Bou WP29 2020 DFS COVID-19 and Future of FS

Working Paper Series

Working Paper No. 29/2020

Digital Financial Services, COVID-19, and Future Financial Services Landscape in Uganda

George Wilson Ssonko and Duncan Roy Kawooya

December 2020

Working Papers describe on-going research by the author(s) and are published to elicit comments and to further debate. The views expressed in the working paper series are those of the author(s) and do not in any way represent the official position of the Bank of Uganda. This paper should1 not therefore be reported as representing the views of the Bank of Uganda or its management.

Bank of Uganda WP No. 29/2020

Digital Financial Services, COVID-19, and Future Financial Services Landscape in Uganda Prepared by George Wilson Ssonko* and Duncan Roy Kawooya** Bank of Uganda December 2020 Abstract

Digital Financial Services (DFS) which is a broad term encompassing the delivery of financial services (deposits, savings, payments, credit, insurance, and wealth management etc.) through Information Communication Technology (ICT) based means was popularised through Person to Person (P2P) payments in Uganda largely driven by the advent of mobile telephony in March 2009. P2P payments dominated the DFS space. The uptake of other value-added services like payment for utilities, Bank to Wallet (B2W), Wallet to Bank (W2B), insurance, and credit extension was low. However, the advent of Coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 virus led to various measures aimed at stemming the spread of the pathogen such as complete national lockdowns and in-land & cross border travel restrictions. Consequently, traditional approaches to banking in Brick & Mortar Financial Institutions were constrained. As a result of the constraints and incentives by Mobile Money Service Providers (MMSPs) such as reduced costs of services, there was an increase in the uptake of other value-added services. Nevertheless, it is known with certainty whether these uptake trends will be maintained post- COVID. The paper contributes to the research that explores the effect of COVID-19 on DFS and provides guidance to stakeholders in the DFS framework. The paper points out that sustainability of DFS uptake will be influenced by among others cost factors such as MMSPs surcharges, Over-The-Counter (OTC) taxes, reliability of DFS infrastructure, as well as cost- benefit comparison of DFS and Traditional Brick & Mortar Financial Services (TBMFS). In addition, policies such as use of Digital Financial Literacy (DFL) to enhance knowledge, skills, and confidence of using DFS are vital in the sustainability question. Although the recommendations therein emanate from the current COVID-19 Pandemic, the rising frequency of economic shocks and disruptions on account of environmental, health, and financial crises point to cross-applicability in other similar circumstances.

JEL Classification: O32; O33 Key Words: COVID-19, Uganda, DFS, DFL, and MMSPs Correspondence Address: *Communications Department and **Economic Research Department, Bank of Uganda, P.O. BOX 7120, Kampala, Uganda, Tel. +256414230791, Fax. +256414230791. E-mails: [email protected], [email protected]

I. Introduction On December 31, 2019, the Chinese authorities notified the World Health Organisation (WHO) about a mysterious respiratory infection which was spreading in one of its provinces (WHO, 2020). By January 12, 2020 the World Health Organization (WHO) had confirmed that a novel coronavirus (SARS-CoV-2) was the cause of the respiratory illness with pneumonia symptoms that would later be named COVID-19 in a cluster of people in Wuhan City, Hubei Province, China. On January 30, 2020, the COVID-19 disease was declared a “public health emergency of international concern” and on March 12, 2020 it was categorised as a pandemic (an outbreak of a new infectious pathogen that spreads easily from person to person across the globe). As at December 03, 2020 (23:26 hours East African Time), the disease had ravaged 190 countries / regions with 64,964,775 confirmed global cases and 1,501,076 deaths (mortality rate of 2.311 percent) (John Hopkins University Coronavirus Resource Center, 2020). Africa has not been spared the effects of the COVID-19 disease. As at December 03, 2020 (10:00 hours East African Time), the total confirmed cases stood at 1,507,349 individuals with 24,464 fatalities, a mortality rate of 1.623 percent (World Health Organisation Regional Office for Africa, 2020). During the same period, Uganda had registered 21,409 cases with 206 fatalities translating into a mortality rate of 0.962 percent (John Hopkins University Coronavirus Resource Center, 2020). Even though the COVID-19 disease has not yet ravaged the weak public health systems of the developing countries of Africa to the levels of Advanced Economies, it has not spared their economies on account of the almost complete national lockdowns and restrictions of in-land and cross border / international travel. According to the ODI (2020), the estimated impact of COVID-19 on the African continent is expected to be a contraction in economic growth from 2.4 percent in 2019 to about minus 2.1 percent to minus 5.1 percent in 2020 which translates into output losses of US$37 billion up to US$79 billion. According to the African Union (AU) (2020), African economies will be affected through two ways:- (1) directly through decline in workers’ remittances from African Diaspora; Foreign Direct Investment (FDI); and Official Development Assistance (ODA) etc.; and (2) indirectly through morbidity and mortality; disruption of supply chains; contraction of domestic demand due to loss or decline of income; and rising public expenditure to support economic activities and safeguard human health against COVID-19. Similar impacts are projected for the Ugandan economy (MoFPED, 2020; BoU, 2020). Mugume, Opolot, Kasekende and Namanya (2020) observe that economic activity in Uganda is expected to contract from 6.8 percent in FY2018/2019 to 3.1 percent in FY2019/2020 before recovering to 4.0-5.0 percent and 6.0-6.5 percent in FY2020/2021 and FY2021/2022, respectively. The projected economic contraction is to be expected because Uganda is a small open economy with various interlinkages in the global trade and financial system such that a ‘sneeze’ by the major players can lead to a cold in this East African nation of 43million people. As a consequence of the negative projections and the recent memories from the Great Recession, countries across the globe have proposed several measures to mitigate the impact of COVID-19

on national economies. “In order to cushion the effect of the crisis on households and firms, Governments are designing a wide range of policy responses, including direct income-support, tax breaks extension of guarantees, and deferred payments on debt” etc. (AU, 2020). The responses adopted in various developing countries like Uganda have been collaborative in nature involving the Central Banks, Central Government, and private sector economic agents. In Uganda, like the rest of the world, the mechanisms deployed by the Government of Uganda to combat the SARS-CoV-2 microbes included quarantine, hygiene, and social distancing. Specifically, measures1 in Uganda included mandatory use of face masks in public spaces; and restriction of people movements by closing borders and the airspace as well as banning of transportation means. In addition, banning of mass gatherings like public prayers; congregating in educational institutions; clustering in business places; and entertainment related gatherings coupled with sensitisation of the masses to enhance nutrition were undertaken. The Government of Uganda restrictions introduced to curb the spread of COVID-19 have affected businesses across the country. The Financial Service Providers (FSPs) have not been spared as well. For example at the height of the national lockdown (March to April 2020), FSPs had closed at least 50 percent of their branch networks and for those branches that remained open, the enforcement of curfew from 19:00hours to 06:30hours led to the reduction in the working hours from 08:30hours - 20:00hours to 09:00hours - 15:00hours. In addition, the Supervised Financial Institutions (SFIs), ceased operating over the weekend. As a consequence, financial consumers were encouraged to use Information Communication Technology (ICT) based delivery models such as mobile money / banking, internet banking, and Automated Teller Machines (ATMs) banking etc. The spatial (movement was not permissible outside one’s administrative jurisdiction e.g. Greater Kampala Metropolitan Area or District) and temporal (curfew limitations) restrictions on human movement introduced by the State implied that access to financial services was largely moved onto digital finance channels. As a consequence, digital delivery channels that were perceived as complementary to traditional face to face delivery channels (Ssonko, 2016) were now the defacto means of accessing financial services. The World Bank observes that ‘the current COVID-19 pandemic has amplified the urgency of utilizing fintech to keep financial systems functioning and keep people safe during this time of social distancing, falling demand, reduced input supply, tightening of credit conditions and rising uncertainty’ (Pazarbasioglu, Mora, Uttamchandani, Natarajan, Feyen & Saal, 2020). It is not known with certainty whether the financial services access traffic pushed towards digital channels on account of COVID-19 will continue in the post COVID-19 era. To address the issue, the paper explores DFS with specific focus on Mobile Money before and during COVID-19. In addition, it draws inferences from the data to shed light on the likely direction of the sub-sector and what ought to be done to ensure the continuance of the digital financial services uptake. The rest of the paper is organised as follows:- (i) DFS in Uganda; (ii) Confluence of factors determine uptake and continuance of MMSPs usage; (iii) Drivers of DFS

1 Appendix 8.1 provides a list of 35 measures Government of Uganda (GoU) deployed at the height of the lockdown 4

before COVID-19; (iv) Drivers of DFS during COVID-19; and (v) Future of DFS landscape in Uganda.

II. Digital Financial Services in Uganda Digital Financial Services (DFS) encompass a ‘broad range of financial services accessed and delivered through digital channels, including payments, credit, savings, remittances, and insurance’ (Kambale, 2018). The digital channels include the internet, cellular / mobile phone, automated teller machines (ATMs), and points of sale (PoS) terminals etc. (Kambale, 2018). DFS includes traditional brick & mortar financial institutions based digitally delivered financial services e.g. internet banking, cheque truncation, telegraphic transfer, and agency banking etc. as well as mobile financial services (MFS) such as mobile money, mobile payments, and mobile banking etc. In Uganda, DFS is dominated by MFS with seven (7) mobile money service providers (MMSPs)2 in the market, namely Afrimoney, Airtel money, Ezee money, MCash, Micropay, MTN mobile money, and UTL MSente. Nonetheless, other fintechs exist in the market. DFS have numerous benefits which can expand the delivery of financial services to the Bottom of the Pyramid (BoP) clients through innovative technologies like mobile phone enabled solutions, electronic money models, and digital payment platforms (AFI, 2020; Pazarbasioglu et al., 2020; Kambale, 2018). Some of the benefits include cost reduction and lower surcharges on account of maximising economies of scale; enhanced accessibility / outreach; increased efficiency; better quality service; increased speed, security, and transparency of transactions; potential for product customisation; as well as convenience (Masocha & Dzomonda, 2018; AFI, 2020; Pazarbasioglu et al., 2020; Kambale, 2018). Ssonko (2011) explored the salient characteristics of Uganda’s MMSPs and noted the following:- (i) The prevalent business model was [mobile network] operator-centric deployed by the three MMSPs then (MTN mobile money, Airtel ZAP, and UTL MSente). As at February 2011, MTN mobile money had about 89.40 percent market share measured as a proportion of total registered customers while Airtel ZAP and UTL MSente had 7.55 percent and 3.05 percent, respectively. (ii) The regulatory framework had a duality of regulators - between March 2009 and July 2020 the regulatory framework provided for a dual oversight of MMSPs by Bank of Uganda and Uganda Communications Commission till the Presidential assent to the National Payments Act 2009. At the time, there was no specialised legislation for the regulation of MMSPs. (iii) The relationship between mobile network operators (MNOs) and commercial banks was such the former did the bulk of the work (marketing, customer care, mobile account opening and clientele safety) while the latter provided custody of the ‘physical cash’ through maintenance of an escrow account. in matters of licensing and supervising MMSPs.

2 Eight, over the time MMSPs have existed in Uganda. Warid Pesa was integrated into Airtel Money with the Airtel -Warid merger that was finalized on April 23, 2013 5

(iv) The MMSPs relied on short messaging services (sms) and USSD (Unstructured Supplementary Service Data) to deliver services to their clientele. (v) The services offered at the time were categorised as payment and remittance services which largely were basic movements of monetary value from one economic agent to another. These included cash-in, cash-out, purchase of airtime, person to person (P2P) money transfers, person to business (P2B), mobile accounts enquiry, and bills payment. (vi) A tiered transaction charges cost structure was in place in which movement of a single Uganda Shilling became cheaper as one transferred higher amounts. (vii) Uptake of the mobile money service assessed as the number of registered customers had increased by over 10,000 percent from 10,011 users in March 2009 to 1,737,904 users in February 2011. Nevertheless, the paper did not indicate usage activity (number of registered users active in the last 90days). (viii) Other metrics such as number of transactions, value of transactions, and balances on clients’ accounts were on an upward trajectory between March 2009 and February 2011 indicating increased uptake of mobile money services in the country. Over the ensuing period since February 2011, a number of changes have occurred in the digital financial services space including among others financial deepening (increased use of existing mobile money services and products); financial widening (creation of new product offerings); policy disruptions such as switching off mobile money during 2016 national elections; as well as introduction of a plethora of taxes on mobile network operators. Twenty one months after the introduction of the social media tax and taxes on the value of mobile money payments in July 2018 which led to the contraction of MMS business volume, the COVID-19 disruption struck in March 2020. The COVID-19 disruption led to the introduction of a national lockdown which saw the closer of businesses3 including Micro, Small and Medium Enterprises (MSMEs) that employ over 80 percent of the 20 million strong labour force and contraction of household incomes. Furthermore, the social distancing measures, banning of public and private transportation, and imposition of curfew that reduced working hours of Traditional Brick & Mortar Financial Institutions pushed financial consumers of DFS towards digital channels especially mobile money. The magnitude and direction of the effect of COVID-19 disruption on MMSPs is still in flux. However, in this paper, we explore preliminary evidence of the likely effects of the COVID-19 disruption and how it might shape the digital financial services landscape going forward.

3 Sectors such as human health & medical services; agricultural & veterinary services; security; banking; telecommunications; construction; factories; utilities; groceries; supermarkets; food markets; and segments of transportation (cargo haulage and delivery services of boda bodas / motorbikes) were exempt from certain forms of extreme lockdown measures 6

III. Confluence of Factors determine Uptake and Continuance of MMSPs Usage 3.1 Determinants based on Theoretical Models of Technology Adoption The successful deployment of mobile money services (MMS) in a country as well as the continued patronisation of the MMSP by financial consumers is determined by a confluence of factors. Table 1 summarizes some studies that investigated determinants of mobile money adoption. Table 1: Determinants of Mobile Money adoption from Literature Author Econometric Additional Explanatory Country & Data Methodology & Variables beyond PEOU and Used Theoretical Framework PU Amoroso and Magnier- Structural Equation Facilitating Conditions; Japan; Primary Watnabe (2012:99) Modeling (SEM) & Perceived Value; Perceived Technology Acceptance Security & Privacy; Social Model (TAM) Influence; Trust; Perceived Risk; Attrativeness of Alternatives

Luarn and Lin Structural Equation Perceived Credibility; Perceived Taiwan; Primary (2005:873) Modeling (SEM) & Self-Efficacy; Perceived Technology Acceptance Financial Cost Model (TAM)

Kuo and Yen (2009:103) Structural Equation Perceived Cost; Perceived Taiwan; Primary Modeling (SEM) & Innovatiness Technology Acceptance Model (TAM)

Tang and Chiang Structural Equation Perceived Convenience; Taiwan; Primary (2009:1605) Modeling (SEM) & Perceived Self-Efficacy Technology Acceptance Model (TAM) Cheney (2008:2) No clear model; Study Consumer experience & USA; Secondary underpinned by two familiarity; Nature of supporting concepts, that is, platform technology; Financial “experience goods” and Inclusion opportunities; Data “learning by doing” Security Problems Chidembo (2009:40-43) Diffusion Innovation Trust & Security; Complexity; South Africa; Primary Theory Relative Advantage; Cost; & Secondary Compatibility

Tossy (2014:4-5) Theory of User Acceptance Facilitating Conditions; Tanzania; Primary and Use of Technology Performance Expectancy; Effort (UTAUT) Expectancy; Social Influence; Trust; Perceived Risk

Padashetty and Kishore Structural Equation Trust; Expressiveness India; Primary (2013:85-86) Modeling (SEM) & Technology Acceptance 7

Author Econometric Additional Explanatory Country & Data Methodology & Variables beyond PEOU and Used Theoretical Framework PU Model (TAM)

Larkotey et al., Structural Equation Perceived positive perception; Ghana; Primary (2013:369-371) Modeling (SEM) & Perceived benefits of the service; Technology Acceptance Pre-knowledge of the user Model (TAM) Lule, Omwansa and Structural Equation Perceived Self-Efficacy; Kenya; Primary Waema (2012:32) Modeling (SEM) & Perceived Credibility; Subjective Technology Acceptance Norms; Transaction Costs Model (TAM)

Kazi and Mannan (2013: Structural Equation Perceived Risk; Social Influence Pakistan; Primary 54-56) Modeling (SEM) & Technology Acceptance Model (TAM)

Zhao and Kurnia (2014: Qualitative Study System Quality; Service Quality; China; Primary 1&6) Social Influence; Trust; Users’ characteristics

Kasyoki (2012: online) Structural Equation Relative advantage; Personal Kenya; Primary Modeling (SEM) & Innovativeness; Perceived Risk; Technology Acceptance Social Norms Model (TAM)

Oluoch (2012: 29-35) Multivariate regression Perceived Risk Kenya; Primary analysis (Probit model); & Technology Acceptance Model (TAM)

Govender and Sihlali Structural Equation Perceived Ease of Adoption; South Africa; Primary (2014: 453-454) Modeling (SEM) & Perceived Value; Trust; Social Technology Acceptance Influence Model (TAM)

CGAP (2013:2) Innovative Analytics and Social network and social Three African Data Mining Techniques interactions of the mobile users; Countries; Primary & User’s telecom usage profile Secondary (quantity and variety of telecom products used such as sms, data, electronic top-ups, and voice etc.)

