mobile money: use, barriers and · pdf filereport july 2013 mobile money: ... 4 mobile money:...

SUmmary report

July 2013

mobile money: USe, barrierS and opportUnitieS

HigHligHtS from Wave one of tHe financial inclUSion tracker SUrveyS (fitS) in pakiStan, Uganda and tanzania

in 2012, intermedia launched the three-year financial inclusion tracker Surveys project (fitS) in pakistan, tanzania and Uganda. the project, commissioned by the bill & melinda gates foundation, features annual panel-based surveys conducted on a national scale.

an analysis of the survey data is presented in annual country research reports as well as periodic country updates based on mini-surveys conducted three times a year. this summary report includes key findings from all three countries.

fitS data and analysis are intended to support the work of the gates foundation, development organizations, mobile operators, regulators and others who are active in m-money ecosystems. the surveys are also facilitating analysis of m-money’s impact on household financial behaviors.

Uganda Tanzania Pakistan

2 Mobile Money: Use, Barriers and Opportunities

Key HigHligHTs

M-money adoption levels varied by demographic characteristics Among households across all three countries, poor households (living on less than $2 a day) and rural households were well represented among households with m-money users. Among individuals in Uganda, Tanzania and Pakistan, education and age were the biggest factors in determining the likeli-hood of using m-money—in Pakistan, gender was another key factor in determining the likelihood of m-money use, with more men using m-money than women.

Regardless of their location, households using m-money were generally more active users of basic financial services (e.g., remittances, payments and savings) and advanced financial services (e.g., banking, borrowing, lending and insurance) than households without m-money users.Sending and receiving remittances for regular support (e.g., allowances to older parents or money for a school payment for younger children) was the most frequent application of m-money services across the three countries. In Tanzania and Uganda, m-money was also used frequently as a savings instrument.

Mobile Money Use—Key Barriers and DriversThe key barriers to m-money adoption and use included insufficient awareness of m-money, poor understanding of the range of available services, and low-quality service by m-money agents. The latter includes, in particular, agent absenteeism, low liquidity, and agents’ rudeness.

Personal recommendations and the use of m-money by family and friends of the respondents emerged as important drivers of m-money registration.

M-Money Use in 2012

Country

Households with at least one m-money user

% of all households

% of poor households (<$2/day)

% of rural households

% of poor rural households

Uganda 21 15 16 13

Tanzania 35 29 25 23

Pakistan 5 5 5 5

FiTs WAVe one sUMMARy—Key sTATisTics

Source: InterMedia FITS study of households in Uganda, February-March 2012, N=3,000; in Tanzania, April-May 2012, N=2,980; in Pakistan, May-September 2012, N=4,940.

Base: poor households in Uganda n=2,380; in Tanzania n=2,198; in Pakistan n=4,120; rural households in Uganda n=2,600; in Tanzania n=2,199; in Pakistan n=3,369; poor rural households in Uganda n=2,192; in Tanzania n=1,814; in Pakistan n=2,921.

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FiTs WAVe one sUMMARy

levelS of mobile money adoptionIn 2012, one in five Ugandan and one in three Tanzanian households had at least one m-money user. The use of m-money services among Pakistani households was at five percent.

According to the 2012 FITS survey, 35 percent of house-holds in Tanzania had m-money users, and 33 percent had m-money users who had an account registered in their name. In Uganda, 21 percent of households had m-money users, and 16 percent had registered users.

In the follow-up mini-surveys in Uganda and Tanzania, 10 to 15 percent of the households reported registering new m-money accounts.

In Pakistan, 5 percent of households reported using m-money and 0.3 percent had a registered user during the first wave of FITS. Follow-up surveys showed no significant change in the uptake.

While the majority of households with m-money users in Uganda and Tanzania had at least one registered account, over-the-counter (OTC) services dominated m-money use in Pakistan. OTC services are designed to allow m-money agents to perform customer transactions using customers’ mobile phones. Registration is not required to make OTC transactions, and registered m-money users can also use OTC services.

