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The Rise of Mobile Savings in Kenya

Gabriel Demombynes and Aaron Thegeya

World Bank

August 2011

Abstract

The mobile revolution has transformed the lives of Kenyans, bringing not just communications but also basic financial access in the form of mobile-phone based money transfer and storage, led by the M-PESA system introduced in 2007. New potential for mobile money has come with the rise of interest-earning bank-integrated mobile savings systems, beginning with the launch of the M-KESHO system in March 2010. We examine the mobile savings phenomenon, using data collected in special survey in late 2010. We show that the usage and reach of bank-integrated mobile savings systems like M-KESHO remains limited and largely restricted to better off Kenyans. However, what we term “cash mobile savings”—the use of simple mobile money systems as a repository for funds—is widespread, including among those who are otherwise unlikely to have any savings. These results suggest that mobile money is already a valuable savings tool for many Kenyans, and that bank-integrated mobile savings tools like M-KESHO have potential to reach a wider market.

Part of this paper draws in work done with Frederick Owegi for the World Bank’s December 2010 Kenya Economic Update. The views expressed in this paper are the authors’ alone, and in no way reflect those of the World Bank, its Executive Directors, or the countries they represent.

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1 Introduction

Kenya underwent a remarkable information and communications technology (ICT) revolution

during the first decade of the millennium. At the close of the 1990s, less than 3 percent of

Kenyan households owned a telephone, and fewer than 1 in 1000 Kenyan adults had mobile

phone service. By the end of 2010, three out of four Kenyan households owned a mobile phone.1

A unique facet of the ICT phenomenon in Kenya has been the widespread proliferation of mobile

money. Starting with the M-PESA system launched by Safaricom in 2007 and later joined by

other systems, mobile money has become a fixture in the lives of Kenyans, extending a basic

form of financial access to a wide population.

Mobile money platforms have evolved since inception and have entered a new phase with the

advent of bank-integrated mobile savings products. The first such product, M-KESHO, was

launched in March 2010 as a partnership between Safaricom and Equity Bank, and other

products have been introduced subsequently.

In this paper we examine the mobile savings phenomenon, using data collected in a survey

during October and November of 2010. This is to our knowledge the first detailed study of

mobile savings based on microdata. The concept of “savings” on mobile platforms is not well

defined, and we begin by putting forward a classification of the existing innovations. We

differentiate between “cash mobile savings” and “bank-integrated mobile savings.” “Cash

mobile savings” refers to the simple storage of credit using a mobile system such as M-PESA.

“Bank-integrated mobile savings” refers to systems which include a fuller set of banking services

such as interest payments on deposits or overdraft facilities.

Our findings shed some light on the value of mobile savings for the poor. 85 percent of the

Kenyan population earns less than KSh. 10,000 per month ($4.20 per day), and 75 percent of M-

1 These 1999 telephone ownership figures are based on census data, the 1999 mobile phone figures are drawn from the International Telecommunications Union statistical database, and the 2010 mobile ownership figure is the authors’ estimate, based on a combination of survey and census data (2009 census, 2008/2009 Demographic and Health Survey, and the 2009 Access to Finance survey) plus data from the Communications Commission of Kenya on growth in mobile phone subscriptions.

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PESA users in Kenya earn less than KSh. 10,000 per month.2 The inflation-adjusted urban and

rural poverty lines in Kenya are currently KSh. 4,608 and KSh. 2,471 per month respectively,

and the poverty headcount in Kenya was approximately 46 percent as of 2006.3

We calculate a wealth index for the dataset, and find that average monthly savings of those in the

poorest wealth quintile are KSh. 704 (US $8.80). Additionally, 47 percent of those in the poorest

wealth quintile have no savings. Average monthly savings of those who earn less than KSh.

10,000 per month are KSh. 989 (US $12.40). Further, the poorest quintile retains on average an

M-PESA balance of KSh. 749 (US $9.40), indicating some value of M-PESA as a secure and

accessible facility even for the poorest users. This balance is comparable amongst those in the

poor and middle wealth quintiles, but lower than the balance of those in the highest wealth

quintiles.