Masocha & Dzomonda Structural Equation Benefits of mobile money; Zimbabwe; Primary (2018:1) Modeling (SEM) & Challenges of traditional Technology Acceptance financial services Model (TAM)

Malinga, Maiga, Jehopio Descriptive Statistics and Level of exposure, Legal Issues, Uganda; Primary and Kareyo (2017:189) Unified Theory of Sensitisation, Security, Acceptance and Use of Performance Expectancy, Effort Technology (UTAUT) Expectancy, Social Influence, 8

Author Econometric Additional Explanatory Country & Data Methodology & Variables beyond PEOU and Used Theoretical Framework PU model and Facilitating Conditions

Meena (2014:1) Descriptive Statistics and Perceived Usefulness; Perceived Tanzania; Primary Technology Acceptance Ease of Use; Intention to Use Model (TAM) Maradung (2013:33) Analysis of Variance Age; Gross Income; Educational Botswana; Primary (ANOVA) and Technology Level; Ownership of bank Acceptance Model (TAM) account

Muir (2015:xi) Correlation Analysis and Relative advantage; Perceived Kenya; Primary Diffusion of Innovation risk; Complexity; Compatibility; Observability

Rolfe (2015: online) Descriptive Statistics Social media & messaging apps; 15 countries world Screening; Trust; Privacy & wide; Secondary Security; Bandwidth; Network Speed Musiime and Alinda Descriptive Statistics and Courtesy of MM agents; Uganda; Primary (2016:1) Linear Regression Analysis Efficiency of MM agents; Cleanliness of MM business premises Tangirala and Nlondiwa Descriptive Statistics Transactional costs; Connectivity Botswana; Primary (2019:1) issues

Muzurura and Chigora Structural Equation Perceived Usefulness; Perceived Zimbabwe; Primary (2019:316) Modeling (SEM) & Ease of Use; Compatibility; Technology Acceptance Demographic factors; Relative Model (TAM) Advantage; Social Influence; Perceived risk Source: Adapted & Modified from Ssonko (2016)

As indicated in Table 1, most factors which have been studied are theoretical constructs from technology adoption theories. CGAP (2013) states that more than 180 variables were identified and created as factors which influence mobile money adoption. The categorisations of the factors were (i) macro-level factors such as national wealth, the vitality of the banking sector, and the level of investment from mobile network operators (MNOs); and (ii) individual drivers like the strength of the agent network in close proximity to a subscriber, and the subscriber’s usage of different types of MNO products (CGAP, 2013). Heyer and Mas (2009) observe that the adoption and continued usage of MMSPs in developing countries are shaped by environmental dynamics such as extent of market penetration and political environment over and above MMSP’s strong strategy and good business models. Pal, De, Herath and Rao (2019) note that contextual variables both environmental and cultural aspects can be enhancers and / or barriers to uptake and continued usage of MMS. In this paper, macroeconomic data about various drivers of adoption and continued usage of MMS namely, products and services offered; transactional 9

costs; taxation regime; reliability of mobile network infrastructure; activity of accounts; as well as number and volumes of transactions are examined. Descriptive statistics are used to analyse how these factors are likely to shape uptake and continued usage in the post COVID-19 period.

3.2 Disruptions may be either enhancers or barriers to DFS adoption and usage The factors influencing uptake and usage of mobile money services have been categorised into either enhancers (positive drivers) and barriers (inhibitors). The enhancers are usually derived from technology adoption theoretical frameworks. The enhancers include constructs such as perceived usefulness, perceived ease of use, and system quality. In a bid to examine contextual environmental variables, scholars have investigated the barriers or hinderances to adoption of Information Systems such as mobile money. As a result of including contextual factors in technology uptake models, variants of the most popular technology adoption theoretical framework (Technology Adoption Model – TAM) such as TAM 2 and the Unified Theory of Acceptance and Use of Technology (UTAUT) (Zhou, Lu, & Wang, 2010; Venkatesh & Davis, 2000) have been devised. Musa, Meso, and Mbarika, (2005) state that most of the research work done about technology adoption theoretical frameworks has occurred in developed countries. In these Advanced Economies researches, there is an inherent assumption in the technology uptake model which is; technology is readily available and the choice of whether to use or reject use is individual focused which is not the reality in Sub- Saharan Africa (Musa, Meso, & Mbarika, 2005). Meso and Musa (2008) as well as Meso, Musa, Straub and Mbarika (2009) observe that individual choice is limited by socio-economic realities such as telecommunications infrastructure that are vital to the day-to-day use of modern technologies. Table 2 provides a synopsis of some of the barriers to mobile money uptake and usage in developing countries’ contexts. Table 2: Barriers of Mobile Money adoption and usage from Literature Author Methodology Barriers Country & Data Used Davidovic, Prady, and Qualitative (Blog) Lack of mobile coverage; Lack Not indicated Tourpe (2020) of easy access to money agents; Inadequate access to electricity; Exchanging mobile money for cash can be expensive; Digital and Financial illiteracy

Xiao and Chorzempa Qualitative (Blog) Infrastructure (Identity, Internet China; Secondary (2020) access, and Legacy Payment Systems); Financial and Economic Costs of DFS e.g. data privacy costs; Market Structure (Monopoly / Duopoly / Oligopoly)

Author Methodology Barriers Country & Data Used Dzokoto and Mensah Qualitative & Technology Distance from banks or agents Ghana; Primary (2012) Acceptance Model (TAM) (accessibility); Geographical location of members of household; Price strustructures; Trust; Historical relationship of people with money; Technological glitches / infrastructural bottlenecks e.g. power cuts; Knowledge gaps about mobile money; ambivalence attitude towards mobile money; failure of other cashless payment systems in the past; inadequate income; security (fraud & theft, network issues, and losing gadget); few agents; competition from TBMFIs; fear of overspending on account of electronic nature of money in DFS

Otieno, Liyala, Odongo Qualitative Lack of national identity cards by Kenya; Primary & and Abeka (2016) potential users; few mobile Secondary money agents; Inadequate cash and floats at mobile money agents; language barrier; Inadequate awareness and lack of information on how to access and operate certain features in mobile money platforms; preference for cash transactions over cashless transactions

Mulwa and Ngigi (2018) Survey Inefficiency of shops due to lack Kenya; Primary of enough electronic money to facilitate loading of mobile money wallets; Insecurity of funds; Cost of transactions; Access to outlets; Inability to transact; Do not trust assistants

Iliasov (2014) Qualitative Awareness of MM; Limited Nigeria; Primary knowledge about MM; Low level of trust

Murray (2016) Qualitative and Survey Digital illiteracy; Risk of account Ethiopia; Primary deactivation discouraged experimentation; network & electricity problems; Limited knowledge of mobile money products; Queuing at agent; Highly vulnerable participants prioritise immediate

Author Methodology Barriers Country & Data Used consumption over MM usage Khan and Goldstein Qualitative Lack of awareness; Lack of trust Pakistan; Primary (2014)

Disruptions may be categorised as climate change induced, technological, financial / economic, as well as geopolitical and their effects may be systemic or localised (Ssonko & Kawooya, 2020). Disruptions may be barriers or enhancers to adoption and usage of digital financial services. According to von Allmen, Khera, Ogawa and Sahay (2020), the COVID-19 disruption will likely increase DFS usage. However on the downside, it is likely to stiffle the growth of the fintech industry’s smaller players through constraining funding opportunities and exacerbating unequal infrastructure access (von Allmen et al., 2020). Von Allmen et al. (2020) note that fintechs will face challenges such as tightening of funding, rising non performing loans, and decline in volume and value of transactions including credit demand. IV. Drivers of Digital Financial Services before COVID-19 4.1 Infrastructure Infrastructure has been defined broadly to include aspects such as access to electricity; mobile and internet coverage / connectivity; number of gadgets; possession of national identity documents for Know Your Customer (KYC) purposes; legacy of payment systems; as well as status of data privacy & protection (von Allmen et al., 2020; Davidovic et al., 2020; Xiao & Chorzempa, 2020; Frankfurt School of Finance & Management gGmbH, 2020:18). Infrastructure was one of the issues identified by the stocktaking survey of the country’s payment system in 1998 by the then Bank of Uganda National Payment Systems Secretariat (Bank of Uganda Annual Report 1998/1999:61).The survey intended to provide context to the National Payment Systems Strategy which was designed to support the modernisation of payment systems had the following major findings:- “a narrow payment instrument base; inadequate legal, communication and energy infrastructure; a preponderance of debit instruments over credit instruments; and inadequate risk management.” 4.1.1 Access to Electricity Access to electricity is key on account of the fact that most DFS gadgets such as ATM deployments, mobile phones, and MNO cell sites etc. rely upon electricity to function (Frankfurt School of Finance & Management gGmbH, 2020:18). Electricity access is a challenge in both rural and urban areas in developing countries (Frankfurt School of Finance & Management gGmbH, 2020:18). Figure 1 shows the evolution of access to electricity (defined as the percentage of population with access to electricity) in Uganda from 1991 to 2018 (World Bank Data, 2020). The urban-rural divide is evident in electricity access.

Figure 1: Evolution of access to electricity in Uganda from 1991 to 2018

Source: World Bank Data (2020) Access to electricity is key on account of the fact that most DFS gadgets such as ATM deployments, mobile phones, and MNO cell sites etc. rely upon electricity to function (Frankfurt School of Finance & Management gGmbH, 2020:18). Electricity access is a challenge in both rural and urban areas in developing countries (Frankfurt School of Finance & Management gGmbH, 2020:18). Figure 1 shows the evolution of access to electricity (defined as the percentage of population with access to electricity) in Uganda from 1991 to 2018 (World Bank Data, 2020). The urban-rural divide is evident in electricity access. The proportion of the urban, rural, and entire population with access to electricity increased to 57.50%, 38.02%, and 42.65%, respectively in 2018 from 33.60%, 1.98%, and 5.60% in 1991 (World Bank Data, 2020). These low electricity access figures are further underscored by Ikonjo- Iwela (2016) who points out that Uganda’s per capita energy consumption of 3.7kWh is one of the lowest in the world. The inadequate access to electricity is one of the primary causes of huge discrepancies in urban–rural internet use and mobile phone penetration rates in Uganda (Gillwald, Mothobi, Ndiwalana & Tusubira, 2019:iv). 4.1.2 Internet Connectivity Even though mobile money can be delivered without internet connectivity via channels such as Unstructured Supplementary Service Data (USSD) and Short Messaging Services (SMS)-based means (Frankfurt School of Finance & Management gGmbH, 2020:26), internet connectivity is key for the delivery of certain value added services and m-commerce or e-commerce. Table 3

summarises key metrics about mobile phone coverage and internet connectivity in Uganda. Internet connectivity is increasing partly driven by uptake of mobile data subscriptions. Table 3: Mobile Subscriptions and Internet Penetration as at September 2019 Key Indicators Q4 2018 Q1 2019 Q2 2019 Q3 2019 (December (March (June 2019) (September 2018) 2019) 2019) Mobile Subscriptions 24,472,033 24,613,995 24,456,617 25,603,296 Fixed line Subscriptions 186,780 197,597 203,132 145,521 Teledensity (%) 63.0 62.0 63.6 63.9 Internet Subscription 14,360,847 14,383,483 15,155,921 15,261,314 (Mobile) Internet Subscription 9,485 9,597 9,929 11,144 (Fixed) Internet Penetration (%) 36.8 35.7 37.6 37.9 Estimated Internet Users 21,636,121 21,670,395 22,833,172 23,003,411 Source: UCC (2020).

4.1.3 Mobile or Cellular Phone Penetration According to the National IT survey 2017/2018 carried out by CIPESA (The Collaboration on International ICT Policy for East and Southern Africa) under the ausipices of the National Information Technology Authority Uganda (NITA-Uganda) which sampled 2,400 individuals / households, mobile phone ownership is summarised as indicated in Table 4. Table 4: Mobile Phone Ownership in Uganda Categorisation Percentage Of all individuals, those who own mobile phones 70.9% Of individuals who own mobile phones, those who own smart phones 15.8% Of all individuals, those who do not own a mobile phone 29.1% Of individuals who owned a mobile phone but did not share their phone with 64.2% anyone Of individuals who did not own mobile phones, but owned an active SIM card 27.4% Of individuals who did not own mobile phones, but had used someone’s phone in 72.0% the past three months Source: CIPESA (2018:130) There has been an improvement in mobile phone ownership over the years as shown in Table 5. However, gaps remain such as digital features phones compared to smartphones; urban/rural, and female/male. However, the share of smart phones in the total mobile phone ownership is one of 14

the lowest in Africa (Gillwald et al., 2019:iv). In addition, phone sharing is also still practiced just like in other African countries (See Sey, 2008). Table 5: Trends in mobile phone ownership Survey All Rural Urban Female Male Individuals NITA-Uganda YES 70.9% 65.7% 78.5% 63.2% 81.6% 2017/2018 NO 29.1% 34.3% 21.5% 36.8% 18.4% Uganda YES 52.3% 46.6% 77.9% 44.4% 61.6% Communications Commission NO 47.7% 53.4% 22.1% 55.6% 38.4% (UCC) 2014/2015 Source: CIPESA (2018:131) 4.1.4 Possession of National Identity Documents for KYC Identification documentation is key for fostering financial inclusion through support for Know Your Customer (KYC) / Customer Due Diligence (CDD) (Frankfurt School of Finance & Management gGmbH, 2020:20). Despite its critical nature, in many developing countries, it remains a major limiting factor (Frankfurt School of Finance & Management gGmbH, 2020:20). By 2016, 14.8 million Ugandans had registered for a National Identification Number (NIN) / National Identification Card (NIC) (Handforth and Wilson, 2019:3). The 14.8 million NICs are way below the population of Ugandans 15 years and above which stood at 24,692,872 as at 2020 (PopulationPyramid.net, 2019). However, replacement of the NIC one lost requires one to wait for at least 60 days and travel to the capital city in Kampala (Handforth and Wilson, 2019:3). In 2017, Government of Uganda (GoU), as part of its national security measures, embarked on an exercise of ensuring that every Subscriber Identification Module (SIM) card of an individual gets validated and verified for purposes of ensuring secure and safer communications. The primary identification document for Ugandan citizens was the NIC. As such, the Uganda Communications Commission (UCC) sought to enforce this requirement, instrucing all telecom providers to ensure mandatory sim card registration. A deadline was set, although this was extended several times. Without a NIC, a Ugandan citizen’s SIM card should ideally not be registered on any Mobile Network Operator’s platform. Similarly, in February 2019, Bank of Uganda issued a directive making the NIC the primary identification document for KYC purposes in all financial institutions under its supervisory purview. Though intended to ease identification of financial consumers in the event of liquidating a financial institution and payout of account insurance monies by the Deposit Protection Fund of Uganda (DPFU), the use of the NIC for KYC purposes whether updating existing financial products access and / or setting up to access new ones is now mandatory. In order to ease NIC verification by supervised financial institutions (SFIs), in January 2020, Bank of Uganda (BoU) together with the UBA, National Identification and Registration 15

Authority (NIRA) and Laboremus launched a shared E-Gateway between NIRA, SFIs, and BoU that would improve on the process of the verification and authentication of SFIs current and prospective customer information against records maintained by NIRA (BoU, 2020). A good proportion of individuals provided mobile money account numbers as the alternate payment channels which could be used in settling insurance monies in case of liquidation of a supervised financial institution. As a consequence, a bulk of customer accounts in SFIs had a registered mobile phone number attached to them, and this made the enrollement onto digital / mobile banking rather seamless. 4.1.5 Legacy of Payment Systems At the time of the advent of mobile money services in Uganda in March 2009, automation of the payment systems had been around for about a decade with the first Automated Teller Machine (ATM) having arrived in 1997. As indicated in Table 6, the bulk of these automations focused on wholesale payment systems. Thus, the advent of mobile money in March 2009 which is primarily a retail payment system did not have serious competition to contend with. In fact, the issues of public policy discussion focused on mobile money security and interoperability across networks and with wholesale payment systems. Table 6: Major Milestones in Uganda’s Payment Systems Automation Drive prior to advent of mobile money in March 2009 Time Period Milestone 1997 First ATM introduced in Uganda by Standard Chartered Bank February 1998 Bank of Uganda resolves to modernise country’s payment systems – Administrative structure and Strategy devised 1998/1999 Survey to stocktake status of payment systems in Uganda – cash was dominant; cheques major non-cash instrument; low usage of electronic instruments; inadequate regulatory framework etc. 1999 National Cheque Standard adopted to harmonise cheques issuance, quicken clearing of cheques, and minimise cheque frauds May 2002 Electronic Clearing System (ECS) - All clearing banks submit cheque data to the clearinghouse in electronic form and the electronic data is then fed into the ECS for derivation of net clearing positions, and generation of inward electronic cheque data for each bank. February 2005 Uganda National Interbank Settlement (UNIS) system, a Real Time Gross Settlement (RTGS) system implemented July 2007 Capping of cheques – regulatory upper limit on the amount on cheques (UGX20million) February 2007 Implementation of EFT Direct Debit for school fees Source: Bank of Uganda Annual Reports 2001/02; 2000/01; 1998/99; Ogwang (2009:10-11)

4.1.6 Status of Data Privacy and Protection One of the issues that the G20 High-Level Principles for Digital Financial Inclusion 2016 emphasise is the need for consumer data protection and privacy (GPFI, 2016). In Uganda, data protection is safeguarded under the Data Protection and Privacy Act 2019 that seeks to “protect the privacy of the individual and of personal data by regulating the collection and processing of personal information”. While the data collected by MNOs is safeguarded through Information Communication Technology (ICT) security measures such as Personal Identification Numbers (PINs) deployed on the mobile money platforms, there is a loophole at agents’ premises. Most mobile money agents leaving records of mobile phones and associated transactions visible to all financial consumers who patronise their kiosks presents a major risk of unauthorised exposure of personal information. In addition to agents’ inadvertent release of financial consumer information, there are practices which are done which further compromise data privacy. These include writing PINs on calendars and walls alongside cellular phone numbers; sharing PINs with mobile money agents, relatives, and money lenders; use of PINs which are easy to decipher such as birthdays; accepting help from strangers at mobile money agents’ kiosks thereby exposing your PIN; and helping strangers register SIM cards using one’s NIC. 4.1.7 Stakeholders of MMSPs There mobile money ecosystem exists only through the collaboration between MMSPs and a diverse arrangement of stakeholders from several sectors including IT, finance, telecommunication, customers, merchants and the regulatory authorities. All these work together to deliver DFS in Uganda. The interests of these stakeholder are diverse, however most of them enjoy a symbiotic relationship and the roles they play are discussed in the subsequent paragraphs. i) Agents: The success of MMSPs depends on heavily accessibility and availability. The agent remains the principal access channel and face of mobile money most especially for agent-centred transactions such as deposits, withdrawals, and in very limited cases, SIM card registration. The agent usually earns a commission from the MMSP for the services rendered to their customers. By February 2020, the total number of mobile money agent points across the country stood at 396,731, which is impressive compared to the approx. 91,000 from 5 years ago. These agents are at the moment also 250 fold compared to the combined 1,534 SFI access points (695 SFI and 839 ATMs) reported by the BoU in 2018. ii) Financial Institutions: Supervised financial institutions have took centre stage when MMSPs started owing to the gaps in the legislation. The Financial Institutions Act (2004), which empowers the central bank to intervene in financial sector matters, especially those invlolving mobilisation of some sort of consumer deposits, was silent on the licencing and regulation payment service providers. The middle ground was for this to be done via a proxy and SFIs seemed like a good place to start. SFIs at the start viewed MMSPs as a competitor, but of recent have embraced them and MMSPs very often are augmenting the traditional SFI banking

experience. Customers of the SFIs are able to move funds to and from their accounts to mobile wallets, a process that was impossible 12 years ago. iii) Teleommunication & IT: The MMSP system needs a paltfom to host it, and the most convinient came in the form of telecom. It is no wonder that four of the seven MMSPs in Uganda are innately providers of telecommunication services (both voice and data), and offer mobile money as a secondary service. The telecom interface goes hand in hand with the IT services available, especially as the adoption of smart devices has ecouraged the use of applications along side the traditional USSD option available for mobile money. iv) Customers: These form the core of the business and are the reason MMSPs exist. Their choices, behaviour, attitudes and patterns often influence the uptake of new services on offer. v) Merchants: There is an increasing appetite for merchants to own a merchant codes (line), which is separate from their business or personal mobile money account. Airtel Pay and MTN Momo Pay offer the highest number of merchant codes, although a number of payment solution providers have developed products that utilize the existing mobile money infrastructure, and essentially create a separate series of merchant codes. The merchant codes of other providers other than MTN and Airtel are not as wide spread. 4.1.8 Legislative Framework – Policy & Regulations From the onset, it was clear that the service being proposed by the first MMSP was a financial service. Even though the provider was a telecom under the jurisdition of the Uganda Communications Commission (UCC); there was general agreement that this service was better supervised by a financial regulator, BoU. However, the existing legislation at the time did not enable the BoU to fully licence and regulate the service. The middle ground was for the issuance of a “letter of no objection”, following a lengthy survey process by the BoU. The main concern of the BoU remains the safety of public mobilised funds that are used to create electronic value. MMSPs are required to partner with a supervised financial institution (under BoU jurisdiction), usually deposit taking, and must hold an escrow account in the latter which should at all times match the electronic value that has been extended to all their customers and agents. However, there are other entities that provide payment solutions, including FinTech companies that offer DFS and are neither regulated by BoU nor UCC. As an interim measure, the BoU issued the 2013 Mobile Money Guidelines, in the absence of a clear legislation on the regulation of mobile money. The National Payment Systems Law which was passed by Parliament on May 28, 2020 and assented to by the President on July 29, 2020 is set to be a game changer with regard to MM regulation. 4.1.9 Institutional Framework – MMSPs Ecosystem Given the dual regulatory regime in DFS, and more specifically for MMSPs, the importance of institutional mapping on the regulatory side is critical for the success of the sector. It is standard practice for regulators to enter into Memoranda of Understanding (MoU) to mainly exchange regulatory information and also provide for other regulatory issues in which they can collaborate.