USer demograpHicSIn all three countries, the level of m-money adoption among rural households and poor households (living on less than $2 a day) was significantly lower than the level of m-money adoption among all households in the sample.

Although Pakistan is in the early stages of m-money adop-tion, proportions of m-money-using households among urban and rural, as well as among poor and well-off house-holds, were similar.

In Tanzania and Uganda, urban and well-off households (living on more than $4 a day) were overrepresented among those using m-money. However, poor and rural households also were using m-money services, although at a lower rate than well-off and urban households.

While there was little difference in the level of m-money adoption between poor and rural households, those that were both poor and rural were the least likely among all demographic groups to use m-money services.

glossARy

banked households—Households that reported saving money in at least one bank account (including microfinance institutions) in the six months prior to the survey.

e-float—When accepting deposits of cash from customers, a mobile money provider issues a commodity known as “e-float,” measured in the same units as the national currency and held in a registered account under a user’s name. When a person sends/receives money through an agent, the agent must have e-float (money on the agent’s account) available to transfer to the recipient’s account. Otherwise, the transaction cannot take place.

m-money—mobile money.

non-remittance payments—Formal payments sent to the government, educational institutions, formal financial institutions (e.g., banks) or private businesses. Non-remittances include payments of taxes, fines or fees, utility bills, goods, debt or insurance payments. Payments might include formal credit disbursements and repayments.

over-the-counter (otc) transaction—A mobile money transaction method akin to a Western Union wire transfer where the customer does not have an account, but simply hands over cash to an agent. The agent then facilitates the transaction on the customer’s behalf using their own mobile money account. OTC services are limited and do not reflect the full range of financial services available to m-money registered users.

remittances—Money or its equivalent (food or goods) sent from one household to another. Remittances include any informal credit and debt repayments between family members or friends who live elsewhere, any repayment of debts, or payments for goods and services.

Uptake—The use of mobile money using a personal account, an agent’s account, or another person’s account (e.g., family members, relatives, friends or neighbors).

Urban households—Urban households are defined according to their location in urban enumeration areas as prescribed by the Federal Bureau of Statistics.

rural households—Rural households are defined according to their location in rural enumeration areas as prescribed by the Federal Bureau of Statistics.

Sim card—A removable micro-card that contains a subscriber identity module that securely stores the electronic codes used to verify subscribers’ identities on mobile phones and computers.



Figure 2. Mobile money markets in Uganda, Tanzania and Pakistan—households using m-money, by service provider

More than 1 provider, 8%

M-sente only, 1%

Warid Pesa only, 1%

MTN M-money only, 87%

Airtel Money only, 3%


Tigo Pesa only, 18%

Easy Pesa only, 0.1%

Vodacom M-Pesa only, 53%



Ufone Upayment only, 1%

MCB Mobile only, 0.4%

Telenor Easypaisa only, 89%

UBL Omni only, 7%


M-sente only, 1%

Warid Pesa only, 1%




Tigo Pesa only, 18%








UBL Omni only, 7%

Uganda households (n=616)


M-sente only, 1%

Warid Pesa only, 1%




Tigo Pesa only, 18%








UBL Omni only, 7%

Tanzanian households (n=1,041)

Pakistani households (n=256)

market SHareMTN Money and Telenor Easypaisa dominated m-money markets in Uganda and Pakistan, respectively. In Tanzania, Vodacom M-Pesa led the market, but some competition among m-money providers was evident.

According to the 2012 FITS survey, 96 percent of m-money users and 74 percent of registered users in Uganda used MTN Mobile Money either exclusively or in combination with other m-money services. Pakistani Tele-nor Easypaisa was used either exclusively or in combination with other services by 92 percent of Pakistani households with m-money users.

In Tanzania, Vodacom M-Pesa was the leading provider of m-money, used by 53 percent of the households with m-money users. Tigo Pesa and Airtel Money ranked second and third for single-provider use, respectively. The follow-up surveys in Tanzania, however, showed that Tigo Pesa was aggressively expanding its customer base throughout 2012.