Income and wealth index data are available for the entire dataset, while savings data are available

only for the subsample of M-PESA users. Our findings on savings behaviour are therefore

restricted to M-PESA users, and they are likely biased upwards as they imply the ability to

purchase a mobile phone. The inflation-adjusted average total expenditure of individuals in the

2nd lowest expenditure decile in Kenya are KSh. 1,350.4

The savings frequency of the poorest quintile is on average two times per month. While average

monthly savings increase as expected with wealth, we do not find evidence of higher frequency

savings by the poorest quintile. Instead, we find that individuals in the middle quintile save most

frequently.

Monthly savings of M-PESA users in

the poorest wealth quintile are 52 percent of this amount. Such high levels of savings are

unlikely, and suggest that M-PESA users are on average wealthier than non-M-PESA users.

Therefore, while mobile savings are increasing access to banking to a wider population, they are

still missing a number of those living in poverty.

We find that a higher proportion of individuals in the poorest and second-poorest wealth

quintiles save with mobile phones than with other types of savings accounts. Conversely, a

2 The granularity of data collected from the survey do not allow a more detailed analysis of income amongst poor individuals. 3 Calculated from Kenya National Bureau of Statistics KIHBS 2005/6 data. 4 Kenya National Bureau of Statistics, “Basic Report on Well-being in Kenya”, April 2007.

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higher proportion of individuals in the remaining wealth quintiles save with other types of

accounts. On average, 70 percent of individuals in the poorest wealth quintile have positive cash

balances, conditional on using M-PESA.

We also find that the relative proportion of savings amounts with M-PESA decreases with wealth

quintile. One possible explanation is that the cost and convenience of M-PESA accounts makes

these accounts relatively more attractive for the poorest quintile, given their income constraints.

If M-PESA is secure, then it also makes income less susceptible to external shocks (for example,

through pressure by relatives or through intra-household pressure).

Our findings from a logit model consumer savings choice indicate that men are more likely than

women to save on M-PESA. We also find that the likelihood of using cash mobile savings

increases with level of education. The findings suggest that individuals living in rural areas are

also more likely to use case mobile savings. We also implement a multinomial logit model of

savings amongst the following choices: only M-PESA accounts, a combination of M-PESA and

other savings accounts, and only other savings accounts. Our findings indicate that those who

save only with M-PESA are likely to be younger, less wealthy and less educated that those with

only other savings accounts.

Those who use bank integrated mobile savings are likely to have higher levels of education and

to save more frequently than those who do not. Married couples and men are also the most

likely users of this type of savings.

The paper is organized as follows. Section 2 reviews the existing literature on the broader

mobile money phenomenon. Section 3 describes how mobile money and mobile savings work in

Kenya and shows the growth of mobile money usage over time. Section 4 describes the data

analyzed in this paper. Section 5 profiles mobile savings usage and presents summary statistics

by demographic indicators. Section 6 presents an econometric analysis of mobile savings.

Section 7 concludes and considers avenues for future research.

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2 Literature on Mobile Money

Kenya stands out as a mobile money success story. Kimenyi and Ndung'u (2009) attribute the

rapid growth in Kenya's mobile banking industry to four factors: a conducive legal and tax

environment, private-public policy dialogue, strategic and prudent macroeconomic policies, and

a guarantee of the existence of a contestable market discouraging dominance by initial entrants.

Comninos et al. (2008) show that the initial success of Kenya’s mobile money transfer industry

can be attributed to the high demand for remittances generated by rural/urban migration, while

its rapid scaling is due to the mobile providers’ growth strategy.

Jack and Suri (2011) report results of a large survey of Kenyan households that use M-PESA.

They find that M-PESA reached nearly 40 percent of the Kenyan adult population after only two

years of operation. While M-PESA was initially adopted mostly by wealthier households,

adoption by less wealthy households was also increasing. Jack and Suri also find an increase in

the use of M-PESA by the unbanked population. However, their findings suggest that not

owning a mobile phone is a major constraint to the adoption of M-PESA. With regard to savings

behaviour, Jack and Suri find that 81 percent of M-PESA users use M-PESA as a savings

instrument. They also find that M-PESA users with a bank account are much more likely to save

on M-PESA than M-PESA users without a bank account. The majority of users cite ease of use

and safety as the major reasons for saving on M-PESA.