The same can be said for BoU and the UCC, who entered into a MoU, on which the oversight role for mobile money in Uganda was built upon. On one hand, the main concern of the BoU is deposit taking and financial intermediation which is a business liable for regulation under the Financial Institutions Act (FIA) 2004 as amended in 2016. However, the law stipulates that the persons being regulated must be one of the categories of financial institutions that BoU can supervise. Unfortunately, telecoms, which were the main providers of mobile money did not meet this criteria, as such, a strategy was taken to supervise these by proxy. MMSPs were required to partner with an SFI. The partnership would be vetted and approved by the BoU if all requirements were met. On the other hand, the UCC is positioned to regulate telecom providers to provide mobile money as a value added service. In addition, it is responsible for ensuring network availability (network system uptime), which is necessary for mobile money services to run. UCC has also to ensure that there is no unfair competition in which that telecoms neither lock out, nor unfairly charge other mobile money service providers who wish to use their networks. With the assent of the National Payment Systems Law, BoU is poised to become the regulator for payment systems. BoU already sits in the Financial Stability Surveillance Committee (FSSC) It is thus an advantage that issues of payment sytem over sight will be brought to the forefront of discussions amongst financial sector regulators. With the numerous and fast changing advances in technology, and by extension payment systems, disruptions in one segment the market could spread quickly throughout the financial sector and put the whole system at risk. As such a payment system regulator working closely with other established institutions allows smoother functioning of the sector. 4.1.10 User Interfaces and Security The successful adoption of mobile money has very much depended on a user interface that was designed to match the technological capabilities of the region and adaptability of users at the time. While smartphones have become more prevalent for today’s urban user today than they were a few years ago, MMSPs still largely deliver their service via Unstructured Supplementary Service Data (USSD). The USSD is a protocol used by GSM4 cellphones to communicate with their service provider's computers via text messages. MMSPs have continued to provide their servies using this simple user interface. It is required that the customer approves the transaction using a 4 or 5 digit code Personal Identification Number (PIN/Code), depending on the provider. Of recent MMSPs provide confirmation details such as name of reciepient, merchant name or account title in the case of utilities, before a user approves any transaction over their mobile money account. This is to prevent funds transfer to the wrong beneficiary, for which a reversal is not instant.

4 Global System for Mobile Communications, a standard that describes protocols for second-generation (2G) digital cellular networks used by mobile devices such as mobile phones and tablets. 19

4.2 Services provided by MMSPs According to Ssettimba (2016), the services which were being offered by mobile money service providers as at March 2016 are indicated in Table 7. Over the last 54 months (4.5years), financial widening has taken place and newer products / services have been devised by MMSPs. Some of these are merely automation of financial services / products provided by TBMFIs while others are innovative solutions to address needs of the public which may not have existed in the TBMFIs space. In this section, the services examined include person-to-person (P2P); deposits; withdrawals; bank-to-wallet (B2W); wallet-to-bank (W2B); bill and merchant payments; as well as cross border remittances. Table 7: Current Mobile Money Services being offered in Uganda [as at March 2016] Product / Service Status Domestic transfers Live

Merchant Payments – enabling Small Medium Enterprises and Corporates to receive payments (P2B) Live Statutory Payments (Taxes) P2G Live

Bulk Payments: Salaries, Wages, B2P e.g. Sugar, Tea, and Construction Firms Live

Micro Loans and Savings Pilot Group Wallets for SACCOs and VSLA Pilot

Cross border Live

Mobile Banking transfers from bank account to M-Wallet Live

Government Payments (Social Benefits) G2P Live Source: Ssettimba (2016) The section below reflects the services offered by MMSPs as at February 2020, which has been considered a cut off date for the pre-COVID analysis. 4.2.1 Person-to-Person Peer to Peer or simply put personal transfers, involve the movement of funds between two parties using their mobile money accounts. This was the first service on offer when mobile money rolled out in March 2009. By February 2020, there were 11.573 million P2P transactions worth UGX822.49 billion up from 6.062 million transactions worth UGX404.80 billion recorded in August 2018 (date when P2P was first reported to BoU by MNOs). 4.2.2 Deposits Deposits, also referred to as Cash-In within the mobile money ecosystem, are defined as funds handed over to a mobile money agent in order to to acquire electronic value (e-value) colloquially known as float. By February 2020, there were 46.598 million deposit transactions worth UGX1,984.640 billion up from 27.961 million transactions worth UGX1,355.209 billion in August 2018.

4.2.3 Withdrawals These are also referred to as cash out and represent the volume and value of funds received from an agent when a customer decides to convert the e-value held on the Subscriber Identity Module (SIM) card into physical cash. This action reduces the e-value balances on a given customers’ mobile money account. Mobile Money Service Providers (MMSPs) prefer that customers customer use their mobile money balances to meet and settle obligations electronically other than withdrawals. Consequently, the cost structure is such that the withdrawal charges are often prohibitive to dissuade customers from drawing their accounts to zero balances. By February 2020, there were 27.751 million withdrawal transactions worth UGX1,858.051 billion up from 19.821 million transactions worth UGX1,313.815 billion in August 2018. 4.2.4 Bank to Wallet (B2W) The B2W is a service that allows bank clients to transfer funds from their bank account to a mobile wallet (mobile money account). This service was introduced many years later and caters for fund transfers between the traditional brick and mortar financial institution (TBMFI) and MMSPs. By February 2020, there were 901,152 B2W transactions worth UGX174.465 billion up from 616,525 B2W transactions worth UGX102.247 billion in August 2018. 4.2.5 Wallet to Bank (W2B) Wallet to Bank (W2B) is a service that allows mobile money account holders to transfer funds from their mobile wallet (mobile money account) to a bank account. In comparison to B2W, W2B is not very common and remains the preserve of a few. The low uptake of W2B is partly due to the delayed granting of access by TBMFIs to the first layer of information that provides the financial consumer with the capacity to verify account details prior to transacting. By February 2020, there were 188,413 W2B transactions worth UGX76.843 billion up from 57,564 W2B transactions worth UGX14.526 billion in August 2018. 4.2.6 Bill and Merchant Payments (Person to Business– P2B) Mobile Money Service Providers (MMSPs) have made available via their platforms / systems, options for bill payments, most especially for utilities (water, electricity and internet), as well as payments due to merchants as a result of purchases. The latter currently may be seen in the form of Airtel Pay and MTN Momo Pay; which allow the transfer of balances to the merchant without the subscriber incurring costs. By December 2011, both the Uganda Revenue Authority (URA) and the National Water and Sewerage Corporation (NWSC), had phased out cash offices at their respective institutions in a bid to avoid long lines at their premises and improve efficiency in revenue collection. Similarly, in 2014, the electricity distributor Umeme phased out cash payments for power bills in a bid to make it easier for customers to meet their power obligations. At the time Umeme still held 25 cash offices across the country for walk-in customers to use in paying their electricity bills. By February 2020, there were 11,576,315 P2B transactions worth UGX244.786 billion up from 5,573,707 P2B transactions worth UGX99.846 billion in August 2018. The large volume and 21

values registered in the category reflect the breadth of items included therein such as utilities, cable / pay TV, merchant payments (school fees, supermarkets), and government revenues (tax and non-tax) etc. 4.2.7 Cross border remittances Remittances from outside the country can be received on mobile money. MMSPs have provided a safe platform for fast and efficient money transfers from foreign sources. In many parts of the African continent, those wishing to send and receive money across the border still incurr the highest transaction fees globally. As such the mobile money cross-border payments, especially within East Africa provide a cheaper alternative. By February 2020, the volume of inward and outward crossborder flows was 141,366 and 27,661 transactions respectively from 66,456 and 7,821 transactions in August 2018. Similarly, the the value of inward and outward crossborder flows was UGX37.325 billion and UGX3.048 billion, respectively in February 2020 from UGX18.840 billion and UGX0.907 billion in August 2018. 4.2.8 Airtime The purchase and consumption of MNO airtime was done using scratch cards before the advent of mobile money in March 2009. Even after the advent of mobile money, scratch cards remained a major mechanism through which airtime was being consumed. However, in August 2018, Uganda Communications Commission (UCC), a regulatory body of the communications sector in Uganda issued an order to phase out the use of airtime scratch cards which were to be replaced by ‘easy load’ (use of mobile money) (Walubiri, 2019; Kisekka, 2018). Efforts to re-introduce scratch cards by Parliamentarians in 2019 on account of the lack of accessibility to easy load facilities in rural areas did not yield positive results. By February 2020, the number of airtime loading transactions stood at 92,452,892 (worth UGX105.613 billion) compared to 105,180,385 transactions (worth UGX117.158 billion) in August 2018. 4.2.9 Data Data was one of the services which MNOs added onto their business offerings once the average revenue per user (ARPU) from voice sources started to decline on account of increased competition (Musazi, 2010). Despite the perception that the cost of data is high in Uganda relative to other jurisdictions (Daily Monitor, 2019), mobile broad band access and usage is on the rise on account of increasing 4G and 3G coverage, a drop in smartphones and modem prices, and a fall in bandwidth prices (CIPESA, 2018:38). As at September 2017, Uganda had an estimated 18.1 million internet users of which 14.8 million were mobile internet subscribers (CIPESA, 2018:38). The high number of mobile internet subscribers suggests an upward trajectory for data usage. By February 2020, the number of data loading transactions stood at 34,089,830 (worth UGX46.671) up from 4,789,376 transactions (worth UGX13.095 billion) in August 2018.

4.2.10 Loans Digital credit has the potential to enhance financial inclusion (through provision of much needed loans without the bureaucratic process of paper work in TBMFIs) as well as exacerbate financial exclusion (through blacklisting of defaulters of digital micro-loans) (Microsave, 2019). For instance in Kenya, most digital loans are used for consumption purposes increasing the probability of default. Indeed, more than 10 percent of the adult population are negatively listed (Microsave, 2019). This 10 percent translates into about 400,000 people blacklisted for defaulting on loans as low as KES200 (about US$2) and who are now rationed out of the formal credit market (Robinson & Wright, 2016) because providers of micro-loans are obligated to file such adverse / negative information with the Credit Reference System (CRS). In Uganda the Financial Institutions (Credit Reference System) Regulations 2020 which would allow providers of digital credit access to the credit reference services as Accredited Credit Providers and file such information with the credit reference system are yet to be finalised (Bank of Uganda Annual Report FY2018/2019:29 and FY2019/2020). Nonetheless, the repayment rates of digital loans in Uganda are still relatively high. For example, Jumo / Airtel Uganda registered repayment rates in the range of 93% to 95% (Microsave, 2019). However, there are isolated cases of digital credit defaults. For instance a man was arrested for failure to repay UGX400,000/= (US$106) digital loan (Zawedde, 2019). In Uganda, digital credit is extended by two major players, that is, Airtel Uganda Limited’s Wewole (Airtel Uganda Limited, 2020; 2017) and MTN Uganda Limited’s MoKash (MTN Uganda Limited, 2020). as indicated in Table 8. Table 8: Uganda’s Digital Credit Providers Digital Product Partners Accessibili Limits Loan Interest Rate Default Uptake Credit Credit Descriptio ty Terms Repayme Range Penalty Scoring Provider n and and nt Date of Conditions Periods Launch

MoKash Micro MTN MTN Savings Interest on Savings (Tiered 10% on 2000 to Alternati (‘More savings Uganda registered savings is Interest outstandi 4500 ve credit Cash’) and loan Ltd customer UGX50/= to paid Strucure) ng loans scoring product (MNO) UGX10 quarterly amount; disburse (mobile launched and At least 6 million UGX1 to reduced d per day money on August NCBA months UGX300,000/= credit data, and 09, 2016 Bank using Loans 2% amount at 9000 mobile Uganda platform Loan is next new phone Ltd (SFI) UGX3,000/= repayable UGX300,001/= attempt customer data) 18 years & to UGX1 in 30 days to s above million UGX800,000/= registerin 3% g gdaily Opt in by dialing UGX800,001/= *165*5# to UGX1,600,000/ == 4%

> UGX1,600,001/ = 5%

Loans

Digital Product Partners Accessibili Limits Loan Interest Rate Default Uptake Credit Credit Descriptio ty Terms Repayme Range Penalty Scoring Provider n and and nt Date of Conditions Periods Launch

9% per month

Wewole Micro Airtel Airtel Persons 7, 14, and 6.75% to 15% 10% on 1 million Alternati (‘Borrow credit Uganda registered 21 days per month outstandi users per ve credit ’) service Ltd customer UGX8,000/= ng month scoring launched (MNO) to amount; (mobile on March and At least 6 UGX500,000/ reduced money 16, 2017 JUMO months = credit data, and (Non- using amount at mobile Bank platform Agents next phone Institutio attempt data) n) 18 years & UGX100,000/ above = to UGX1,000,000 Opt in by /= dialing *185*8#

Source: Websites of Airtel Uganda Limited and MTN Uganda Limited; Words in parentheses indicate the meaning of the digital credit brand By February 2020, the number of loan disbursements stood 549,111 transactions (worth UGX58.081 billion) up from 428,031 transactions (worth UGX20.871 billion) in January 2019. Similarly, the number of loan repayments rose to 1,405,518 transactions (UGX61.511 billion) in February 2020 from 1,019,436 transactions (worth UGX20.237 billion) in January 2019. Overall, mobile network operators offer a plethora of other services which have not been examined in this paper. These include Business-to-Business (B2B); Busines-to-Person (B2P); Agent-to-Agent (A2A); insurance; as well as money transfer to non-users of mobile money. AFI (2019) provides a full list of all services offered via mobile money services. Nonetheless, the quality of data could benefit from further disaggregation into clearly defined groupings namely, Business-to-Business (B2B); Business-to-Government (B2G); Business-to-Person (B2P); Government-to-Business (G2B); Government-to-Person (G2P); Person-to-Business (P2B); Person-to-Government (P2G); and Person-to-Person (P2P) (Frankfurt School of Finance & Management gGmbH, 2020:8). 4.3 MMSPs Surcharges 4.3.1 Charges of MMSPs The MMSPs charge for the different services rendered as indicated in Appendix 8.2. The fees vary across networks. The MMSPs have structured their tarrif plan in tiers. The design of the charge structure is such that a financial consumer pays more per unit Shilling transacted (sending or withdrawing) at lower tiers compared to the higher tiers. In addition, the MMSPs do not charge for deposits but charge for withdrawals with higher fees for monies being accessed from a competing MMSP. Furthermore, withdrawing money from an

agent is cheaper than accessing it from an ATM. Similar patterns are reflected in the sending of money in P2P, W2B, and cross border transactions. 4.3.2 Cost-Benefit Comparison of DFS and TBMFIs In a study by Ssonko and Tait (2018), it was observed that The nature of the data submitted by commercial banks to the Central Bank of Uganda showed that the wholesale payment systems namely, ATMs, cheques, bank drafts, telegraphic transfers, RTGS, and EFT were not comparable to retail payment systems in terms of pricing structure given that the latter has a multi-tiered charge system while the former has a lumpsome charge system. Nonetheless, both the pricing structure of retail and wholesale payment systems share one common trend namely, the unit cost of transacting across the platforms decreases with increases in the amounts transacted. This observation concurs with earlier studies such as Mohapatra (2011) who found that unit remittance costs decreased with an increase in the amount transferred across a particular payment system. The data used in the above study was administratively collected as at 2016. Nevertheless, the trend has not changed in the last four years. However, as shown in the Appendix 8.2, while MMSPs charge for payment for services like pay TV / cable TV and other utilities, TBMFIs do not charge for such deposits. This is explained by the fact that MMSPs are merely payment channels who do not intermediate funds which go through their platforms while TBMFIs are deposit taking and would benefit from deposits made by financial consumers paying for utilities through the credit creation process. Furthermore, TBMFIs have adopted the multi-tiered charge structure for ATM services mimicking the strategies deployed by MMSPs. 4.4 Taxation Uganda’s taxation of its digital financial services especially the mobile financial services component is examined in a policy brief by Stork and Esselaar (2018). The implications on the tax base, Gross Domestic Product (GDP), financial inclusion, and employment are explored in the policy brief. Uganda’s ICT sector taxes are shown in Table 9. Table 9: ICT sector taxes in Uganda Product / Service April 2002 July 2005 July 2014 July 2018 Airtime 7% 12% 12% 12% Value Added Service (VAS) 20% 20% Landlines 5% 12% International Calls** US$0.09 US$0.09 per minute per minute Mobile money fees 10% 15%

