) Financial Product 0.7501 0.2487 0.1433 -0.7303 * Awareness (0.8374) (0.6692) (0.7046) (0.3795) Age -0.0295 0.1460 ** 0.0785 -0.0444 (0.0576) (0.0664) (0.0737) (0.0302) Male 1.9757 -1.6053 3.5699 ** -1.4592 (1.835) (1.7907) (1.7425) (1.0049) No schooling as the baseline Primary, special and -1.8475 -5.0370 4.7250 2.9034 * informal (3.7845) (3.4741) (3.2629) (1.5002) Secondary, vocational -1.3500 -0.4207 5.0253 3.2707 ** and tertiary (4.4158) (4.2638) (3.7015) (1.5181) Read/write in English 3.2908 -0.0974 1.9575 -1.8074 or another language (2.2624) (2.5562) (2.1429) (1.1342) HH Head -1.8849 3.4163 * -1.5740 1.2012 (1.7854) (1.7911) (1.7966) (1.0877) First quartile as the baseline Second quartile -5.4213 ** 1.0611 5.9931 *** -0.4989 (2.2633) (1.945) (1.8789) (0.9179) Third quartile -9.7112 *** 9.0518 *** 4.0321 * 0.2028 (2.5908) (3.1084) (2.4115) (1.1853) Fourth quartile -15.3017 *** 19.0371 *** 10.7568 *** 2.4002 (3.0201) (3.5741) (2.918) (1.4777) Out of labor force and retired as the baseline Unemployed 1.8409 5.5726 -5.7693 0.1758 (7.0498) (7.6325) (6.0664) (3.2977) Formally employed 2.0758 7.3397 -9.2952 -0.9319 (7.3254) (7.2413) (6.4461) (3.3335) Informally employed -1.9411 0.8644 -8.0388 -0.8790 (7.4944) (7.2605) (5.7843) (3.033) Self-employed -2.2770 -2.5257 -9.4736 * -1.8985 (7.3109) (7.2398) (5.4318) (3.161) Urban village -0.4464 -1.3010 -4.4660 * -0.9153 (2.2743) (2.781) (2.3339) (1.1334) 90 Controlled Saving capacity Planning for old Planning for the budgeting age expenses unexpected Variables in the Coefficient Coefficient Coefficient Coefficient Equation 0 – 1 Media as the baseline 2 Media 0.8228 1.6490 0.5386 0.6623 (2.0293) (2.1262) (1.912) (1.0196) 3 Media 2.1875 7.8950 *** 1.5474 0.4172 (2.0762) (2.2742) (1.9994) (1.3175) 4 Media 4.4294 3.9191 4.7371 * -1.5397 (3.0212) (3.1204) (2.6859) (1.5201) 5 – 6 Media -0.2230 6.3899 0.9732 -2.2753 (3.9993) (4.3458) (2.9701) (1.872) HH size -0.2980 -0.3076 -0.2936 0.1123 (0.346) (0.3879) (0.3922) (0.1751) Stable income 0.8516 7.3924 *** -2.9254 * 1.5922 * (1.5348) (1.9576) (1.7567) (0.9375) Saved as a child 1.5484 2.5181 2.1010 38.6423 *** (2.129) (2.4726) (2.0304) (0.5913) Constant 60.3834 *** 0.5776 39.8989 *** 62.6627 *** (6.6644) (8.41) (7.4537) (3.7403) Estimates of the regression model. Standard error in parentheses *** p<0.01, ** p<0.05, * p<0.1 Table 21. Financial Capabilities by Social and Demographic Factors (II) Living within Responsibility Self-discipline Choosing one’s means financial products Variables in the Coefficient Coefficient Coefficient Coefficient Equation Financial Literacy 0.6409 -0.2894 0.2934 -0.3511 Score (0.4321) (0.3978) (0.3601) (0.5149) Financial Product 0.6616 0.6174 -0.4474 -0.4783 Awareness (0.5638) (0.4386) (0.4368) (0.4959) Age 0.0233 -0.0845 ** -0.0303 -0.0797 * (0.0404) (0.0359) (0.0373) (0.0451) Male -0.0657 0.2724 -3.0965 *** 0.4922 (1.1535) (1.3641) (1.1779) (1.3308) No schooling as the baseline Primary, special and 5.0569 ** -5.6539 *** -4.7156 ** 1.7549 informal (2.4914) (1.8305) (2.3487) (2.2033) 91 Living within Responsibility Self-discipline Choosing one’s means financial products Variables in the Coefficient Coefficient Coefficient Coefficient Equation Secondary, vocational 5.4510 * -6.4751 *** -4.6956 * -0.4247 and tertiary (2.787) (2.0931) (2.4475) (2.7001) Read/write in English -2.1897 -0.1963 2.6705 * -0.1771 or another language (1.5365) (1.2915) (1.3988) (1.4148) HH Head 1.1940 0.0224 1.8931 1.1447 (0.9909) (1.2561) (1.3234) (1.3992) First quartile as the baseline Second quartile 2.9445 * 1.6415 -1.4703 1.3019 (1.6243) (1.1918) (1.516) (1.3655) Third quartile 2.6653 4.1022 *** 0.0992 2.3462 (1.9342) (1.4838) (1.5372) (1.6255) Fourth