Morawczynski (2009) suggests that incomes of rural mobile money transfer recipients have

increased due to remittances, which have also led to higher savings by households. His results

are based on an ethnographic study conducted in Kibera, a slum in Kenya, in 2007. Participants

in a study by Plyler et al. (2010) ranked money circulation as the most important effect of mobile

money, and credited mobile money with boosting local consumption. The flow of remittances

into rural areas was perceived to have increased local economic activity because M-PESA

enabled “just-in-time” remittances that made capital available when it was most needed.

Preliminary results from Mbiti and Weil (2010) also suggest that the growth of M-PESA in

communities has been associated with increases in local farm employment.

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Mbiti and Weil (2009) find that the major use of M-PESA is for transfers, and conversely that

there is extremely little storage value. They estimate the M-PESA velocity for a typical unit of

e-float at 11.0 to 14.6 transactions per month. They also estimate that the average number of

transactions between creation and destruction of a unit of e-float is close to one. This suggests

that the majority of M-PESA use is of the form of a cash deposit, followed by an e-float transfer,

and finally a cash withdrawal. However, a significant number of survey respondents indicate

that they use their M-PESA accounts as a vehicle for saving. Mbiti and Weil also find that M-

PESA use decreases the use of informal savings mechanisms such as ROSCAs, and increases the

probability of being banked.

Other important benefits of M-PESA include increased security of funds, and the empowerment

of women. Hughes and Lonie (2007) suggest that mobile money transfer is more secure and cost

effective than alternative methods of money transfer, such as using couriers or friends. Focus

group participants in Plyler et al. (2010) highlight the greater security they enjoy because they

are able to keep funds as mobile money, rather than at home in cash. Men in Kibera, Nairobi’s

largest slum, focus on the aspect of physical danger due to mugging, which has decreased

because fewer people carry large amounts of cash. Likewise, other respondents in the study

indicate that local businesses and street vendors often convert their cash to M-PESA at the end of

the day for safekeeping. Additionally, mobile money empowers women by giving them an

independent place to store and manage funds that is private and inaccessible to other family

members.

Survey data examined by Aker and Mbiti (2010) show that current users of mobile money

transfer in Kenya tend to be wealthier, better educated, urban and already banked, with most

transfers occurring within urban areas and remittances being smaller but more frequent. On the

basis of a study of 409 small business entrepreneurs in Kenya, Mbogo (2010) finds that for

micro-businesses, factors responsible for adoption and continued usage of mobile money transfer

include convenience, support, cost, satisfaction and security.

Camner and Sjöblom (2009) compare the adoption of M-PESA in Tanzania to adoption in

Kenya. They find much lower adoption rates in Tanzania, which are explained by the lower

mobile telephony market share of Vodacom, which is the M-PESA provider in Tanzania, its

inability to build a strong agent network, and its lower marketing budget. Other factors are

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Tanzania's generally lower GDP growth, smaller proportion of unbanked population, higher

financial illiteracy, more dispersed population and the absence of a national ID.

Aker and Mbiti (2010) develop the theory of the general mechanisms through which mobile

phones remove constraints to social and economic progress. They assert that improved access

and use of information reduces search costs and facilitates co-ordination among agents, thereby

increasing productive and market efficiency. Mobile phones also create employment and

increase incomes by spurring demand for mobile-related services. In addition, mobile phones

enable social networks to respond more immediately to idiosyncratic shocks, thereby reducing

household exposure to risk.

3 The Basics of Mobile Money and Mobile Savings

3.1 What is Mobile Money?

Mobile money systems consist of electronic money accounts that can be accessed via mobile

telephones. They are often likened to simple banks, although a basic mobile money system does

not pay interest or provide loans. Each of the mobile service providers in Kenya currently has a

mobile money service. Safaricom’s M-PESA was introduced in March 2007; Zain’s Zap (now

known as Airtel Money) was initiated in February 2009; yuCash, started in December 2009; and

Orange’s Orange Money was launched in November 2010. The following description is based

on M-PESA, which is by far the largest system, although the other systems are similar.

To have a mobile money account and make a deposit, a customer must own a cell phone SIM

card with the mobile operator and register for a mobile money account. The customer then can

make cash deposits at the physical offices of one of the operator’s mobile money agents These

cash deposits create electronic money credit in the customer’s account.