Product / Service April 2002 July 2005 July 2014 July 2018 Value of mobile money payments, 0.5% transfers, and withdrawals* Social Media Tax UGX200/= per day Source: Modified from Stork and Esselaar (2018:1); * Originally 1 percent and covering all MM transactions but was lowered to 0.5% and focused strictly on withdrawals; ** Calls from Kenya, Rwanda, and South Sudan are exempt in the 2018 amendment Using an example of the monthly social media tax of UGX6,000/=; Stork and Esselaar (2018:9) suggest that on average 71 percent of a customer’s communications budget would be spent on tax before even consuming data or airtime. Similarly, GSMA (2008:11) cited in Musazi (2010:19) ranks Uganda’s airtime as the most taxed out of 16 countries in Sub-Saharan Africa with 18 percent VAT (Value Added Tax) and 12 percent in other airtime specific taxes. Stork and Esselaar (2018:6) note that mobile money is highly price elastic and the July 2018 introduction of mobile money transaction tax of 1.0 percent led to a price hike (unweighted average) of between 4.7 percent (Airtel) and 71 percent (MTN) with a disproportionate increase experienced in transacting higher amounts. The mobile money transaction tax led to the transaction values declining more than the number of transactions suggesting discrimination against higher value transactions (Stork and Esselaar, 2018:6). Furthermore, the mobile money transaction tax threatened the trust and simplicity associated with mobile money and the resultant “increase in transaction costs made mobile money unaffordable to the poor, incentivising cash use and weakening tax complaince” (Stork and Esselaar, 2018:7). By February 2020, there were 8,876,012 Over the Top (OTT) tax also known as social media tax transactions worth UGX4.418 billion from 6,738,782 transactions worth UGX4.192 billion in August 2018. Nonetheless, in FY2018/2019, OTT raised UGX49.5 billion out of an expected amount of UGX284 billion (about 17 percent performance) (Daily Monitor, 2019). A similar pattern was repeated in FY2019/2020 on account of the fact that 7.6 million mobile internet subscribers do not pay OTT (Lyattu, 2020). Only 11.3 million mobile internet subscribers pay OTT out of 18.9 million subscribers with the rest evading the tax through use of virtual private networks (VPNs) and / or WiFi (which is not subject to OTT). 4.5 Number of registered and active customers Financial inclusion is a multi-dimensional concept which focuses on access, usage, and quality etc. The number of registered users is a reflection of access while active customers (individual who has performed at least one transaction using mobile money in the last 90days) is indicative of usage. The number of registered users has steadily grown from 10,011 individuals in March 2009 (advent of mobile money in Uganda) to 27,529,017 consumers in February 2020. Similarly, the number of active mobile money accounts stood at 17,322,229 in February 2020 up from

14,030,577 in August 2018. Active accounts in a month followed a similar trajectory rising to 13,322,123 in February 2020 from 10,433,580 in August 2018. 4.6 Volume and Value of Transactions The number and value of transactions rose to 263,417,445 transactions worth UGX6,954.783 billion in February 2020 up from 11,016 transactions worth UGX0.489 billion in March 2009. 4.7 Balances on Customers’ Accounts The balances on customers’ accounts rose to UGX697.827 billion in February 2020 from UGX0.601 billion in March 2009. This is on account of the increased uptake of mobile money services and rise in trust by users. V. Drivers of Digital Financial Services during COVID-19 During the COVID-19 pandemic, the infrastructure and taxation regime for MMSPs did not change. However, there were changes to the financial services offered on account of the responses the industry took to shield the financial consumers against COVID-19. The subsequent paragraphs examine how COVID-19 shaped the industry. The COVID-19 era for Uganda is assumed to have commenced in March 2020 with the first case having been reported on March 21, 2020. 5.1 Responses by the Industry to minimise and / or mitigate impacts of COVID-19 on DFS 5.1.1 Business Continuity and Risk Mitigation measures underpinned the Industry Responses During the pandemic, it was imperative that DFS be promoted in a bid to prevent the spread of the virus by limiting person-to-person contact as well as adhering to social distancing norms. Generally, financial services providers including both Traditional Brick and Mortar Financial Institutions (TBMFIs) and fintechs implemented measures aimed at safeguarding their staff and financial consumers against contracting the COVID-19 disease as well as ensuring that the business continued. In line with the Uganda National COVID-19 taskforce, the FSPs provided personal protective equipment (PPE) to staff who stayed working on-site; moved several staff to work off-site; and shortened work days from 08:00hours-17:00hours to 09:00hours-15:00hours. Furthermore, FSPs provided handwashing / sanitisation facilities on-site; undertook temperature monitoring using infrared thermometers for all stakeholders who accessed the premises; and regular tests for symptomatic staff amongst others. In order to continue supporting their financial intermediation business, FSPs moved a lot of their financial services business onto digital channels. Indeed, even the credit relief and loan restructuring measures introduced by Bank of Uganda effective April 01, 2020 through March 31, 2021 could be negotiated and agreed remotely with physical signing of paperwork being undertaken much later.

5.1.2 Collaboration amongst the Regulators and Industry Stakeholders shaped the COVID- 19 Responses The efforts to support the financial services sector to continue undertaking the role of financial intermediation and the broader economy to sustain residents’ livelihoods during the COVID-19 pandemic involved a diverse group of stakeholders including financial services providers (FSPs); member association of FSPs; Mobile Money Service Providers (MMSPs); Bank of Uganda (BoU); Ministry of Finance, Planning and Economic Development (MoFPED); and development practitioners like Financial Sector Deepening Uganda (FSDU) etc. Uganda Bankers’ Association (UBA) was the first to respond when the national lockdown was instituted through a Presidential pronouncement. The UBA is an umbrella organisation, established in 1981 and is currently made up of 35 members (All 25 licensed Commercial Banks, as well as 5 Tier II and III FSPs, Uganda Development Bank, and East African Development Bank). UBA’s proposed mechanism of tackling COVID-19 covered precautions to safeguard people against the disease; business continuity to minimize disruptions of bank operations; contingency plans to monitor liquidity and minimize credit risk; as well as support to ensure smooth flow and running of payment processes and access points including alternative electronic / digital channels (UBA, 2020). Specifically, the operationalization of the framework entailed UBA members “reviewing payment related tariffs to cushion customers during [the] difficult [COVID-19] period and minimize congestion at traditional service points”. The cost reduction entailed the following measures:- a) For a period of 30 days, banks would not charge for the Bank to Wallet (B2W) transactions below UGX30,000/= (approx. US$ 9) per day; b) Charges were waived off for withdrawals made at agency banking terminals for up to UGX50,000/= (approx. US$ 15) for a period of 30 days; c) There would be no withdrawal charges levied for transactions undertaken at the ATM of the SFI for which a customer holds an account, for amounts up to UGX50,000/= for a period of 30 days5; and d) Transactions undertaken on any other online platform up to UGX30,000/= per day, would be zero rated (free of charge) for 30 days. Similarly, Bank of Uganda issued several measures which would enable FSPs navigate the economic shock occasioned by the COVID-19 pandemic. The measures entailed accommodative monetary policy stance; readiness to intervene in the foreign exchange market to smoothen volatility; macro-prudential policy measures (COVID Liquidity Assistance Program – CLAP); micro-prudential policy measures (credit relief and loan restructuring); moratorium on payment of dividends for 90 days; and moral suasion (encouraging MMSPs to further reduce costs of

5 This clearly excludes transactions carried out by consumers at ATMs other those of their own bank, courtesy of Visa, Master Card, Union Pay and Interswitch, for which interconnectivity charges may apply 28

services, as well as expand the scope and duration of coverage of the reductions) (BoU, 2020a; BoU, 2020b; BoU, 2020c; Daily Monitor, 2020). The Ministry of Finance, Planning and Economic Development (MoFPED) deployed a number of fiscal policy measures to tame the likely impacts of COVID-19 (MoFPED, 2020; GoU, 2020). The Mobile Money Service Providers (MMSPs) initially targeted the lower tiers for reducing P2P transaction surcharges (zero rated). However, the MMSPs later reduced surcharges across the entire spectrum of P2P transactions. The reduction in surcharges lasted from March 21, 2020 through to mid-May 2020. Thereafter, the surcharges were revised upwards to 50 percent of pre- COVID rates. 5.2 Evolution of DFS during COVID-19 5.2.1 Services provided by MMSPs During the pandemic, no new services were created by the FSPs. The subsequent paragraphs provide an analysis of the evolution of existing services. 5.2.1.1 Person-to-Person As shown in Table 10, on average the number and value of transactions were greater in the six months after the official declaration of a COVID-19 case in Uganda compared to a similar period before. The higher outturn of P2P volume and value of transactions was expected on account of the national lockdown and social distancing guidelines which made other channels of remittance relatively inaccessible. Table 10: Comparison of P2P Volumes and Values before and after COVID-19 P2P Volumes and Values 12 6 months 6 months CY 2018 CY 2019 CY 2020 months before after (August to (January {so far} before (September (March December 2019 to (January (March 2019 to 2020 to 2018) December 2020 to 2019 to February August 2019) August February 2020) 2020) 2020) 2020) Volume (No. Sum 119.960 67.324 103.595 31.647 110.833 126.238 of Transactions in Millions) Average 9.997 11.221 17.266 6.329 9.236 15.780

Value of Sum 8,427.502 4,676.81 7,068.241 2,127.991 7,844.789 8,649.434 Transactions (UGX Billions) Average 702.292 779.468 1,178.040 425.598 653.732 1,081.179

Source: Bank of Uganda Mobile Money Statistics 29

5.2.1.2 Deposits As shown in Table 11, on average the volume and value of deposits were lower in the six months after the official declaration of a COVID-19 case in Uganda compared to a similar period before. The lower outturn of deposits volumes and values suggests that as the national lockdown progressed from March 2020 through June 2020, the amounts of deposits declined as most people were no longer earning. The informal sector which employs about 80 percent of the labour force was not operating. Furthermore, other sectors like tourism were also at a stand still. Table 11: Comparison of Deposit Volumes and Values before and after COVID-19

Deposit Volumes and 12 months 6 months 6 months CY 2018 CY 2019 CY 2020 Values before before after (August (January {so far} (March (September (March to 2019 to (January 2019 to 2019 to 2020 to December December 2020 to February February August 2018) 2019) August 2020) 2020) 2020) 2020) Volume Sum 509.999 284.100 267.756 149.428 475.465 366.472 (No. of Transactions in Millions) Average 42.500 47.350 44.626 29.886 39.622 45.809

Value of Sum 21,627.783 11,390.133 10,833.881 7,203.008 20,850.396 14,690.092 Transactions (UGX Billions) Average 1,802.315 1,898.356 1,805.647 1,440.602 1,737.533 1,836.261

Source: Bank of Uganda Mobile Money Statistics 5.2.1.3 Withdrawals As shown in Table 12, on average the volume and value of withdrawals were lower in the six months after the official declaration of a COVID-19 case in Uganda compared to a similar period before. The lower outturn of withdrawals volumes and values suggests that individuals might have decided to maintain the monies received on their mobile money accounts (balances on customers’ accounts) for a rainy day later. Alternatively, the financial consumers might have decided to take advantage of the free digital payments via products like MoMo pay. In addition, the lowered cost of sending money (P2P) might have encouraged movement of monetary value electronically rather than cashing it out.

Table 12: Comparison of Withdrawals Volumes and Values before and after COVID-19 Withdrawals Volumes 12 months 6 months 6 months CY 2018 CY 2019 CY 2020 and Values before before after (August (January {so far} (March (September (March to 2019 to (January 2019 to 2019 to 2020 to December December 2020 to February February August 2018) 2019) August 2020) 2020) 2020) 2020) Volume Sum 317.423 165.108 161.469 105.687 305.654 216.904 (No. of Transactions in Millions) Average 26.452 27.518 26.911 21.137 25.471 27.113

Value of Sum 20,555.799 10,851.984 10,628.250 7,023.012 19,837.297 14,272.742 Transactions (UGX Billions) Average 1,712.983 1,808.664 1,771.375 1,404.602 1,653.108 1,784.093

Source: Bank of Uganda Mobile Money Statistics 5.2.1.4 Bank to Wallet (B2W) As shown in Table 13, on average the volume and value of B2W were higher in the six months after the official declaration of a COVID-19 case in Uganda compared to a similar period before. The higher outturn of B2W volumes and values suggests that individuals moved monies from their bank accounts to mobile wallets to ease transacting during the COVID-19 pandemic. During the COVID-19 pandemic, there was a national lockdown which made accessing TBMFIs physical premises challenging. As a consequence, people took up DFS hence the increased B2W. Table 13: Comparison of B2W Volumes and Values before and after COVID-19 B2W 12 6 months 6 months CY 2018 CY 2019 CY 2020 months before after (August to (January {so far} before (September (March December 2019 to (January (March 2019 to 2020 to 2018) December 2020 to 2019 to February August 2019) August February 2020) 2020) 2020) 2020) Volume (No. Sum 9,769.731 4,708.469 7,203.728 3,555.776 9,469.432 8,964.897 of Transactions in Average 814.144 784.745 1,200.621 711.155 789.119 1,120.612 Thousands)

Value of Sum 1,810.316 914.840 1,453.734 593.234 1,730.058 1,787.546

B2W 12 6 months 6 months CY 2018 CY 2019 CY 2020 months before after (August to (January {so far} before (September (March December 2019 to (January (March 2019 to 2020 to 2018) December 2020 to 2019 to February August 2019) August February 2020) 2020) 2020) 2020) Transactions (UGX Billions) Average 150.860 152.473 242.289 118.647 144.171 223.443

Source: Bank of Uganda Mobile Money Statistics 5.2.1.5 Wallet to Bank (W2B) As shown in Table 14, on average the volume and value of W2B were higher in the six months after the official declaration of a COVID-19 case in Uganda compared to a similar period before. The higher outturn of W2B volumes and values suggests that individuals who sought to save used mobile money platforms to move money into their TBMFIs accounts. Table 14: Comparison of W2B Volumes and Values before and after COVID-19 W2B 12 6 months 6 months CY 2018 CY 2019 CY 2020 months before after (August to (January {so far} before (September (March December 2019 to (January (March 2019 to 2020 to 2018) December 2020 to 2019 to February August 2019) August February 2020) 2020) 2020) 2020) Volume (No. Sum 2,068.362 1,061.820 1,297.616 526.449 2,003.655 1,673.216 of Transactions in Average 172.364 176.970 216.269 105.290 166.971 209.152 Thousands)

Value of Sum 845.400 407.678 846.075 153.225 828.411 996.202 Transactions (UGX Billions) Average 70.450 67.946 141.013 30.645 69.034 124.525

Source: Bank of Uganda Mobile Money Statistics

5.2.1.6 Bill and Merchant Payments (Person to Business – P2B) The P2B constitutes payments for goods and services as well as utilities (cable TV, water, electricity, and solar suppliers). As shown in Table 15, on average the volume and value of P2B were lower in the six months after the official declaration of a COVID-19 case in Uganda compared to a similar period before. The lower outturn of P2B was on account of the fact that during the national lockdown the President had directed the utility companies (Umeme and National Water & Sewerage Corporation) not to disconnect these services even if the clients do not pay. In addition, the shops which use MoMo Pay and Airtel Pay as a means of receiving payment for their goods and services were closed. Table 15: Comparison of P2B Volumes and Values before and after COVID-19 P2B 12 6 months 6 months CY 2018 CY 2019 CY 2020 months before after (August to (January {so far} before (September (March December 2019 to (January (March 2019 to 2020 to 2018) December 2020 to 2019 to February August 2019) August February 2020) 2020) 2020) 2020) Volume (No. Sum 173.888 96.380 78.804 31.336 167.993 101.998 of Transactions in Millions) Average 14.491 16.063 13.134 6.267 13.999 12.750

Value of Sum 2,307.805 1,303.400 1,032.175 498.709 2,146.744 1,472.527 Transactions (UGX Billions) Average 192.317 217.233 172.029 99.742 178.895 184.066

Source: Bank of Uganda Mobile Money Statistics 5.2.1.7 Cross border remittances Inflows / Inward As shown in Table 16, on average the volume and value of inward cross border remittances were higher in the six months after the official declaration of a COVID-19 case in Uganda compared to a similar period before. The higher outturn of inward cross border remittances volumes and values suggests that individuals did receive private flows from outside Uganda during the COVID-19 pandemic to supplement their incomes which had dwindled to zero on account of the national lockdown which led to the closure of all sectors save those considered to be critical such as financial services, agriculture, and health etc.