Among individual household members in all three countries, those aged 55+ and those with no formal education were the least likely to be m-money users. Gender disparity in m-money use was most pronounced in Pakistan with men more likely to be users than women.

Regardless of the specific country, the lower the levels of education and the higher the ages of individual household members, the less likely they were to report using m-money or having a registered m-money account. Access to mobile phones and ownership of SIM cards between these two subgroups were on par with the general population.

Only 5 percent of current m-money users in Pakistan were females. However, at the time of the main survey, access to mobile phones and SIM-card ownership among Pakistani females was at 38 percent.

Figure 1. Percentage of poor households and rural households reporting m-money users and registered m-money users, by country

Percentage of poor households with registered m-money users

Percentage of poor households with m-money users

Pakistan (n=4,120)Tanzania (n=2,198)Uganda (n=2,380)

Percentage of rural households with registered m-money users

Percentage of rural households with m-money users

Pakistan (n=3,369)Tanzania (n=2,190)Uganda (n=2,600)

12%

16%

25%

0.3%

5%

23%

15%

29%

0.3%

11%

27%

■ Percentage of households with m-money users ■ Percentage of households with registered m-money users

5%

Poor

Rural


InterMedia 5

mobile money information SoUrceSFigure 3. sources of information about m-money and drivers of m-money uptake and registration

Source: InterMedia FITS study of households in Uganda, February-March 2012, N=3,000; in Tanzania, April-May 2012, N=2,980; in Pakistan, May-September 2012; N=4,940.

For each country, the base sample is the sum of all registered users of all providers. Some users were registered for and interviewed about more than one provider. As a result, the base for this chart is larger than the actual number of registered users in the sample.

barrierS to USe and regiStrationLow awareness, insufficient understanding of m-money services and poor services from m-money agents were the main barriers to m-money uptake and registration.

In the first wave of FITS, 40 percent of Pakistani house-holds and 32 percent of Ugandan households were unaware of the services compared with only 13 percent of house-holds in Tanzania.

Those who did use m-money in Pakistan, but preferred the over-the-counter (OTC) option, were comfortable using an agent and did not see the need to register their own account.

In Tanzania and Uganda, registered and nonregistered users reported insufficient understanding of the range of financial services available to them via m-money. Another barrier to m-money uptake, particularly in rural Uganda, was agent location. In some rural areas, respondents reported that m-money agents were located too far from their house-holds, and respondents were reluctant to travel long dis-tances to access m-money services.

Registered users in Tanzania and Uganda also struggled with unsatisfactory service from m-money agents. In partic-ular, users were faced with agent absenteeism (agents were not at their locations when they were supposed to be), or insufficient liquidity (agents did not have enough cash or e-float) to help with transactions.

Although most registered users first learned about m-money services from the media, an individual’s social circle was a key factor in uptake. A large propor-tion of m-money users in all three countries reported they started using m-money and/or registered for the services because of either a personal recommendation or because there was an m-money user among their family, friends or other acquaintances.

Rural respondents were more likely to name radio as their first source of information about m-money, while urban residents were more likely to learn about m-money from TV. However, a recommendation from someone within a respondent’s social circle is a frequently mentioned stimulus to adopting m-money services. The research also showed the lack of m-money users within one’s personal network is a reason for not registering for m-money, especially in Paki-stan. However, the FITS study did not provide direct evi-dence to show that information from one’s social network leads to higher rates of adoption and/or registration.

With the increase in m-money use since 2008, when Vod-acom launched M-Pesa in Tanzania, word-of-mouth is gain-ing ground as a frequent source of information about m-money services. In Tanzania and Uganda, respondents who started using m-money services in 2011and 2012 were more likely than respondents who started using between 2008 and 2010 to learn about the services from other peo-ple, including family, friends and business acquaintances.

Although media (TV and radio in particular) remain the main source of information about m-money, a personal recommendation is the key driver of m-money registration.