Customers can make person-to-person transfers of mobile money credit to the accounts of other

mobile money users on the same network. They can also use their mobile money credit to pay

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bills and to buy phone airtime. Withdrawals (conversion to cash) can be made at the offices of

the network’s mobile money agents. It is also possible for a mobile money customer to make a

transfer to someone who is not registered with the same network. In this case, when notice of the

transfer is received in the form of an SMS text message, the recipient can receive the cash at a

mobile money agent.

After a slow start in 2007, mobile money usage grew rapidly through 2008 and 2009.

Extrapolating from data through April 2010, we estimate that the value of person-to-person

transactions alone exceeded 20 percent of GDP as of December 2010 (see Figure 1).5

Due to the

rapid growth of mobile money usage, the portrait of mobile money users is a moving target.

Figure 2 summarizes various sources on total numbers of mobile money users. Mobile phone

subscriptions within the figure represent the total number of M-PESA customers, Zap

subscribers, and yuCash subscribers, based on data from each of the three providers through

August 2010. Mobile phone and mobile money subscriptions are projected to December 2010

based on recent growth. We project that the number of mobile money customers as of December

2010 was near 15 million, equivalent to roughly 2 out of every 3 Kenyan adults.

3.2 What is Mobile Savings?

M-PESA, the first mobile money system in Kenya, was originally developed primarily as a

money transfer device and was attractive because it allowed people to send remittances across

distance at low cost. The system has become popular for other uses, including storing credit. The

term “mobile savings” has been used to describe this phenomenon. While the term “savings”

could have various meanings, conceptually we employ the term to refer to storage of funds not

required for immediate short-term usage.

We distinguish between three types of mobile savings:

• Cash mobile savings. This is simply the use of a standard mobile money system such as M-PESA to store funds. Cash mobile savings do not earn interest.

5 These figures do not include mobile money bill payments or transfers from companies to individuals.

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• Fully integrated bank mobile savings. This term refers to direct access to an interest-bearing account via mobile phone. M-KESHO is the leading example.

• Partially integrated bank mobile savings. This is the linking of a mobile money system to a standard bank account, allowing transfers between the two systems.

The fully integrated bank mobile savings model has the advantage of not requiring a mobile

phone subscriber to already have a bank account. This access potential leverages the mobile

service provider’s existing network of agents, which outnumber the number of bank branches by

a factor of 100 to 1 (Mas and Radcliffe 2010).

Mobile savings products have increased rapidly: as of December 2010, there were at least seven

alternatives available in the market.6

The first mobile savings platform in Kenya was launched

in March 2010. M-KESHO, a joint venture between Equity Bank and Safaricom offering a fully

integrated service, grew to 613,000 subscribers in the six months after its launch. The market

has since rapidly expanded as more banks have structured agreements with the mobile service

providers. Bank-mobile service provider partnerships are not exclusive, and banks are seeking

agreements with multiple mobile service providers with the ultimate aim of providing universal

access to their diverse client account bases. Additionally, banks are beginning to build their own

agent networks in order to assume a more competitive bargaining position in accessing mobile

service platforms.

Partially and fully integrated savings present different types of contracts amongst the partnering

bank and mobile service provider. A partially integrated product clearly delineates the role of

the bank, which provides and owns banking services, and the mobile service provider, which

provides the mobile telephony infrastructure and controls the agent network. The bank

compensates the mobile service provider for access to the network and enjoys the remaining

profits. This type of contract more closely resembles a debt contract between the parties. A

fully integrated solution may not draw the same distinction between bank and mobile service

provider. In this case, the distribution of surplus depends on the relative bargaining power of the

6 Alternatives include M-KESHO, Pesa-Pap, KCB Connect, Pesa Chap Chap, ZAP/Standard Chartered, NIC Bank M-PESA link, Co-op Bank M-PESA link.

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bank and mobile service provider. This type of contract more closely resembles an equity

contract between the parties. Equity-like contracts are likely to be more complex and therefore

more difficult to negotiate than debt-like contracts, thereby presenting a potential hurdle towards

the goal of increasing access.