Table 16: Comparison of Cross border remittances – inflows Volumes and Values before and after COVID-19 Cross border remittances - 12 6 months 6 CY 2018 CY 2019 CY 2020 Inflows months before months (August to (January {so far} before (September after December 2019 to (January (March 2019 to (March 2018) December 2020 to 2019 to February 2020 to 2019) August February 2020) August 2020) 2020) 2020) Volume (No. Sum 1.380 0.775 1.293 0.348 1.315 1.567 of Transactions in Millions) Average 0.115 0.129 0.216 0.070 0.110 0.196

Value of Sum 383.348 215.000 438.956 97.172 352.827 515.159 Transactions (UGX Billions) Average 31.946 35.833 73.159 19.434 29.402 64.395

Source: Bank of Uganda Mobile Money Statistics Outflows / Outward As shown in Table 17, on average the volume and value of outward cross border remittances were higher in the six months after the official declaration of a COVID-19 case in Uganda compared to a similar period before. The higher outturn of outward cross border remittances volumes and values suggests that individuals did send out money to relatives outside Uganda. This was expected given that Uganda has a high number of foreigners from the East African region (Rwanda, Kenya, and South Sudan) working in the country. Given that these countries were also under lockdown, it is not surprising that the outturn for outward cross border remittances was high. Table 17: Comparison of Cross border remittances – outflows Volumes and Values before and after COVID-19 Cross border remittances - 12 6 months 6 CY 2018 CY 2019 CY 2020 Outflows months before months (August to (January {so far} before (September after December 2019 to (January (March 2019 to (March 2018) December 2020 to 2019 to February 2020 to 2019) August February 2020) August 2020) 2020) 2020) Volume (No. Sum 0.239 0.153 0.219 0.046 0.252 0.275 of Transactions

Cross border remittances - 12 6 months 6 CY 2018 CY 2019 CY 2020 Outflows months before months (August to (January {so far} before (September after December 2019 to (January (March 2019 to (March 2018) December 2020 to 2019 to February 2020 to 2019) August February 2020) August 2020) 2020) 2020) in Millions) Average 0.020 0.026 0.037 0.009 0.021 0.034

Value of Sum 27.855 17.691 26.092 5.021 25.692 32.522 Transactions (UGX Billions) Average 2.321 2.948 4.349 1.004 2.141 4.065

Source: Bank of Uganda Mobile Money Statistics 5.2.1.8 Airtime Airtime can be used for making voice calls and / or purchase of data to be used to access the internet thereby being able to use social media platforms like WhatsApp. Table 18: Comparison of Airtime Volumes and Values before and after COVID-19 Airtime 12 6 months 6 CY 2018 CY 2019 CY 2020 months before months (August to (January {so far} before (September after December 2019 to (January (March 2019 to (March 2018) December 2020 to 2019 to February 2020 to 2019) August February 2020) August 2020) 2020) 2020) Volume (No. Sum 1,182.850 588.158 539.626 520.625 1,194.489 731.840 of Transactions in Millions) Average 98.571 98.026 89.938 104.125 99.541 91.480

Value of Sum 1,304.830 647.983 607.372 576.126 1,312.601 826.511 Transactions (UGX Billions) Average 108.736 107.997 101.229 115.225 109.383 103.314

Source: Bank of Uganda Mobile Money Statistics

As shown in Table 18, on average the volume and value of airtime were lower in the six months after the official declaration of a COVID-19 case in Uganda compared to a similar period before. The lower outturn of airtime suggests that individuals might have moved voice calls to other channels like WhatsApp, skype, Zoom, and Microsoft Teams which use internet data. Internet data may be purchased directly. 5.2.1.9 Data As shown in Table 19, on average the volume and value of data were higher (almost double) in the six months after the official declaration of a COVID-19 case in Uganda compared to a similar period before. The higher outturn of data suggests that individuals used more data during the COVID-19 pandemic. This was expected given that a good proportion of individuals were working from home and used platforms like WhatsApp, skype, Zoom, and Microsoft Teams which rely on internet data. In addition, children of urbanites consumed data as their classes were moved online after the Government barred physical face to face classes in educational institutions. Table 19: Comparison of Data Volumes and Values before and after COVID-19 Data 12 6 months 6 CY 2018 CY 2019 CY 2020 months before months (August to (January {so far} before (September after December 2019 to (January (March 2019 to (March 2018) December 2020 to 2019 to February 2020 to 2019) August February 2020) August 2020) 2020) 2020) Volume (No. Sum 215.366 138.147 265.540 50.982 166.556 333.509 of Transactions in Millions) Average 17.947 23.024 44.257 10.196 13.879 41.689

Value of Sum 304.515 192.705 370.962 75.308 247.276 464.469 Transactions (UGX Billions) Average 25.376 32.118 61.827 15.062 20.606 58.059

Source: Bank of Uganda Mobile Money Statistics 5.2.1.10 Loans Loans Disbursements As shown in Table 20, on average the volume and value of loans disbursements were lower in the six months after the official declaration of a COVID-19 case in Uganda compared to a similar period before. The lower outturn of loans disbursements suggests risk averseness on the

part of the digital credit lenders due to the adverse economic status which had been projected to persist through FY2020/2021. Table 20: Comparison of the Volumes and Values of Transactions of Loan Disbursements before and after COVID-19 Loan Disbursements 12 months 6 months 6 months CY 2018 CY 2019 CY 2020 before before after (August (January {so far} (March (September (March 2018 to 2019 to (January 2019 to 2019 to 2020 to December December 2020 to February February August 2018) 2019) August 2020) 2020) 2020) 2020) Volume (No Sum 7.845 3.849 2.496 - 7.763 3.647 of transactions Average 0.654 0.641 0.416 - 0.647 0.456 in Millions) Value of Sum 520.823 327.362 238.590 - 448.513 361.451 Transactions (UGX Average 43.401 54.560 39.765 - 37.376 45.181 Billions) Source: Bank of Uganda Mobile Money Statistics Loans Repayments As shown in Table 21, on average the volume and value of loans repayments were lower in the six months after the official declaration of a COVID-19 case in Uganda compared to a similar period before. The lower outturn of loans repayments is on account of the credit relief extended by MMSPs. Table 21: Comparison of the Volumes and Values of Transactions of Loan Repayments before and after COVID-19 Loan Repayments 12 months 6 months 6 months CY 2018 CY 2019 CY 2020 before before after (August (January {so far} (March (September (March 2018 to 2019 to (January 2019 to 2019 to 2020 to December December 2020 to February February August 2018) 2019) August 2020) 2020) 2020) 2020) Volume (No Sum 17.282 8.836 6.784 - 16.811 9.685 of transactions Average 1.440 1.473 1.131 - 1.401 1.211 in Millions) Value of Sum 501.862 300.647 267.191 - 426.407 393.326 Transactions (UGX Average 41.822 50.108 44.532 - 35.534 49.166 Billions) Source: Bank of Uganda Mobile Money Statistics

According to the Background to the Budget FY2020/2021 page 58, During April 2020, both Airtel and MTN provided some relief to the borrowers who subscribe to their mobile micro credit solutions in a bid to manage the impact of the COVID-19 pandemic that was expected to have adverse effects on incomes and repayment abilities of their customers. Specifically, Airtel removed all penalty fees on customers who would fail to clear the outstanding Wewole loan on the agreed date, allowing them to pay at a later date. Likewise, MTN and its partner Commercial Bank for Africa (CBA), deferred by 30 days, all sanctions for late loan payments and removed charges on moving value between the mobile money and Mokash wallets. These deferments would hold over the next three months. 5.3 MMSPs Surcharges 5.3.1 Charges of MMSPs Though initially planned for low value transactions (below UGX30,000/=) for MTN mobile money (Gilbert, 2020; Obwot, 2020), MTN mobile money and Airtel money, on March 19, 2020, “implemented a zero charge on all Person to Person (P2P) and Mobile Wallet to Bank Transactions for a period of 30 days” (MTN and Airtel Joint Press Statement, 2020). The 30 day period which would have expired around April 19, 2020 was extended to May 25, 2020. Effective May 26, 2020, “all MTN mobile money and Airtel money Person to Person (P2P) transactions on the same network and mobile wallet to bank transactions [surcharges were] gradually re-introduced [initially] at a 50 percent discount to standard tariffs for a period of 30 days” (MTN and Airtel Joint Press Statement, 2020).In addition, all MoMo / Airtel Money Pay transactions between customers and merchants continued to attract zero transaction charges for 30 days from May 26, 2020. By June 26, 2020, the MMSPs had reinstated their normal tariff structure (Gilbert, 2020).

Even though P2P, W2B, and B2W transactions had their surcharges reduced, withdrawing money was charged including the GoU tax of 0.5 percent on each transaction (The Independent, 2020), cross MMSP transactions as well as bill payments amongst others were not subsidized. Such price reduction measures might not necessarily encourage a movement towards a ‘cashless’ society because they foster monetary value movement without necessarily encouraging settlement of transactions electronically. Indeed, the essence of zero charge on P2P and W2B transactions was to reduce the likelihood of contracting COVID-19 from the physical exchange of currency notes (MTN and Airtel Joint Press Statement, 2020). However, in a move intended to shore up its transaction volumes, MTN mobile money cut its withdrawal charges effective November 02, 2020 (Twaha, 2020).

5.3.2 Cost-Benefit Comparison of DFS and TBMFIs Traditional Brick and Mortar Financial Institutions (TBMFIs) did not alter their pricing structure during the COVID-19 pandemic except for B2W and the MMSPs only altered surcharges for

P2P and W2B. As a consequence, the cost-benefit did not change from that described in section 4.3.2.

5.4 Taxation The taxation tracked in this section is “Over-The-Top” (OTT). As shown in Table 22, on average the volume and value of OTT were higher in the six months after the official declaration of a COVID-19 case in Uganda compared to a similar period before. The higher outturn of OTT suggests that more individuals paid the tax to access social media platforms like Whatsapp after the onset of COVID-19. Table 22: Comparison of the Volumes and Values of “Over-The-Top” (OTT) Tax Transactions before and after COVID-19 “Over-The-Top” (OTT) 12 6 months 6 CY 2018 CY 2019 CY 2020 Tax Transactions months before months (August (January {so far} before (September after 2018 to 2019 to (January (March 2019 to (March December December 2020 to 2019 to February 2020 to 2018) 2019) August February 2020) August 2020) 2020) 2020) Volume (No Sum 103.768 53.442 63.629 35.061 97.459 82.031 of transactions Average 8.647 8.907 10.605 7.012 8.122 10.254 in Millions) Value of Sum 53.705 27.036 29.705 21.724 53.088 38.854 Transactions (UGX Average 4.475 4.506 4.951 4.345 4.424 4.857 Billions)

5.5 Number of registered and active customers As shown in Table 23, on average the number of registered customers as well as active customers (monthly and quarterly) were higher in the six months after the official declaration of a COVID-19 case in Uganda compared to a similar period before. The higher outturn suggests that accessibility (registration of new mobile money accounts) as well as usage (activity on a monthly and quarterly basis) were high. It appears that the national lockdown ocassioned by the COVID-19 pandemic drove people to take up and use MMS.

Table 23: Comparison of the Number of Customers before and after COVID-19 Number of Customers 12 months 6 months 6 months CY 2018 CY 2019 CY 2020 before before after (August (January {so far} (March (September (March 2018 to 2019 to (January 2019 to 2019 to 2020 to December December 2020 to February February August 2018) 2019) August 2020) 2020) 2020) 2020) Registered Sum 313.977 161.478 172.195 120.288 306.633 226.996 Customers (Millions) Average 26.165 26.913 28.699 24.058 25.553 28.374

Registered Sum 191.152 98.607 107.890 70.895 187.105 142.184 Customers - Active in Average 15.929 16.434 17.982 14.179 15.592 17.773 90days (Millions) Registered Sum 145.972 75.985 83.637 54.006 142.511 109.726 Customers - Active in Average 12.164 12.664 13.939 10.801 11.876 13.716 30days (Millions) Source: Bank of Uganda Mobile Money Statistics

5.6 Volume and Value of Transactions Related to increased uptake and usage of MMS, on average the number and value of transactions increased in the six months after the official declaration of a COVID-19 case in Uganda compared to a similar period before (Table 24). Table 24: Comparison of the Number and Value of Transactions before and after COVID- 19 Number and Value of 12 months 6 months 6 months CY 2018 CY 2019 CY 2020 Transactions before before after (August (January {so far} (March (September (March 2018 to 2019 to (January 2019 to 2019 to 2020 to December December 2020 to February February August 2018) 2019) August 2020) 2020) 2020) 2020) No. of Sum 2.898 1.551 1.645 0.941 2.785 2.197 Transactions (Billions) Average 0.241 0.258 0.274 0.188 0.232 0.275

Value of Sum 74.001 39.703 42.562 26.828 71.774 56.520 Transactions (Trillions) Average 6.167 6.617 7.094 5.366 5.981 7.065

Source: Bank of Uganda Mobile Money Statistics

5.7 Balances on Customers’ Accounts As shown in Table 25, on average the balances on customers’ mobile money accounts increased to UGX0.770 Trillion in the six months after the official declaration of a COVID-19 case in Uganda compared to UGX0.458 Trillion in a similar period before. The higher outturn suggests that customers were using mobile money accounts which are primarily transaction accounts for savings purposes. Table 25: Comparison of the Balances on Customers’ Mobile Money Accounts before and after COVID-19 Balances on Customers’ 12 months 6 months 6 months CY 2018 CY 2019 CY 2020 Mobile Money Accounts before before after (August (January {so far} (March (September (March 2018 to 2019 to (January 2019 to 2019 to 2020 to December December 2020 to February February August 2018) 2019) August 2020) 2020) 2020) 2020) Value of Sum 4.708 2.747 4.619 1.800 4.089 5.901 Transactions (Trillions) Average 0.392 0.458 0.770 0.360 0.341 0.738

Source: Bank of Uganda Mobile Money Statistics 5.8 Independent Samples t-tests to compare means six months before and after COVID-19 The COVID-19 pandemic provided a confluence of factors that shaped the DFS landscape albeit of a temporary nature. The measures introduced by DFS players to slow the advance of COVID- 19 such as zero rated P2P transfers, grace period for the repayment of digital credit for 30 days without penalty fees; free MoMo Pay and Airtel Money Pay (P2B); as well as reduced tariffs for W2B and B2W happened against a backdrop of reduced economic activity induced by the Coronavirus pandemic. Nevertheless, the situation provides a natural experiment of how a reduction in the pricing of mobile money services (P2P, W2B, B2W, and P2B); a grace period for the repayment of digital credit without penalty feees; and a disruptive force (disease pandemic which led to cessation of economic activity in most sectors of the macro-economy) affected the usage of mobile financial services (MFS) in Uganda. Independent samples t-tests were conducted to compare whether differences in variables six months before official declaration of COVID-19 in Uganda (September 2019 to February 2020) and six months after (March 2020 to August 2020) were statistically significant. Table 26 provides a summary of all the results at an alpha level of 0.05.

Table 26: Comparison of Means six months before and after COVID-19 for select MFS variables MFSProduct / Unit of Six months before Six months after df Computed Computed Sig. OR Service Measures COVID-19 COVID-19 t-value p-value Not Sig.

Mean S.D. Mean S.D.

1. No. of 0.258 0.015 0.274 0.020 10 -1.543 0.154 Not Sig. Transactions Trans (Bn)

Value 6.617 0.388 7.094 1.002 10 -1.086 0.303 Not Sig. (UGX Trillion)

2. Balances on UGX 0.458 0.143 0.770 0.054 10 -5.009 0.0005 Sig. Customers' Trillion Accounts

3. Registered Total 26.657 0.469 28.304 0.631 10 -5.129 0.0004 Sig. Customers Registered Customers (Mn)

Active 16.434 0.649 17.982 0.527 10 -4.532 0.001 Sig. Customers on Quarterly Basis (Mn)

Active 12.664 0.450 13.939 0.590 10 -4.210 0.001 Sig. Customers on Monthly Basis (Mn)

4. “Over The No. of 8.907 0.406 10.605 0.684 10 -5.229 0.0004 Sig. Top” (OTT) Trans. Tax (Millions)

Value of 4.506 0.188 4.951 0.194 10 -4.037 0.002 Sig. Trans. (UGX Billions)

5. Loans No. of 1.473 0.124 1.131 0.110 10 5.051 0.0005 Sig. Repayments Trans. (Millions)

Value of 50.108 18.055 44.532 7.589 10 0.697 0.501 Not Sig. Trans. (UGX Billions)

6. Loans No. of 0.641 0.095 0.416 0.057 10 4.980 0.0006 Sig. Disbursements Trans. (Millions)

Value of 54.560 22.792 39.765 7.290 10 1.515 0.161 Not Sig. Trans. (UGX

MFSProduct / Unit of Six months before Six months after df Computed Computed Sig. OR Service Measures COVID-19 COVID-19 t-value p-value Not Sig.

Mean S.D. Mean S.D.

Billions)

7. Data No. of 23.024 9.510 44.257 4.990 10 -4.843 0.0007 Sig. Trans. (Millions)

Value of 32.118 12.602 61.827 5.286 10 -5.325 0.0003 Sig. Trans. (UGX Billions)

8. Airtime No. of 98.026 3.523 89.938 6.333 10 2.734 0.021 Sig. Trans. (Millions)

Value of 107.997 5.118 101.229 8.128 10 1.726 0.115 Not Sig. Trans. (UGX Billions)

9. Cross No. of 0.026 0.004 0.037 0.006 10 -3.661 0.004 Sig. Border Trans. Remittances – (Millions) Outflows / Outward

Value of 2.948 0.456 4.349 0.956 10 -3.238 0.004 Sig. Trans. (UGX Billions)

10. Cross No. of 0.129 0.010 0.216 0.030 10 -6.737 5.125X10-5 Sig. Border Trans. Remittances – (Millions) Inflows / Inward

Value of 35.833 2.967 73.159 22.875 10 -3.964 0.003 Sig. Trans. (UGX Billions)

11. P2B No. of 16.063 3.682 13.134 2.705 10 1.570 0.147 Not Sig. Trans. (Millions)

Value of 217.233 26.669 172.029 38.540 10 2.363 0.040 Sig. Trans. (UGX Billions)

12. W2B No. of 176.970 11.193 216.269 64.287 10 -1.475 0.171 Not Sig. Trans. (Thousands)

MFSProduct / Unit of Six months before Six months after df Computed Computed Sig. OR Service Measures COVID-19 COVID-19 t-value p-value Not Sig.

Mean S.D. Mean S.D.