quartile 4.2955 ** 7.3755 *** -3.2377 * 2.6288 (2.1359) (1.7997) (1.6574) (1.9064) Out of labor force and retired as the baseline Unemployed -2.7237 3.7628 1.5230 8.3765 (4.7595) (3.9492) (4.6788) (5.6456) Formally employed -1.5499 3.9335 4.5606 5.2671 (4.2409) (4.1281) (4.413) (5.5422) Informally employed -3.4197 3.9620 4.2310 3.7487 (4.2049) (3.7317) (4.2533) (5.4745) Self-employed -1.3361 5.2870 4.5814 2.1718 (4.0883) (3.6548) (4.4058) (5.5167) Urban village -0.8558 1.0781 -0.6413 -0.6839 (1.6284) (1.3897) (1.5103) (1.6137) 0 – 1 Media as the baseline 2 Media -0.6766 1.3103 -1.6916 2.5595 ** (1.4555) (1.2807) (1.6177) (1.2621) 3 Media 3.1815 * 5.1701 *** -1.2995 3.0789 ** (1.7002) (1.4445) (1.6734) (1.4056) 4 Media 4.6640 ** 7.4701 *** -0.3925 6.1073 *** (2.0168) (1.9288) (2.1293) (1.7118) 5 – 6 Media 7.3755 *** 2.8954 -2.5259 1.8208 (1.7287) (2.9506) (2.4134) (2.6239) HH size -0.1741 -0.0864 0.0983 -0.4766 ** (0.2764) (0.2245) (0.2097) (0.2338) Stable income -1.0078 1.7963 * 2.0148 * -0.3450 (1.1943) (1.0431) (1.0791) (1.1331) Saved as a child 3.5130 ** 1.9945 -2.8464 * 1.1043 (1.3396) (1.5499) (1.5757) (1.821) Constant 76.3748 *** 37.2272 *** 46.6972 *** 42.6240 *** (5.9646) (4.842) (4.9427) (6.1858) 92 Living within Responsibility Self-discipline Choosing one’s means financial products Variables in the Coefficient Coefficient Coefficient Coefficient Equation Estimates of the regression model. Standard error in parentheses *** p<0.01, ** p<0.05, * p<0.1 93 Chapter 3. Relationship Between Financial Inclusion and Financial Capability Table 22. Probability of Financial Inclusion by Financial Literacy Score, Financial Product Awareness, Social and Demographic Factors Financial inclusion Variables in the Equation Coefficient Financial Literacy Score 0.0200 (0.0232) Financial Product Awareness 0.1485 *** (0.0234) Age 0.0027 (0.002) Male 0.1217 * (0.0639) No schooling as the baseline Primary, special and informal -0.2611 ** (0.1172) Secondary, vocational and tertiary -0.1340 (0.1446) Read/write in English or another language 0.0202 (0.0718) HH Head 0.0272 (0.062) First quartile as the baseline Second quartile 0.2332 *** (0.0766) Third quartile 0.3880 *** (0.0964) Fourth quartile 0.7861 *** (0.1089) Out of labor force and retired as the baseline Unemployed 0.0653 (0.2324) Formally employed -0.0666 (0.2228) Informally employed 0.0635 (0.2262) Self-employed -0.0741 (0.2128) Urban village 0.3655 *** (0.0937) 0 – 1 Media as the baseline 2 Media -0.0994 (0.0796) 3 Media 0.0352 (0.0792) 4 Media 0.1676 94 Financial inclusion Variables in the Equation Coefficient (0.1032) 5 – 6 Media -0.0463 (0.134) HH size 0.0188 (0.0125) Stable income -0.0330 (0.0574) Saved as a child -0.1115 (0.0777) Constant -1.2078 *** (0.273) Estimates of probit model. Standard error in parentheses *** p<0.01, ** p<0.05, * p<0.1 Table 23. Probability of Using Financial Instruments on Financial Capability Scores (I) Bank/NSCI Insurance MFI Product Product Usage Product Usage Usage Variables in the Coefficient Coefficient Coefficient Equation Financial Product 0.1392 *** 0.4150 *** 0.3523 *** Awareness (0.0237) (0.053) (0.0455) Financial Literacy 0.0709 *** -0.0103 -0.0463 Score (0.0231) (0.0424) (0.0371) Controlled budgeting -0.0002 0.0026 * 0.0038 *** (0.0009) (0.0014) (0.0012) Saving capacity 0.0005 0.0015 -0.0038 *** (0.0007) (0.0012) (0.0012) Planning for old age 0.0019 ** 0.0004 -0.0030 ** expenses (0.0009) (0.0015) (0.0014) Planning for the 0.0011 0.0054 ** 0.0004 unexpected (0.0013) (0.002) (0.0017) Living within one’s -0.0006 -0.0001 -0.0017 means (0.0011) (0.002) (0.0014) Responsibility 0.0024 ** 0.0008 -0.0022 (0.0011) (0.0022) (0.0019) Self-discipline 0.0024 ** -0.0061 *** -0.0004 95 Bank/NSCI Insurance MFI Product Product Usage Product Usage Usage Variables in the Coefficient Coefficient Coefficient Equation (0.0011) (0.0021) (0.0015) Choosing financial 0.0002 -0.0020 -0.0005 products (0.0012) (0.0021) (0.0017) Age 0.0034 -0.0066 0.0080 ** (0.0026) (0.0059) (0.0038) Male 0.1224 * -0.0598 0.0377 (0.0653) (0.1208) (0.0824) No schooling as the baseline Primary, special and -0.3030 ** 0.0189 -0.2926 * informal (0.1232) (0.2406) (0.1753) Secondary, vocational -0.1952 0.0231 -0.1656 and tertiary (0.1357) (0.2817) (0.1976) Read/write in English 0.0246 -0.0267 0.0139 or another language (0.0744) (0.1524) (0.112) HH Head -0.0591 0.1370 0.1908 * (0.0658) (0.1044) (0.1023) Constant -1.4628 *** -3.5901 *** -2.8413 *** (0.2126) (0.5339) (0.3838) Estimates of probit model. Standard error in parentheses *** p<0.01, ** p<0.05, * p<0.1 96 Table 24. Probability of Using Financial Instruments on Financial Capability Scores (II) Money Transfer E-money Agent Product Usage Product Usage Variables in the Coefficient Coefficient Equation Financial Product 0.2629 *** 0.2790 *** Awareness (0.0278) (0.0283) Financial Literacy 0.0564 ** 0.1434 *** Score (0.0249) (0.0254) Controlled budgeting 0.0007 0.0019 ** (0.0008) (0.0008) Saving capacity 0.0030 *** 0.0023 *** (0.0008) (0.0008) Planning for old age -0.0015 0.0012 expenses (0.0009) (0.001) Planning for the 0.0062 *** 0.0043 *** unexpected (0.0013) (0.0012) Living within one’s 0.0023 ** 0.0027 ** means (0.0011) (0.0012) Responsibility 0.0011 0.0050 *** (0.0014) (0.0013) Self-discipline 0.0019 0.0003 (0.0013) (0.0012) Choosing financial -0.0008 0.0002 products (0.0012) (0.0012) Age -0.0041 0.0052 * (0.0032) (0.0026) Male 0.0211 0.0936 (0.0757) (0.0842) No schooling as the baseline Primary, special and -0.0446 -0.0578 informal (0.1466) (0.1217) Secondary, vocational 0.0899 0.0788 and tertiary (0.1643) (0.1555) Read/write in English 0.0523 -0.0381 or another language 97 Money Transfer E-money Agent Product Usage Product Usage Variables in the Coefficient Coefficient Equation (0.0962) (0.0978) HH Head 0.1020 -0.0393 (0.0669) (0.0766) Constant -1.1900 *** -3.4247 *** (0.2588) (0.2697) Estimates of probit model. Standard error in parentheses *** p<0.01, ** p<0.05, * p<0.1 98 Chapter 4. Consumer Protection Table 25. Probability of Encountering a Financial Conflict by Social and Demographic Factors Financial disputes Variables in the Equation Coefficient Age 0.0045 * (0.0026) Male 0.1576 * (0.0796) No schooling as the baseline Primary, special and informal -0.1414 (0.1349) Secondary, vocational and tertiary -0.0333 (0.1589) Read/write in English or another language 0.1400 (0.1021) HH Head -0.0772 (0.0742) First quartile as the baseline Second quartile 0.0909 (0.0922) Third quartile -0.0511 (0.1154) Fourth quartile -0.0362 (0.1393) Out of labor force and retired as the baseline Unemployed 0.1740 (0.2971) Formally employed 0.3076 (0.2789) Informally employed 0.2981 (0.2639) Self-employed 0.3135 (0.2616) Urban village 0.1036 (0.0952) 0 – 1 Media as the baseline 2 Media -0.1291 (0.0818) 3 Media -0.1483 (0.0943) 4 Media 0.1385 (0.118) 5 – 6 Media 0.0063 (0.1523) HH size 0.0223 (0.0149) Stable income -0.1408 * 99 Financial disputes Variables in the Equation Coefficient (0.0758) Save as a child -0.1701 * (0.0986) Central as the baseline Copperbelt -0.8250 *** (0.3041) Eastern -0.2124 (0.1611) Luapula -0.8324 *** (0.1867) Lusaka -0.6622 *** (0.2409) Muchinga -0.1175 (0.2608) Northern -0.3730 ** (0.1826) North -0.2878 (0.2172) Southern 0.3862 ** (0.1559) Western -0.0044 (0.2204) Constant -1.7657 *** (0.31) Estimates of probit model. Standard error in parentheses *** p<0.01, ** p<0.05, * p<0.1 100