4 Data

4.1 Data Description

We analyze mobile savings data from a survey conducted by the Financial Sector Deepening –

Kenya, in October to November 2010. Mobile savings data were collected using systematic

sampling with implicit stratification, where sub-locations were used as the primary sampling

units. Household data were collected for 6,083 observations. These observations were then

categorized into M-PESA users and non-users. Mobile savings data were then collected for the

M-PESA users, comprising a subsample of 2,692 observations. An extra 103 observations were

collected by the snowballing method to boost the sample of M-KESHO users. These

observations were dropped from the analysis. Individual probability weights are used to make

the sample nationally representative.

The survey was not conducted in North Eastern province due to insecurity in the region. Mobile

savings data collected include general financial product usage, savings behaviour, mobile phone

ownership and usage, M-PESA usage, mobile savings awareness and usage, and M-KESHO

usage.

The dataset only considers savings with M-PESA, and therefore excludes Zap and yuCash – both

launched in 2009. As of 2010, Safaricom accounted for 78 percent of the mobile phone market

by subscribers.7

7 Safaricom Annual Report 2010.

In addition, M-PESA accounts for the majority of the mobile money market.

Therefore, an analysis of M-PESA gives a clear view of trends in the major segment of the

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market. Bank-integrated savings products included in the dataset are M-KESHO, Pesa Pap,

KCB Connect, Pesa Chap Chap, ZAP/Standard Chartered, NIC Bank M-PESA Link, and Co-op

Bank M-PESA Link.

A wealth index is created using principal components analysis and used to group survey

respondents by wealth quintile. To create the wealth index, we follow the approach established

by Filmer and Pritchett (2001), where principal components analysis is used to determine the

weights to assign to the assets included in the index. The index weights are given by the first

principal component, which is the linear index of all the variables that captures the largest

amount of information that is common to all of the variables. Importantly, this approach

assumes that household long-run wealth explains the maximum variance in the asset variables.

The variables included in the wealth index are household items (for example radio, bicycle

refrigerator, microwave), quality of toilet facilities (for example flush toilet or pit latrine), quality

of water source (for example piped water into dwelling or rainwater), quality of walls (for

example stone or mud), quality of roofing material and number of habitable rooms in the

household.

4.2 The Concept of Savings

Survey respondents are asked to indicate whether they save with mobile money (through M-

PESA). Specifically, each respondent is asked “Do you save any portion of your income?”

Those who respond “Yes” are then asked “Where do you save your money?” The options

included, which are not mutually exclusive, are M-PESA, MKESHO/PESA PAP/ KCB Connect,

Bank account, SACCO account, ASCA, ROSCA, Microfinance Institution and ‘Other’.

Each respondent’s response is a statement of his personal motive for using each service, as well

as an account of his subjective definition of ‘saving’. This definition may reflect the opportunity

cost of holding funds across time, or may reflect the value of services such as security and ready

geographical access to liquidity, which are key functions provided competitively by mobile

savings platforms.

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A subset of survey respondents hold positive mobile money balances on their telephones, but

they do not consider these balances as savings. For example, some individuals may transact

frequently using M-PESA and find it convenient to hold a positive balance on their phones,

which they do not consider as savings. The record these amounts, M-PESA users are asked:

“How much on average do you retain on your M-PESA account?”

Summary statistics and econometric analyses take both views into account, as it is difficult

objectively to define the concept of savings. Two sets of analyses are presented: first, an

analysis of individuals who consider their mobile money balances as savings; and second, an

analysis of individuals who hold on average positive balances on their mobile phones,

independent of whether or not they consider their balances as savings.

Bank-integrated mobile savings are not subject to the same ambiguities encountered with cash

mobile savings. All individuals using bank-integrated products are considered to save with these

products.

5 Summary Statistics

All summary statistics and econometric analyses are conditional on usage of M-PESA. Table 1

gives a summary of the sub-sample of M-PESA users for whom mobile savings data were

collected. Forty five percent of individuals in the sample are M-PESA users, and 54 percent of

M-PESA subscribers are male. In addition, 40 percent of these users are from urban areas.8

A comparison of the entire sample to the 2010 Kenya population census shows that sample data

are roughly representative of the Kenyan population by gender, region (province) and age. The

data are relatively undersampled by urban setting. The analysis of mobile savings is limited to

those who save with M-PESA because the dataset does not include savings information for those

Compared to the entire sample, the distribution of M-PESA users by age is similar to that of the

entire sample. However, M-PESA users are more concentrated in the middle and upper wealth

quintiles.