Value of 67.946 12.397 141.013 47.220 10 -3.666 0.004 Sig. Trans. (UGX Billions)

13. B2W No. of 784.745 261.004 1,200.621 108.447 10 -3.604 0.0048 Sig. Trans. (Thousands)

Value of 152.473 53.293 242.289 36.915 10 -3.394 0.0034 Sig. Trans. (UGX Billions)

14. No. of 27.518 0.767 26.911 3.432 10 0.422 0.682 Not Sig. Withdrawals Trans. (Millions)

Value of 1,808.664 107.754 1,771.375 369.007 10 0.238 0.817 Not Sig. Trans. (UGX Billions)

15. Deposits No. of 47.350 3.387 44.626 6.234 10 0.940 0.369 Not Sig. Trans. (Millions)

Value of 1,898.356 92.820 1,805.647 308.370 10 0.705 0.497 Not Sig. Trans. (UGX Billions)

16. P2P No. of 11.221 0.802 17.266 2.160 10 -6.426 7.576X10-5 Sig. Trans. (Millions)

Value of 779.468 59.855 1,178.040 175.076 10 -5.277 0.0004 Sig. Trans. (UGX Billions) Source: Authors’computation using MS-Excel Data Analysis Functionality While most products show that there were statistically significant changes in their usage in the six months before COVID-19 (September 2019 to February 2020) compared to the six months after official declaration of COVID-19 in Uganda (March 2020 to August 2020), which was to be expected, there are notable exceptions. For instance, the number and value of transactions even though increased in the six months after official declaration of COVID-19 in Uganda, there were not statistically significant. The confounding nature of results points to the complexity of consumer behaviour in the use of MFS in particular and DFS in general; the interconnectedness of MFS services and products; the

granularity of the data to capture differences in product characteristics and usage is still inadequate; and the increased integration of MFS into TBMFIs to create a resilient DFS ecosystem. The withdrawals and deposits which are the most common transactions in Uganda’s MFS ecosystem (both in terms of number and value of transactions) were not statistically significant when compared over the six months period before and after the official declaration of COVID-19 in Uganda. So how were the increased person-to-person (P2P) transactions funded? P2P transactions were statistically significant in both number and value of transactions. The results suggest that in addition to the commonly used approach of deposits at agents, financial consumers used Bank to Wallet (B2W) to fund these P2P transactions. Given that the TBMFIs were operating about 30 percent branch network capacity, withdrawing funds for later depositing at MM agents while possible due to the wide reaching ATM network especially in urban areas would be irrational consumer behaviour. The economic costs of withdrawing money from TBMFIs and cashing it in at MMSPs would be greater than those of B2W due to restrictions on public transportation and COVID-19 exposure risks. As a consequence, use of the B2W was the optimal consumer behaviour for funding MM accounts. The use of wallets to fund TBMFIs accounts (W2B) was not statistically significant in terms of number of transactions partly reflecting the slow down in economic activity and thereby the reduction in the number of Bottom of the Pyramid (BoP) users who would use mobile wallets to send money to their TBMFIs accounts after earning a wage in the informal sector at the end of the business day. However, the value of transactions were statistically significant suggesting that a good proportion of people in the population continued to send money from their mobile wallets to bank accounts. This may imply that not all P2P receipts were necessarily consumed, but some might have been saved in TBMFIs accounts for a rainy day. In the case of P2B, the value of transactions were significant yet number of transactions were not statistically significant. Person-to-Business (P2B) is a broad category where individuals are paying money for utilities (electricity, water, post paid solar power systems, and cable TV etc.) as well as goods and services. Due to the closure of most businesses especially in the hospitality and travel sector, the payment for goods and services slowed down thereby impacting transaction numbers. The low uptake of electronic or mobile commerce by Ugandans means that once the physical shops where MoMo Pay or Airtel Money Pay could be used to pay for goods and services were closed, the transaction numbers in P2B had to dwindle. On the other hand, however, the regular payments for utilities must have remained due to the need for such services when individuals are confined to their homesteads. However, what appears to have happened is that individuals for fear of being in a blackout might have paid for say electricity and cable-TV for relatively longer durations than they would ideally have done in case of daily incomes. Instead of paying for cable-TV on a daily basis, some might have instead paid on a monthly basis. This does not impact on the monthly value of transactions significantly but affects the number of transactions. Despite the presidential directive to differ utility bill payments till after COVID-19, individuals with electricity pre-paid meters popularly known as

YAKA had to fork out money before accessing the service. During the lockdown, there was a concerted effort by Umeme (the power distribution conncession holder in Uganda) to change post paid customers to pre-paid customers by replacing old post-paid meters with new pre-paid meters known as YAKA. Airtime, the number of transactions were significant yet the value of transactions were not statistically significant. Airtime has two purposes when consumed by customers, that is, make voice calls and / or purchase data. However, voice calls can now be made via other models such as Whatsapp, Zoom, Microsoft Teams, and Skype etc. which require internet data. Mobile internet data may be purchased using USSD prompts without first purchasing airtime. Alternatively, it might be purchased via the airtime channel / route. The decline in airtime usage during this period might suggest that individuals reduced their spend on airtime and probably replaced traditional voice calls with “voice over the internet calls”. The number of transactions for loans disbursements and the value therein dropped, but the latter was not statistically significant while the former was statistically significant. Overall, the decline points to risk averseness to the digital credit lenders due to the slow down in economic activity ocassioned by COVID-19. It appears that the number of micro digital credit applicants and thereby approvals (disbursements) dropped immensely reflecting the self censure by borrowers (self credit rationing) during tough economic times as well as a more stringent evaluation and therefore rationing by microcredit providers. The number of transactions for loan repayments and the value therein dropped, but the latter was not statistically significant while the former was statistically significant. Overall, the decline reflects the moratorium on charging default penalties for 30 days imposed by the digital credit providers and the tough economic times. The tough economic times must have been more straining for borrowers whose income was largely from the informal sector which was shutdown during the national lockdown. Even though the value of loan repayments dropped, it was not statistically different across the two periods suggesting that financial consumers who could afford servicing loans (probably fixed income earners in Government Ministries, Departments, and Agencies and / or private sector corporate jobs) continued honouring their obligations even during tough economic times to prevent being disadvantaged in future credit worthiness assessments by the MFS algorithms.

VI. Future of DFS Landscape in Uganda 6.1 Disruptions in the DFS Landscape in Uganda In this paper, the effect of changes to the pricing structure of P2P on DFS amongst other anti- COVID measures amidst the Coronavirus pandemic context were explored. Nonetheless, the DFS (especially the Mobile Financial Services component) landscape has dealt with various disruptions since mobile money was introduced in Uganda in March 2009. As shown in Figure 2, there have been four major disruptions.

Figure 2: Disruptions in Uganda’s Mobile Money Services from 2009 to 2020

8,000 35.00

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May-20 TOTAL TRANSACTION VALUES (BN (BNSHS) TRANSACTION TOTAL VALUES VALUE OF TRANSACTIONS NUMBER OF REGISTERED USERS Source: Bank of Uganda A: System upgrade In September 2014, there was a scheduled 3-day upgrade of mobile money systems that forced the service to experience down time. The system was taken down for 3 days and a new one installed. This followed the repeated concerns about the security of users. BoU had in the previous year issued mobile money guidelines, which although not binding, offered some relief to customers. The provider did announce via its various platforms that an upgrade would be taking place between Saturday 20 to Monday 22 September 2014 to make mobile money more secure, reliable and easier to use. In reality, the down time went on for a total of 5 days. B: Nation wide shut down This occurred during the presidential and parliamentary elections of 2016. On on February 18, 2016, the Uganda Communications Commission, citing a threat to "national security," ordered mobile network operators to shut down key social media sites (WhatsApp, Facebook, Twitter) and disable mobile money platforms. Restrictions on the latter were lifted after 4 days, while users found a way round to access social media using virtual private networks (VPN). Bold and Pillai (2016) state that the abrupt shut down left millions of customers stranded as many had topped up their accounts on account of bank closures on public holidays and fear for election violence. This shut down saw volume of transactions falling by 6.94 million and total value of transactions declining by UGX139.4 billion. C: OTT and Mobile Money Tax In July 2018, an amendment on the excise duty came into effect. This would be known as the Excise Duty (Amendment) Act 2018, which stated that “A tax of 1 percent of the value of the

transaction will apply on mobile money transactions on receiving money, making payments and withdrawals of money” Customers were up in arms over this seemingly unfair and double taxation. Several studies were done to explain the impact of this policy. The Government of Uganda, later in the month, clarified that the 1 percent was meant to be charged on the received amounts and not the deposits, even though customers had been charged on both deposits as well as transfers off their mobile money accounts. The 1 percent also applied to bill and merchant payments; but did not apply to the payment of URA taxes. Later on during the parliamentary proceedings of October 3, 2018, the house approved the Excise Duty (Amendment) (No.2) Bill, 2018 effectively reducing the mobile money transaction tax from 1 to 0.5 percent on withdrawals. Customers responded by making changes to their mobile money behaviour almost immediately. Starting June 2018, the value of transactions dropped by UGX743 billion, even before the tax was to come into force owing to the media campaign by various civil society originations decrying the tax, which had been passed by the parliament months earlier. The reaction was intensified the following month when the value of transactions fell by UGX 2.45 trillion in July 2018 alone. The service would take another 19 months to recover transaction values equal to pre- mobile money tax levels, and just as it did, COVID-19 struck. D: COVID-19 Lockdown A detailed description of this particular disruption on the services of MMSPs is the focus of this paper. 6.2 Implications The paper set out to examine how the change in pricing of mobile financial services and products (P2P, W2B, B2W, and P2B); easing of digital credit repayment terms and conditions (moratorium on application of late repayment penalties for 30 days and enforcement of collection); and disruptions in the financial services consumption patterns ocassioned by a health risk (COVID-19 pandemic). The measures taken by Ugandan MNOs are largely in line with those taken at the international level to contribute to the prevention of the spread of COVID-19 and support economic activity during the pandemic. Muthiora (2020) list seven categories of measures taken at international level, namely, (i) P2P transaction fee waivers; (ii) waivers on B2W and W2B transaction fees; (iii) easier access to digital credit; (iv) support to financial services providers agents e.g. designating them as essential service providers thereby ensuring continued access to cash-in / cash-out facilities etc.; (v) waiver of interchange fees; (vi) increasing transaction and balance limits; and (vii) flexible Know Your Customer and on- boarding. The first four categories encompass what Ugandan MNOs implemented. Four key findings and the implications therein can be derived from this paper. 1. Pricing influences adoption / uptake / usage of mobile financial services. Reduction in prices as those effected by MNOs during the COVID-19 pandemic do increase usage of MFS products and services. The price reduction had both direct (uptake of product whose price was adjusted changes) and indirect (alternate product whose price was not moved manifests a change in 48

uptake ocassioned by a price change in another product) effects on the usage of MFS products and services. For example a price reduction in the cost of P2P transfers was manifested in higher P2P volumes and transactions. In contrast, the reduction in prices of B2W directly and positively affected volumes and values of B2W but negatively impacted deposits. The pricing structure is tiered and reflects the marketing strategy of the MNO; cost of doing business (taxation by government and cost of operations etc.); financial consumer’s ability to pay (larger amounts attract larger fees); and profit margin of MNO’s mobile money business (MM surcharges are major cash cows for MMSPs with estimated daily revenues grossing above UGX5billion) amongst others. Thus, while lower prices would foster affordability and increase uptake of the MFS products and services, MNOs may not be able to unilaterally reduce their prices without due regard to other stakeholders like fiscal authorities. The reduction implemented during the COVID-19 pandemic was a result of wide ranging consultations between MNOs and the Central Bank of Uganda. None of the reduced prices altered tax policy or the tax component in MM surcharges. Even though Government forfeited tax on the MM surcharges revenue that would have been collected from March 19, 2020 to June 25, 2020, long term effect on tax is restricted to that period of no collection. Similarly, the MNOs also lost revenues for the same period. However, long term, they benefitted in terms of good will from their clients as caring and responsible corporate players willing to support the country’s citizenry through a major economic shock induced by a health risk. In addition, MNOs benefitted from a wealth of data demonstrating how price reduction could be used to influence usage. Indeed, one can point to the decision by MTN mobile money to reduce withdrawal charges on November 02, 2020 (TechJaja, 2020; Asingwire, 2020; Twaha, 2020) as a quick learning from this price reduction induced by the COVID-19 response. Overall, it is highly likely that the reduction in prices is temporary but future uses of pricing as a competition tool in the mobile money services space will persist going forward continuing a culture observed in the past in the areas of voice and mobile internet data business components of MNOs. 2. Disruptions whether legal (suing of stakeholders for lack of comprehensive legal framework); political (switch off of mobile money systems during political events like elections or riots); political economy (changes to taxation arrangements of MMSPs); technological (switch off MMSP platform on account of system upgrade or overhaul); and health related (pandemic or epidemic which changes financial consumer behaviour and / or interaction with the MMSP system) are major drivers of DFS access, usage, affordability, and quality of the customer experience.In its 12 years of existence, MFS in Uganda have experienced all these disruptions and some have a high likelihood of recurring.For instance, hotly contested elections in 2016 led to the switch off of mobile money services (Bold & Pillai, 2016). The electoral cycle of 2021 is characterised by similar features with a high likelihood of interference in mobile money platforms to the detriment of financial consumers. It is imperative that financial consumers who are usually the ones most affected by such disruptions devise modalities of hedging against such eventualities.

One such approach would be to spread the risk of one’s hard earned monies betweeen accounts in MMSPs and TBMFIs. Since both have agent networks, one can access their monies from anywhere in the country. If one of the platforms is switched off, a financial consumer may substitute it with the other which would be up and running. However, the MMSPs have about 29million accounts compared to about 16million accounts of TBMFIs. The financial consumers without TBMFIs (about 10 million individuals) should be incentivised to open such accounts by both the FSPs (charges should be affordable) and GoU authorities (expedite identification cards issuance by NIRA; and BoU should introduce tiered KYC for such transactional accounts). The TBMFIs’ transactional platform has not yet experienced any shutdowns on account of national security concerns probably due to the higher KYC requirements used in opening TBMFIs accounts. In other words, it is easier to trace and apprehend a TBMFI account holder if they get involved in AML/CFT crime compared to an MMSP account holder. Overall, disruptions provide learnings which must not be wasted as rightly pointed out must not be wasted as rightly pointed out by Sir Winston Churchill in the mid 1940s when he states that “never let a good crisis go to waste”. 3. Infrastructure gaps exist in the DFS ecosystem encompassing among others electricity supply bottlenecks; ICT infrastructure gaps (e.g. low numbers of smart phones); financial infrastructure (interoperability across networks not yet seamless); and identification infrastructure (challenges of obtaining and / or replacing national IDs yet it is a stringent condition for all kinds of KYC which KYC is not tiered to reflect different risk profiles for various activities and / or individuals). These gaps limit the extent to which DFS can be leveraged to foster financial widening and deepening. Indeed, these infrastructural gaps possibly explain why MMS have remained money transfer services rather than growing rapidly into a support system to mobile commerce. Nonetheless, a nascent mobile commerce value chain appears to be forming in Uganda partly supported by the developments in the mobile money space. 4. The relaxation of terms and conditions for digital credit repayments led to a reduction in loan repayments as was expected. In addition, the general economic condition characterised by low economic activity led to low loan disbursements suggesting self credit rationing for fear of default and / or FSP induced credit rationing due to stringent approval criteria.Given that these are microcredit facilities not documented in the Credit Reference System (CRS) yet, tickering with terms and conditions may lead to moral hazard (desire to default due to low risk associated with default) and adverse selection (attracting rogue financial consumers to borrow these hard times without intention of repaying their loans). The tough economic times are further exacerbated by the relatively high lending interest rates of these microcredit facilities which range from 81 percent per annum to 180 percent per annum. The credit relief measures to be deployed in this space need further scrutiny by the MMSPs and regulatory authorities to ensure that they are not detrimental to this fledgling subsector.

6.3 Recommendations Muthiora (2020) opines that the anti-COVID measures introduced are “at best temporary and geared at limiting the spread of COVID-19 as well as alleviating the cost of living pressure on users of mobile money services during the pandemic.” His proposed recommendations are associated with how quickly the pre-COVID normal tariff structure can resume without “impair[ing] long-term sustainability of mobile money business”. Nonetheless, there are lessons which this unexpected natural experiment elicited which should not be sacrificed on the altar of mobile money business viability even if it is a key consideration in the sustainability discourse. Hence, the recommendations derived from this study include:- 1) There is ample room for stakeholders to negotiate and agree on a pricing structure which does not disadvantage any of the stakeholders especially Bottom of the Pyramid (BoP) clientele. Not withstanding Muthiora (2020)’s projected impacts of P2P price reductions namely, (i) MMSPs do not intermediate funds but are simply channels making them heavily reliant on P2P revenues; (ii) reduced P2P revenues can lead to diminished agent networks; and (iii) lower mobile money excise taxes from zero rating can lead to regressive taxes pegged to underlying principle amounts, there is room for a pricing strategy that prioritises turnover other than cost. In addition, free transactions (Muthiora, 2020) with a ceiling of say UGX30,000/= for a frequency of three times daily, can provide relief for the low income users affected by such surcharges. A scheme akin to cross subsidisation where high income P2P users subsidise the surcharges of low income P2P users can be devised. Furthermore, Muthiora (2020)’s suggestion of using interest earned from escrow / trust accounts to subsidise P2P transactions is one way in which cross subsidisation can be achieved. Muthiora (2020) suggests that TBMFIs should put in place incentives that attract financial consumers to patronise the TBMFIs so as to increase deposits and savings with a view of removing W2B and B2W lowered fees. There is no doubt that TBMFIs need to augment their deposit mobilisation beyond urban and peri-urban areas, however, there is need for increased interoperability between systems of MMSPs and TBMFIs. Issues of inefficiencies and fear for competition are still keeping prices of these W2B and B2W very high. 2) Disruptions to DFS are likely to remain a major limiting factor in the foreseeable future. Therefore, financial consumers should devise substitutes to meet needs during moments when MFS or TBMFIs digital financial services are not accessible. One approach would be to get MFS account holders without TBMFIs accounts to open low value transaction accounts in TBMFIs. Such low value transaction accounts should have lower KYC requirements and be relatively easy to operate through TBMFIs agent networks. 3) The digital infrastructure (internet and overall telecom connectivity) are largely urban based and this may not be a viable argument for the drive to extend fianncial inclusion to the non urbanised areas. That said, the COVID-19 pandemic presented a unique opportunity for digital financial services. Low-income households and small firms can benefit greatly from advances in digital financial services most especially mobile money, fintech services, and digital banking. While its evident that the pandemic increased use of DFS, it has also posed challenges 51

for the growth of the industry’s smaller players, especially those with a constrained agent network and highlighted unequal access to digital infrastructure. Several actions will need to be taken to ensure maximum inclusion going forward. One of them is the creation regulatory frameworks that promote remote and virtual banking solutions such as digital banking and open application programming interfaces (API), cloud computing and distribution ledger technology (DLT), commonly refered to as block chain. These developments would serve the need for financial sector deepening, by minimizing physical contact and over reliance on the traditional transaction channels. In the medium term policy regulators in this sector such as National Information Technology Authority of Uganda (NITA-U), BoU and UCC as well as private sector players through Public Private Partnerships (PPP) need to work towards erecting and promoting the necessary infrastructure required for the development of DFS, such as digital identity systems, expanded broadband and encouraging agency banking, which has already taken root in Uganda. 4) As pointed out by Muthiora (2020), digital credit terms and conditions being relaxed posseses a serious risk of having an oversupply of microcredit loans which may culminate into a high level of non performing loans. In Uganda, the risk of default is high since digital microcredit is not yet being booked on the Credit Reference System (CRS). Regulators and FSPs should be vigilant with monitoring this subsector and scrutinising credit relief measures in this space before rolling them out. 5) There is a need for stakeholders especially regulatory authorities and financial services providers to undertake financial literacy activities targeted at popularising the safe use of digital financial services. The efforts must entail Digital Financial Literacy (knowledge, skills, confidence, and self-efficacy of using DFS) and utilise Open Distance electronic Learning (ODeL) approaches to minimise cost and COVID-19 spread. 6) Data quality needs to be enhanced. The Central Bank of Uganda commenced collecting data about MFS services such as P2B, B2W, and W2B etc. in August 2018. Nonetheless, some of these categories such as P2B are too broad making analysis challenging. There is a need to split such large categorisations and enhance granularity of data collected. 6.4 Conclusions Mobile money services uptake and usage is driven by a multiplicity of factors like all other technological advancements. In this paper, using administratively collected data, three factors, that is, price, terms and conditions of a service, and disruptive forces have been demonstrated as key drivers of usage of mobile money services in Uganda. The findings provide information on how to design an appropriate pricing strategy as part of the broader marketing and competition strategy of FSPs (MMSPs). In addition, the findings challenge regulators to re-examine the pricing models of FSPs and how aligned these models are to financial inclusion policy objective(s) which regulators are tasked with achieving.