M-money agent

Another person

Media

Pakistan(OTC users,

n=234)

Tanzania(registered users,

n=1,120)

Uganda(registered users,

n=523)

■ Media ■ Another person ■ M-money agent

58%

66%

36%

80%

36%

20%

1%

0.1%

0%

How did you first learn about m-money services?

52% Registered because of a personal recommendation

32% Registered because of a personal recommendation

Lack of personal recommendation is also a barrier to registration. 12% Never registered because no one in their network is registered


driverS of USe and regiStrationThe reasons households gave for using m-money services varied by country. In Uganda and Tanzania, m-money services were most frequently used to deliver remittances and store savings. In Pakistan, m-money also accommodated informal loan payments and business-related transfers.

In all three countries, m-money services are most frequently used to send or receive remittances that are part of regular support (e.g., monthly allowances to young children or elderly parents). Sending or receiving occasional emergency help is the second most popular application of the services.

In Pakistan, m-money also frequently accommodated busi-ness-related transfers among friends. Some of the business-related remittances were deliveries or repayments for informal loans.

Figure 4. Use of m-money for various financial operations by households (HH) with m-money users


Used m-money for insurance

Used m-money for loans

Sent/received payments via m-money

Saved money on an m-money account

Sent/received remittances via m-money

Pakistan (n=256 HHs with m-money users)

Tanzania (n=1,041 HHs with m-money users)

Uganda (n=616 HHs with m-money users)

■ Sent/received remittances via m-money ■ Saved money on an m-money account ■ Sent/received payments via m-money■ Used m-money for loans ■ Used m-money for insurance

52%56%

39%

1%

50%

3%6%7%

3% 0.3%

25%

34%

0.4%5%

26%

In Uganda and Tanzania, m-money had a prominent role as a savings method for households with m-money users. In Pakistan, the use of m-money as a savings instrument was negligible, possibly because few households have an account registered in their name and storing money on somebody else’s account is perceived as unsafe.

In Pakistan, one-quarter of households that use m-money used the services to send or receive non-remittance pay-ments; in Uganda and Tanzania, less than 10 percent of households with an m-money user did so. This difference might partially be explained by the fact that, in Pakistan, m-money uptake was initiated by the formal banking sector as a service for formal payments, while in East Africa, mobile money started as a service for informal transfers between individuals.

Using m-money to pay for any type of insurance was rare in all three countries.

InterMedia 7

tHe financial beHaviorS of HoUSeHoldS USing mobile moneyThe financial activities of households with m-money users were more varied than households with nonusers of the services. Similarly, poor households with m-money users were engaged in more financial activi-ties than poor households without m-money users.

When reporting on their financial activities in the past six months, poor households with m-money users were more likely to say they sent or received remittances and pay-ments, saved money and owned a bank account than households with no m-money users. They were also more likely to be banked and to borrow money.

In all three countries, households using m-money were more likely to choose formal financial institutions (a bank

Figure 5. Financial activities of poor households with and without m-money users, by country

Source: InterMedia FITS study of households in Uganda, February-March 2012, N=3,000; in Tanzania, April-May 2012, N=2,980; in Pakistan, May-September 2012; N=4,940.

or a microfinance institution) as opposed to informal com-munity-level organizations/groups for their savings. Despite this, households still considered a hiding place an impor-tant savings instrument.

Households using m-money were less likely to choose hand-delivery or other types of personal delivery methods for sending or receiving remittances and payments than were households with nonusers of the services.

Due to relatively low uptake and registration of m-money in Pakistan, the differences in financial behaviors between poor households with and without m-money were less pro-nounced than in Uganda or Tanzania.

Poor HHs without m-money users (n=2,028)

Poor HHs with m-money users (n=352)

Owned insurance

Lent moneyBorrowed money

Had a bank account

Sent/received payments

Sent/received remittances

Saved money



Owned insurance


Had a bank account



Saved money



Owned insurance


Had a bank account



Saved money

20%

34%

13%

30%

8% 8%

Uganda

97%

15%

88%

42%

3% 2% 5% 1%

8%20%

9%17%

4% 6%

75%

15%

50% 54%

2% 1%12%

4%

94%96%

3%14%

6% 5%

40%

9%

36%28%

1% 1% 3% 2%

■ Poor HHs with M-money users (n=352) ■ Poor HHs without m-money users (n=2,028)

Tanzania

Pakistan


AboUT inTeRMediAInterMedia (www.intermedia.org) is a consulting group with expertise in applied research and evaluation. We help clients understand, inform and engage people worldwide—especially in challenging environments. InterMedia’s offices are located in Washington, D.C., London and Nairobi, and we work with a global network of research partners.

Clients active in international development, global media and strategic communication come to us for insight on how people gather, interpret, share, and use information from all sources and on all platforms. We provide guidance and impact assessment for strategies focused on engagement, behavior change, content delivery and the use of communi-cation technologies for social benefit.

InterMedia promotes knowledge-sharing through a range of online and offline resources, including AudienceScapes (www.audiencescapes.org)—a research dashboard providing data and analysis of media and communication environments in developing countries. We are also committed to strength-ening research capacity in the countries where we work.

HeadquartersWashington, D.C.Tel: +1.202.434.9310

interMedia europelondon, u.K.Tel: +44.207.253.9398

interMedia AfricaNairobi, KenyaTel: +254.720.109183

www.intermedia.org For general inquiries: [email protected]

The Financial Inclusion Tracker Surveys (FITS) project was carried out with funding from the Bill & Melinda Gates Foundation. All survey materials and data resulting from this study are the property of the Gates Foundation, but the findings and conclusions within are those of the authors and do not necessarily reflect positions or policies of the foundation.

MeTHodologyThe InterMedia FITS household surveys in Pakistan, Tan-zania and Uganda are three-year panel studies consisting of annual waves of face-to-face household surveys in Uganda (N=3,000 households), Tanzania (N=2,980 households) and Pakistan (N=4,940 households), and three telephone mini-surveys per year based on the same households, con-ducted between each annual wave.

The core of the wave questionnaire covering households’ financial behaviors is generally the same in all three coun-tries to allow for cross-market comparisons. Some sections and questions, however, are tailored to the local context to allow for a more accurate assessment of the development of m-money in different financial, regulatory and socio- cultural environments.

The InterMedia FITS surveys are designed to collect trend data primarily about m-money use and overall financial behaviors at the household level—that is, the data repre-sents collective usage patterns for entire households. The households for this panel were selected from a random sam-ple frame and, thus, their usage and behavior patterns are representative of usage and behavior patterns of households in the respective countries in general.

In addition to the household-level data, the surveys gather data on behaviors and experiences with m-money services based on interviews with individual over-the-counter (OTC) users (in Pakistan), and with individual registered users of m-money services (in Uganda and Tanzania) among mem-bers of the selected households.

Separate reports address the first wave surveys in Uganda, Tanzania and Pakistan, and can be found on audiencescapes.org/fits.

Author: Anastasia Mirzoyants

Subsequent FITS survey reports will monitor market growth and measure whether challenges to greater adoption of m-money have been overcome, particularly among the unbanked and those living at the bottom of the pyramid.

InterMedia FITS data, reports and related analyses are dis-seminated to stakeholders in the financial access commu-nity, both in the countries studied and globally, to help inform policies and practices in the field of financial inclu-sion. InterMedia is also making the data and analyses avail-able on AudienceScapes, www.audiencescapes.org/FITS.

For more information: [email protected]

© 2013 InterMedia. All Rights Reserved.

A special note of thanks goes to the following individuals and organizations for their support and contributions to this study: Peter Goldstein, Tim Cooper, Dixie Avugwi, Abdinasir Abdi, Hugh Hopestone, Michelle Kaffenberger, Max Richman, Mary Ann Fitzgerald, Diane Buric, TNS Kenya, PIPO Pakistan, and SwissPeaks.

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