A longitudinal study to examine the effect of anti-COVID measures on MFS over a longer term horizon would enrich the findings of this study. However, even in its current state, the paper provides useful insights of DFS stakeholders’ response to COVID-19 and the implications to sustainability of the DFS ecosystem.

VII. References AFI (Alliance for Financial Inclusion) (2020). Digital Financial Services: DFS expand the delivery of basic financial services to the poor. https://www.afi-global.org/policy-areas/digital- financial-services AFI (Alliance for Financial Inclusion) (2019). Uganda’s Journey to Inclusive Finance Through Digital Financial Services. https://www.afi-global.org/sites/default/files/publications/2019- 07/AFI_MS_Uganda_AW_digital.pdf African Union (AU) (2020). Impact of the Coronavirus (COVID-19) on the African Economy. https://au.int/en/documents/20200406/impact-coronavirus-covid-19-african-economy Airtel Uganda (2020). Evolution of Airtel Money. https://www.airtel.co.ug/media/blogs/evolution_of_airtel_money Amoroso, D.L. and Magnier-Watanabe, R. (2012). Building a research model for mobile wallet consumer adoption: the case of mobile Suica in Japan. Journal of Theoretical and Applied Electronic Commerce Research, 7(1), 94-110. Asingwire, N. (November 03, 2020). MTN Uganda reduces mobile money withdraw charges. http://kampalapost.com/content/mtn-uganda-reduces-mobile-money-withdraw-charges AU (African Union) (2020). Impact of the Coronavirus (COVID-19) on the African Economy. https://au.int/en/documents/20200406/impact-coronavirus-covid-19-african-economy Bank of Uganda (BoU) (June 08, 2020). Monetary Policy Statement for June 2020. https://www.bou.or.ug/bou/bouwebsite/bouwebsitecontent/MonetaryPolicy/Monetary_Policy_St atements/Monetary-Policy-Statement-for-June-2020.pdf Bank of Uganda (BoU) (April 06, 2020). Monetary Policy Statement for April 2020. https://www.bou.or.ug/bou/bouwebsite/bouwebsitecontent/MonetaryPolicy/Monetary_Policy_St atements/MPS-April-2020-FINAL.pdf Bank of Uganda (BoU) (March 20, 2020). Measures to mitigate the economic impact of COVID- 19. https://www.bou.or.ug/bou/export/sites/default/mediacenter/Otherspeeches/2020/Mar/Measures- to-mitigate-the-economic-impact-of-COVID-19.pdf Bank of Uganda (2020). Annual Report FY2019/2020. https://www.bou.or.ug/bou/bouwebsite/bouwebsitecontent/publications/Annual_Reports/All/Ann ual-Report-2019-2020.pdf Bank of Uganda (2019). Annual Report FY2018/2019. https://www.bou.or.ug/bou/bouwebsite/bouwebsitecontent/publications/Annual_Reports/All/Ann ual-Report-2019.pdf

Bank of Uganda (2002). Annual Report FY2001/2002. https://www.bou.or.ug/bou/bouwebsite/bouwebsitecontent/publications/Annual_Reports/All/ann ualReport2001-02.pdf Bank of Uganda (2001). Annual Report FY2000/2001. https://www.bou.or.ug/bou/bouwebsite/bouwebsitecontent/publications/Annual_Reports/All/ann ualreport2000-01.pdf Bank of Uganda (1999). Annual Report FY1998/1999. https://www.bou.or.ug/bou/bouwebsite/bouwebsitecontent/publications/Annual_Reports/All/ann ualReport1998-09.pdf Bold, C. and Pillai, R. (March 07, 2016). The Impact of Shutting Down Mobile Money in Uganda. https://www.cgap.org/blog/impact-shutting-down-mobile-money-uganda Cheney, J.S. (2008). An Examination of Mobile Banking and Mobile Payments: Building Adoption as Experience Goods? http://www.philadelphiafed.org/consumer-credit-and- payments/payment-cards-center/publications/discussion-papers/2008/D2008MobileBanking.pdf Chidembo, N. (2009). Exploring Consumer Adoption of NFC-enabled mobile payments in South Africa. Master’s Thesis. University of Pretoria. CIPESA (The Collaboration on International ICT Policy for East and Southern Africa) (March 2018). National Information Technology Survey 2017/2018 Report. Kampala, Uganda: NITA- Uganda. https://www.nita.go.ug/sites/default/files/publications/National%20IT%20Survey%20April%201 0th.pdf CGAP (Consultative Group to Assist the Poor) (March 2013). The Power of Social Networks to Drive Mobile Money Adoption. https://www.cgap.org/research/publication/power-social- networks-drive-mobile-money-adoption Daily Monitor (September 21, 2019). Ugandans paying highest for mobile data in E. Africa – survey. https://www.monitor.co.ug/News/National/Ugandans-paying-highest-for-mobile-data-in- E--Africa/688334-5282268-s90bmv/index.html Daily Monitor (July 17, 2019). Social media tax fails to raise expected amount. https://www.monitor.co.ug/uganda/news/national/social-media-tax-fails-to-raise-expected- amount-1837820 Davidovic, S., Prady, D., and Tourpe, H. (June 22, 2020). You’ve got money: mobile payments help people during the pandemic. https://blogs.imf.org/2020/06/22/youve-got-money-mobile- payments-help-people-during-the-pandemic/ Ducharme, J., Roache, M., and Walcott, J. (August 03, 2020). Inside the Global Quest to Trace the Origins of COVID-19 and Predict Where it will go next. https://time.com/5870481/coronavirus-origins/

Dzokoto, V.A.A. and Mensah, E.C. (March 30, 2012). Barriers to Mobile Money Transfer Uptake in Ghana. https://www.marketlinks.org/sites/marketlinks.org/files/resource/files/eps6_dzokoto_mensah_pre sentation_033012.pdf Frankfurt School of Finance & Management gGmbH (2020). Certified Expert in Financial Inclusion Unit 3 Digital Financial Services. Gilbert, P. (June 24, 2020). African Operators reinstate mobile money fees. http://www.connectingafrica.com/author.asp?section_id=761&doc_id=761931& Gillwald, A., Mothobi, O., Ndiwalana, A., and Tusubira, T.F.F. (May 2019). The State of ICT in Uganda. Research ICT Africa Policy Paper Series No. 5 After Access: Paper No. 8 Govender, I. and Sihlali, W. (2014). A study of mobile banking and adoption among university students using an extended TAM. Mediterranean Journal of Social Sciences, 5(7), 451-459. Government of Uganda (2020). National Payments Systems Act 2020. Government of Uganda (2018). Excise Duty (Amendment) Act 2018. Government of Uganda (2016). Financial Institutions Act 2004 as amended in 2016. GPFI (Global Partnership for Financial Inclusion) (2016). G20 High-Level Principles for Digital Financial Inclusion. https://www.gpfi.org/publications/g20-high-level-principles-digital- financial-inclusion GSMA (Global System Mobile Association) (May 2008). Taxation and the growth of mobile services in sub-Saharan Africa. https://www.gsma.com/publicpolicy/wp- content/uploads/2012/03/taxgrowthsubsaharanafrica.pdf Handforth, C. and Wilson, M. (2019). Digital Identity Country Profile: Uganda. https://www.gsma.com/mobilefordevelopment/wp-content/uploads/2019/02/Digital-Identity- Country-Report-Uganda.pdf Heyer, A. and Mas, I. (2009). Seeking fertile grounds for mobile money. http://www.gsma.com/mobilefordevelopment/wp-content/uploads/2009/09/Fertile-Grounds-for- Mobile-Money.pdf Ikonjo-Iwela, N. (August 02, 2016). African Central Banks: Rethinking Role or Staying the Course – Learning from Global Experience. 24th Joseph Mubiru Memorial Lecture. Kampala, Uganda: Bank of Uganda Iliasov, A. (July 10, 2014). Barriers to Mobile Money Adoption in Nigeria. http://finclusion.org/blog/barriers-to-mobile-money-adoption-in-nigeria.html Johns Hopkins University Coronavirus Resource Center (2020). COVID-19 Dashboard by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU). https://coronavirus.jhu.edu/map.html

Kambale, L. (2018). Digital Financial Services: A Case of Malawi. https://www.itu.int/en/ITU- D/Capacity- Building/Documents/IG_workshop_August2018/Presentations/Session8_LindaKambale.pdf Kasyoki, K.T. (2012). Factors affecting adoption of mobile phone banking by customers of commercial banks in Kenya. MBA Dissertation, University of Nairobi, Kenya. Kazi, A.K. and Mannan, M.A. (2013). Factors affecting adoption of mobile banking in Pakistan: Empirical Evidence. International Journal of Research in Business and Social Science (IJRBS), 2(3), 54-61. Khan, I. and Goldstein, P. (May 13, 2014). Pakistan: Mobile Money Uptake, Awareness, and Trust. http://finclusion.org/blog/pakistan-mobile-money-uptake-awareness-and-trust.html Kisekka, J.I. (August 03, 2018a). Unused Airtime Scratch Cards to be converted to Mobile Money. https://techjaja.com/unused-airtime-scratch-cards-converted-mobile-money/ Kisekka, J.I. (August 10, 2018b). Airtime Scratch Cards are not going away after Government lifts ban. https://techjaja.com/airtime-scratch-cards-not-going-away-government-lifts-ban/ Kuo, Y.F. and Yen, S.N. (2009). Towards an understanding of the behavioral intention to use 3G mobile value-added services. Computer in Human Behaviour, 25(1), 103-110. Larkotey, W.O., Amoako, P.Y., Laryea, E.A. and Dey, E. (2013). Adoption of Mobile Payment Systems in Ghana. International Journal of Societal Applications of Computer Science, 2(4), 367-372. Luarn, P. and Lin, H.H. (2005). Toward an understanding of the behavioral intention to use mobile banking. Computers in Human Behavior, 21(6), 873-891. Lule, I., Omwansa, T. K. and Waema, T.M. (2012). Application of Technology Acceptance Model (TAM) in M-Banking Adoption in Kenya. International Journal of Computing and ICT Research, 6(1), 31-43. Lyatuu, J. (October 19, 2020). 7.6 million mobile Internet subscribers do not pay OTT. https://www.monitor.co.ug/uganda/business/finance/7-6-million-mobile-internet-subscribers-do- not-pay-ott--2484776 Malinga, R.B., Maiga, G., Jehopio, P., and Kareyo, M. (2017). Determinants of Mobile Money Services adoption by traders in Uganda. International Journal of Multidisciplinary Research and Development, 4(8), 189-201. Maradung, P. (2013). Factors affecting the adoption of mobile money services in the banking and financial industries of Botswana. MBA Dissertation, North-West University. Masocha, R. and Dzomonda, O. (2018). Adoption of Mobile Money Services and the Performance of Small and Medium Enterprises in Zimbabwe. Academy of Accounting and Financial Studies Journal, 22(3), 1-11.

Meena, G. (2014). Factors influencing the uptake of Mobile Money Service in Tanzania. https://www.researchgate.net/publication/320058830_Factors_Influencing_the_Uptake_of_Mobi le_Money_Service_in_Tanzania/citation/download Meso, P. and Musa, P.F. (2008). Extending the ICT Technological Culturation Model: The Role of Accessibility and Perceived Socio-economic prospects of ICT Diffusion. PreICIS Workshop on Global Development. http://www.globdev.org/files/33-Paper-Meso-Tech-Culturation.pdf Meso, P., Musa, P., Straub, D. and Mbarika, V. (2009). Information Infrastructure, Governance, and Socio-economic Development in Developing Countries. European Journal of Information Systems, 18, 52-65. MicroSave (2019). All Digital Credit is Not Equal … Consumer vs SME Lending https://sptf.info/images/IND-Digital-Credit-for-SPTF-Final-for-SPTF.pdf Ministry of Finance, Planning and Economic Development (MoFPED) (June 11, 2020). Background to the Budget Fiscal Year 2020/2021 – Stimulating the Economy to safeguard livelihoods, jobs, businesses, and industrial recovery. https://www.finance.go.ug/sites/default/files/Publications/BACK%20GROUND%20TO%20BU DGET%202020.pdf Ministry of Finance, Planning and Economic Development (March 20, 2020). Parliamentary Statement on the Economic Impact of COVID-19 on Uganda. https://www.finance.go.ug/press/statement-minister-finance-parliament-economic-impact-covid- 19-uganda Ministry of Health (2020). The Public Health Act Statutory Instruments of 2020 No. 45, 46, 52, 53, 55, 56, 57, and 58. Entebbe, Uganda: GoU/UPPC Mohapatra, S. (2011). Are mobile transfer costs too high? http://blogs.worldbank.org/peoplemove/are-mobile-money-transfer-costs-too-high MTN and Airtel Joint Press Statement, 2020 (May 25, 2020). MTN Uganda on Twitter: "MTN & AIRTEL wish to inform the public that effective 26th May 2020, all #MTNMoMo & Airtel money Person to Person ( P2P) transactions on the same network & Mobile Wallet to bank transactions will be gradually re-introduced at a 50% discount to standard tariffs for 30 days. https://t.co/MNUvtOPqwm" / Twitter MTN Uganda Limited (2020). Savings and Loans. https://www.mtn.co.ug/how-to/savings-and- loans/ Mugume, A., Opolot, J., Kasekende, E. and Namanya, C.A. (2020). The Macroeconomic Dynamics of COVID-19 in a Small Open Economy: The Case of Uganda. BoU Working Paper No. 01/2020. Muir, I. (2015). The Mobile Alternative to Banking: Patterns of Financial Transactions in Emerging Countries. http://thesis.haverford.edu/dspace/bitstream/handle/10066/16244/2015MuirI.pdf?sequence=1

Mulwa, M., and Ngigi, S. (2018). Barriers to uptake and use of added value mobile money products by the lesser off segments in Kenya. International Journal of Innovative Research and Development, 7(6), 145-155 Murray, S. (November 2016). Can e-transfers promote financial inclusion in emergencies: a case study from Ethiopia. https://www.mercycorps.org/sites/default/files/2020- 01/ETransfersFinInclusionCaseStudyEthiopia2017.pdf Musa, P.F., Meso, P., and Mbarika, V. W., (2005). Toward Sustainable Adoption of Technologies for Human Development in Sub-Saharan Africa: Precursors, Diagnostics, and Prescriptions. Communications of AIS, 15(April 2005), 592-608. Musazi, M. (November 15, 2010). Assessment of Telecom Tower Infrastructure sharing on cost and time to market for new entrants in the Ugandan Telecommunications Sector. Case study: Warid-Orange Site Sharing Arrangement. MBA, Dissertation, Eastern & Southern Africa Management Institute (ESAMI). Musiime, D. and Alinda, F. (2016). Drivers of Customer’s Choice of Mobile Money Agent for Mobile Money Service in Kampala, Uganda. DBA Africa Management Review, 6(4), 1-10. Muthiora, B. (April 2020). Mobile Money Recommendations to Central Banks in Response to COVID-19. https://www.gsma.com/mobilefordevelopment/wp-content/uploads/2020/04/Mobile- money-recommendations-to-central-banks-in-response-to-COVID-19.pdf Muzurura, J. and Chigora, F. (2019). Consumers’ Behavioural Intention to adopt mobile banking in rural Sub-Saharan Africa using an extension of Technology Acceptance Model: Lessons from Zimbabwe. International Journal of Business, Economics, and Management, 6(6), 316-334. Obwot, S. (March 20, 2020). Coronavirus: Airtel Uganda scraps all Airtel Money transaction fees. https://techjaja.com/coronavirus-airtel-uganda-scraps-all-airtel-money-transaction-fees/ ODI (Overseas Development Institute) (2020). The future of finance and banking systems in Africa beyond COVID-19. https://www.odi.org/events/16975-future-finance-and-banking- systems-africa-beyond-covid-19 Ogwang, A.M. (2009). Perceived Ease of Use, Usefulness, Trust, Information Accessibility and Acceptance of Electronic Funds Transfer. MSc. Dissertation. Makerere University Business School (MUBS). Oluoch, R.A. (2012). Factors affecting adoption of mobile banking technology in Kenya – A Case of Bank Customers within Nakuru Municipality. MBA Dissertation, Kabarak University, Kenya. Otieno, O.C., Liyala, S., Odongo, B.C., and Abeka, S. (2016). Challenges facing the use and adoption of mobile phone money services. World Journal of Computer Application and Technology 4(1), 8-14.

Padashetty, S. and Kishore, K.S.V. (2013). An Empirical Study on Consumer Adoption of Mobile Payments in Bangalore City – A Case Study. Journal of Arts, Science & Commerce, 4(1), 83-94. Pal, A., De, R., Herath, T., and Rao, R. (2019). A review of contextual factors affecting mobile payments adoption and use. Journal of Banking and Financial Technology, 3(5), 43-57. Pazarbasioglu, C., Mora, A.G., Uttamchandani, M., Natarajan, H., Feyen, E. and Saal, M. (April 2020). Digital Financial Services. http://pubdocs.worldbank.org/en/230281588169110691/Digital-Financial-Services.pdf PopulationPyramid.net (December 2019). Population Pyramids of the World from 1950 to 2100: Uganda https://www.populationpyramid.net/uganda/2020/ Robinson, I. and Wright, G. (December 13, 2016). Digital Credit is not always good for financial inclusion. https://fsduganda.or.ug/digital-credit-not-always-good-financial-inclusion-2/ Rolfe, A. (June 22, 2015). Nine drivers of mobile money identified as consumers embrace mobile. https://www.paymentscardsandmobile.com/nine-drivers-of-mobile-money-identified-as- consumers-embrace-mobile/ Sey, A. (August 2008). Mobile Communication and Development: A Study of Mobile Phone Appropriation in Ghana. University of Southern California, PhD Thesis. Ssettimba, J.I. (March 16, 2016). Mobile Money in Uganda. https://www.theigc.org/wp- content/uploads/2016/03/3.-Ivan-Ssettimba-Bank-of-Uganda.pdf Ssonko, G.W. and Kawooya, D.R. (2020). Financial Inclusion in an era of disruption – Achieving sustainable economic growth. Bank of Uganda Working Paper 27/2020. 37pp.https://www.bou.or.ug/bou/bouwebsite/bouwebsitecontent/research/BoUworkingPapers/res earch/BouWorkingPapers/2020/BoU_WP26_2020-Financial-Inclusion-in-the-Era-of-Disruption- Achieving-Sustainable-Economic-Growth-in-Uganda.pdf Ssonko, G.W. and Tait, M. (2018). Cost structure of mobile money in Uganda. Proceedings of the 2018 Annual Conference of the Emerging Markets Conference Board (EMCB) pp188-206. Ssonko, G.W. (2016). Mobile Money and Financial Inclusion in Uganda. Unpublished Doctor of Business Administration (DBA) Thesis. Port Elizabeth, SA: Nelson Mandela Metropolitan University Ssonko, G.W. (2011). Status of Mobile Money Services in Uganda: An Exploratory Study. https://www.academia.edu/4602371/Status_of_Mobile_Money_Services_in_Uganda_An_Explor atory_Study_BOUWP0811?auto=download Stork, C. and Esselaar, S. (August 22, 2018). Policy Brief on Uganda’s ICT Sector Taxes. https://researchictsolutions.com/unleash-not-squeeze-ugandas-ict-sector/ Tang, J-T, E. and Chiang, C. (2009). Towards an understanding of the behavioural intention to use mobile knowledge management. Journal WSEAS Transactions on Information Science and Applications, 6(9), 1601-1613. 60

Tangirala, S. and Nlondiwa, S. (2019). The Utilization of Mobile Money Services in Small Scale Enterprises: A Case Study. European Journal of Business & Management Research (EJBMR), 4(6), 1-6. TechJaja (November 04, 2020). MTN Uganda reduces mobile money withdraw charges. https://techjaja.com/mtn-uganda-reduces-mobile-money-withdraw-charges/ The Independent (May 25, 2020). MTN, Airtel re-instate mobile money sending charges. https://www.independent.co.ug/mtn-airtel-re-instate-mobile-money-sending-charges/ Tossy, T. (2014). Modeling the adoption of Mobile Payment System for Primary and Secondary School Student Examination Fees in Developing Countries: Tanzanian Experience. International Journal of Information Technology and Business Management, 27(1), 1-12. Twaha, A. (November 03, 2020). MTN cuts Mobile Money withdrawal charges. https://www.newvision.co.ug/news/1531160/mtn-cuts-mobile-money-withdrawal-charges UCC (Uganda Communications Commission) (January 30, 2020). Uganda Communications Commission Blog: Communication Sector Report – September 2019. https://uccinfo.blog/2020/01/30/communication-sector-report-september-2019/ Venkatesh, V. and Davis, F.D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46(2): 186-204. Von Allmen, U.E., Khera, P., Ogawa, S. and Sahay, R. (July 01, 2020). Digital Financial Inclusion in the times of COVID-19. https://blogs.imf.org/2020/07/01/digital-financial-inclusion- in-the-times-of-covid-19/ Walubiri, M. (January 30, 2019). Parliament wants airtime scratch cards reinstated. https://www.newvision.co.ug/news/1493402/parliament-gov-reinstate-airtime-scratch-cards World Bank Data (2020). Access to Electricity. https://data.worldbank.org/ . World Health Organisation (WHO) (January 05, 2020). Pneumonia of unknown cause – China. https://www.who.int/csr/don/05-january-2020-pneumonia-of-unkown-cause-china/en/ World Health Organisation Regional Office for Africa (2020). Coronavirus (COVID-19): WHO Africa Region Numbers at a glance. https://www.afro.who.int/health-topics/coronavirus-covid- 19 Xiao, Y. and Chorzempa, M. (May 06, 2020). How digital payments can help countries cope with COVID-19, other pandemics: Lessons from China. https://www.weforum.org/agenda/2020/05/digital-payments-cash-and-covid-19-pandemics/ Zawedde, C. (September 29, 2019). Man arrested for failure to pay 400,000shs from Wewole Airtel. https://www.kigezinews.com/man-arrested-for-failure-to-pay-400000shs-from-wewole- airtel/

Zhao, Y. and Kurnia, S. (2014). Exploring Mobile Payment Adoption in China. http://pacis2014.org/data/PACIS_mainconference/pdf/pacis2014_submission_468.pdf Zhou, T., Lu, Y. B. and Wang, B. (2010). Integrating TTF and UTAUT to explain mobile banking user adoption. Computers in Human Behavior, 26(4), 760-767.

VIII. APPENDICES Appendix 8.1: Government of Uganda Measures to Mitigate COVID-19 S/N Presidential Number Measure (s) Introduced Date of Address of Gazetting about COVID- Measures COVID-19 19 and Date Patients at the Time 1. 1st on March 0 Closure of all educational institutions to S.I. No. 52 18, 2020 disperse 15million learners spread across of 2020 of 50,688 entities effective March 20, 2020 March 24, 2020 2. 1st on March 0 Suspension of communal prayers S.I. No. 52 18, 2020 of 2020 of March 24, 2020 3. 1st on March 0 Prohibition of all political and / or cultural S.I. No. 52 18, 2020 mass gatherings such or conferences of 2020 of March 24, 2020 4. 1st on March 0 Banning all out-bound movement by S.I. No. 46 18, 2020 Ugandans to and / or through Category One of 2020 of (I) countries namely, Austria, Belgium, March 17, China, France, Germany, Italy, Malaysia, 2020 Netherlands, Norway, Pakistan, San Marino, South Korea, Spain, Sweden, Switzerland, UK, and USA 5. 1st on March 0 All returning Ugandans were allowed back S.I. No. 46 18, 2020 provided they undergo mandatory quarantine of 2020 of at their cost for 14 days March 17, 2020 6. 1st on March 0 Allowed the continued operation of the non- No S.I. 18, 2020 agricultural gathering points e.g. factories, found hotels, large plantations, markets, and taxi parks under Standard Operating Procedures (SOPs). 7. 1st on March 0 Discouraged the hexagonal, extravagant S.I. No. 52 18, 2020 Ugandan-style weddings (restricted numbers of 2020 of to utmost 10) March 24, 2020 8. 1st on March 0 Burials / Funerals restricted to a maximum of S.I. No. 52 18, 2020 10 close relatives / people of 2020 of March 24, 63

S/N Presidential Number Measure (s) Introduced Date of Address of Gazetting about COVID- Measures COVID-19 19 and Date Patients at the Time 2020 9. 1st on March 0 Suspension of weekly and / or monthly S.I. No. 55 18, 2020 markets but farm gate sales by cultivators and of 2020 of cattle keepers could continue. Fishermen were March 31, banned. 2020 10. 1st on March 0 Public Transport Systems were allowed to No S.I. 18, 2020 remain operational under Standard Operating found Procedures (SOPs) and unnecessary travel discouraged

11. 1st on March 0 Suspension of all the discos, dances, bars, S.I. No. 52 18, 2020 sports, music shows, cinemas, and concerts as of 2020 of well as other merry-making events that March 24, involve mass gatherings 2020 12. 1st on March 0 Advised the public to maintain hygiene S.I. No. 52 18, 2020 measures (wash hands with soap and water or of 2020 of sanitize; don’t touch soft parts [mouth, nose, March 24, and eyes]; stay home if you have a cold; 2020 disinfect frequent touched surfaces; and don’t shake hands or hug) 13. 1st on March 0 Advised the public on good nutrition to boost No S.I. 18, 2020 the immune system found 14. 2nd on March 1 Stopped all the passengers coming into S.I. No. 53 21, 2020 Uganda by air, land, and / or water effective of 2020 of March 23, 2020 (00:00hours) March 24, 2020 15. 2nd on March 1 Prohibited pedestrians from entry into the S.I. No. 53 21, 2020 country from the neighbouring countries of 2020 of effective March 22, 2020 (00:00hours) March 24, 2020

16. 5th on March 5 All public passenger transport vehicles were S.I. No. 55 25, 2020 stopped from operation of 2020 of March 31, 2020 17. 5th on March 5 Only food sellers were allowed to remain in S.I. No. 55 64

S/N Presidential Number Measure (s) Introduced Date of Address of Gazetting about COVID- Measures COVID-19 19 and Date Patients at the Time 25, 2020 the markets of 2020 of March 31, 2020 18. 5th on March 5 Private vehicles allowed to continue but with S.I. No. 55 25, 2020 only three (3) people maximum per vehicle of 2020 of March 31, 2020 19. 5th on March 5 Ambulances, army vehicles, security vehicles, S.I. No. 55 25, 2020 and garbage collection vehicles were allowed of 2020 of to continue moving if needed March 31, 2020 20. 6th on March 33 Imposition of curfew from 19:00hours to S.I. No. 55 30, 2020 06:30hours effective March 31, 2020 of 2020 of March 31, 2020 21. 6th on March 33 Banned the movement of all privately owned S.I. No. 55 30, 2020 passenger vehicles of 2020 of March 31, 2020 22. 6th on March 33 Suspension of activities in the shopping S.I. No. 55 30, 2020 arcades, shopping malls, and hardware shops of 2020 of March 31, 2020 23. 6th on March 33 Directed all the non-food shops (stores) to S.I. No. 55 30, 2020 close of 2020 of March 31, 2020 24. 6th on March 33 The Supermarkets were allowed to remain S.I. No. 55 30, 2020 open at that time of 2020 of March 31, 2020 25. 6th on March 33 Established food markets in Kampala and the S.I. No. 55 30, 2020 other towns were allowed to continue being of 2020 of open March 31, 2020 26. 6th on March 33 The food sellers were not allowed to commute S.I. No. 55 to and from home to work for 14 days of 2020 of 65

S/N Presidential Number Measure (s) Introduced Date of Address of Gazetting about COVID- Measures COVID-19 19 and Date Patients at the Time 30, 2020 March 31, 2020 27. 6th on March 33 Salons, lodges, and garages were ordered to S.I. No. 55 30, 2020 be shut for the subsequent 14 days of 2020 of March 31, 2020 28. 6th on March 33 Like the farms, factories were allowed to S.I. No. 55 30, 2020 remain open with camps for their workers of 2020 of March 31, 2020 29. 6th on March 33 Construction sites were allowed to continue S.I. No. 55 30, 2020 operating if they were able to encamp their of 2020 of workers March 31, 2020 30. 6th on March 33 The essential services such as the medical, S.I. No. 55 30, 2020 veterinary, agriculture, and financial services of 2020 of etc., were allowed to continue operating March 31, 2020 31. 6th on March 33 Cargo transport by train, plane, lorry, pick-up, S.I. No. 55 30, 2020 tuku-tukus, bodaboda, and bicycle were of 2020 of allowed to continue operating but only with March 31, minimum numbers of crews 2020 32. 6th on March 33 Tax collection by Uganda Revenue Authority S.I. No. 55 30, 2020 (URA) had to continue of 2020 of March 31, 2020

33. 6th on March 33 Later, gatherings of more than 5 persons were S.I. No. 57 30, 2020 prohibited of 2020 of April 09, 2020 34. 6th on March 33 The prohibitions of in-coming and out-going S.I. No. 55 30, 2020 means of transport did not include the cargo of 2020 of planes, lorries, pick-ups, and trains etc. March 31, 2020 35. 6th on March 33 Health emergencies were to be attended to as S.I. No. 55 30, 2020 and when they arose of 2020 of March 31,

S/N Presidential Number Measure (s) Introduced Date of Address of Gazetting about COVID- Measures COVID-19 19 and Date Patients at the Time 2020 36. 6th on March 33 Boda bodas to stop at 05:00pm [though S.I. No. 55 30, 2020 initially they had been proposed to stop at of 2020 of 02:00pm] March 31, 2020

Appendix 8.2: Charges of Mobile Money Service Providers (MMSPs)

Appendix 8.2.1: Charges for MTN Mobile Money

Sending Money Making Payments Withdraw Cash To Azam TV, To UMEME, NWSC, To Other Ready Pay, DStv, From Transaction Tiers To MTN To East Africa From ATM Networks School Fees, StarTimes, NSSF, Agent Solar Now Multiplex 500 – 2,500 50 830 1,000 110 190 350 2,501 – 5,000 150 940 1,150 150 600 480 1,150 5,001 – 15,000 500 1,880 1,400 550 1,000 770 1,150 15,001 – 30,000 600 2,310 1,650 650 1,600 970 1,150 30,001 – 45,000 700 2,310 1,950 750 2,100 1,350 1,400 45,001 – 60,000 850 3,325 2,250 850 2,800 1,650 1,400 60,001 – 125,000 1,000 2,500 3,200 950 3,700 2,150 2,150 125,001 – 250,000 1,150 4,975 5,000 1,050 4,150 3,950 4,000 250,001 – 500,000 1,300 7,175 9,050 1,300 5,300 7,700 6,650 500,001 – 1,000,000 1,500 12,650 17,200 3,350 6,300 13,750 11,950 1,000,001– 2,000,000 1,500 22,000 33,450 5,750 6,300 18,500 - 2,000,001– 4,000,000 1,500 37,400 55,900 5,750 6,300 25,000 - 4,000,001– 7,000,000 1,500 55,000 61,100 5,750 6,300 25,000 -

*Charge taxes are inclusive in Ugandan Shillings and are automatically deducted on process of a transaction. Transactions whilst roaming are additionally charged to local charges. Paying for Goods & Services with MoMoPay is FREE Daily transaction limit: UShs 7 000 000 Minimum account balance: UShs 0 Maximum account balance: UShs 15 000 000 Minimum transaction amount: UShs 50

Appendix 8.2.2: Charges for Airtel Money

TRANSFER BILL PAYMENT WITHDRAWAL

Utilities (UMEME, Sending to Sending to Pay Bill; Goods & NWSC, Pay Tv, Transaction Tiers Unregistered & From Agent ATM Withdrawal Registered Users Services Multiplex Parking Offnet users ) 500 – 2,500 250 1,000 110 190 330 - 2,501 – 5,000 500 1,000 140 330 440 - 5,001 – 15,000 1,000 2,000 500 1,000 700 1,100 15,001 – 30,000 1,000 2,200 500 1,600 880 1,100 30,001 – 45,000 1,000 2,800 500 2,000 1,210 1,320 45,001 – 60,000 1,000 2,800 550 2,650 1,500 1,320 60,001 – 125,000 1,500 4,400 660 3,500 1,925 2,035 125,001 – 250,000 1,500 8,400 950 3,950 3,575 3,795 250,001 – 500,000 1,500 11,000 1,250 5,050 7,000 6,325 500,001 – 1,000,000 2,000 21,000 3,200 10,700 12,500 11,385 1,000,001 – 2,000,000 2,000 40,000 5,500 20,500 19,800 2,000,001 – 3,000,000 2,000 70,500 10,000 40,000 35,200 3000001 – 4,000,000 2,000 70,500 10,000 40,000 35,200 4000001 – 5,000,000 2,000 70,500 10,000 40,000 49,500

Appendix 8.2.3: Charges for UTL’s M-Sente Sending money to Making Payments Withdraw Cash Registered and Non Transaction Tiers Bills School Fees Agent ATM registered Users 500-2,500 200 150 120 200 500 2,501-5,000 450 200 140 300 500 5,001-15,000 900 500 500 600 800 15,001-30,000 900 1,000 500 800 1,100 30,001-45,000 900 1,250 500 900 1,200 45,001-60,000 900 1,800 500 1,000 1,500 60,001-125,000 1,400 2,500 500 1,250 3,000 125,001-250,000 1,400 2,800 800 2,500 5,000 250,001-500,000 1,400 4,000 1,000 4,200 10,000 500,001-1,000,000 1,800 8,000 3,000 8,000 12,500 1,000,001-2,000,000 1,800 10,000 5,000 15,000 15,000 2,000,001-4,000,000 1,800 12,000 5,000 30,000 0 >4,000,000 1,800 5,000

Appendix 8.2.4: Charges for Africell Money

TRANSFER BILL PAYMENT WITHDRAWAL

Utilities Sending to Sending to Pay Bill; (UMEME, Africell & ATM Transaction Tiers Unregistered Goods & NWSC, Pay Tv, From Agent Other Withdrawal Customers Services Multiplex Networks Parking ) 500 – 2,500 250 880 110 150 250 - 2,501 – 5,000 500 880 150 300 300 - 5,001 – 15,000 1,000 1,900 300 700 800 - 15,001 – 30,000 1,000 1,900 450 1,200 820 - 30,001 – 45,000 1,000 1,900 5,00 1,500 1,100 - 45,001 – 60,000 1,000 1,900 500 1,800 1,100 - 60,001 – 125,000 1,600 4,200 600 3,000 1,300 - 125,001 – 250,000 1,600 7,700 900 3,500 2,560 - 250,001 – 500,000 1,600 11,000 1,250 4,000 4,360 - 500,001 – 1,000,000 2,000 21,000 2,500 7,000 8,500 - 1,000,001 – 2,000,000 2,000 38,000 3,500 12,000 15,440 -