8 The largest concentration of mobile phone subscribers is in Nairobi, at 83 percent, and the lowest at the Coast Province, at 51 percent.

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who do not use M-PESA. All analyses are performed on the data with the above caveats in

mind.

We distinguish between two definitions of savings: stated cash mobile savings and positive cash

mobile balances. Stated cash mobile savings refer to those individuals who answer “yes” to the

question “do you save your money on M-PESA?” Positive cash mobile balances refer to those

individuals who on average have a balance of above zero in their mobile money accounts (that is,

those who do not load money onto their accounts only for the purpose of immediate remittance).

Thirty seven percent of M-PESA users save with M-PESA, but only 6 percent of M-PESA users

use bank-integrated savings. A comparison of stated cash mobile savings and positive cash

mobile balances shows some differences in adoption patterns. 37 percent more individuals hold

positive balances on their mobile phones than those who consider their mobile phone balances as

savings. Table 2 shows that while stated cash mobile savings are relatively higher in rural areas,

positive cash mobile balances are more prevalent in urban areas. This suggests that individuals

in rural areas are more likely to perceive their mobile phones as savings devices than individuals

in urban areas, who may be more likely to view their phones as transactions devices.

Additionally, Table 2 highlights that the penetration of stated cash mobile savings is

approximately the same as the penetration of other traditional types of savings accounts for

younger individuals (those below the age of 24), while the penetration of other types of accounts

is higher for older individuals. Further, the penetration of cash mobile savings is higher for those

who are relatively poorer (those in the poorest and 2nd poorest wealth quintiles). This relatively

higher access suggests that mobile phones are able to provide some relative utility for lower

wealth individuals that they cannot access from other types of accounts. Additionally, it is

remarkable that cash mobile savings penetration levels are rapidly approaching those of

traditional savings accounts, given that the mobile money market is still new.

Table 2 also shows that adoption rates of bank-integrated savings products are low in general

across Kenya. Many of these products were introduced in Kenya in mid to late 2010, and

therefore our analysis is only preliminary. However, we note that the types of contractual

agreements between mobile service providers and banks will influence the success with which

bank-integrated products will be rolled out.

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According to Table 3, 79 percent of those saving with M-PESA save at least once a month. Men

save more frequently than women, and savings frequency increases with age. We are unable to

find any evidence that individuals in lower wealth quintiles save more frequently than those in

higher wealth quintiles. Our findings suggest that those in the middle wealth quintile save most

frequently.

Table 4 gives savings statistics by wealth quintile. Those in the poorest quintile save on average

KSh. 704 per month, and earn on average KSh. 6,862 per month. Income data are collected by

income bracket where the lowest category is “Less than KSh. 10,000”. We take the mid-point

for each income bracket, and are therefore likely overstating income. However, the amounts

saved by individuals in the lowest wealth quintile of the sample suggest that mobile savings

products, while rapidly increasing access to savings, may still not be reaching the very poorest

Kenyans. For these individuals, the costs of using mobile savings may not be sufficient to justify

uptake.

Average monthly savings given any type of account are of similar magnitude to average monthly

savings for those who hold only M-PESA accounts, for lower wealth quintiles. However,

savings in other types of accounts are significantly higher than savings for those who hold only

M-PESA accounts for middle and higher wealth quintiles. Additionally, the average M-PESA

balance for the lowest wealth quintile is significantly higher than the balances for other low to

middle wealth quintiles.

Access to liquidity ranks as the most popular use of M-PESA savings. Almost 80 percent of

those saving with M-PESA list access to funds for emergencies as one of the top three reasons

for using M-PESA. In addition, almost 40 percent list access to funds for meeting day-to-day

household needs are one of their top three reasons. Of those using mobile savings, security ranks

as one of their top reasons for adopting the service. 79 percent of those using mobile savings list

the ability to save money safely as one of their top reasons. The ability to link to another account

ranks high as well, with 46 percent valuing this service.

6 Econometric Analysis

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We perform two sets of econometric analyses, on stated cash mobile savings and positive

average cash mobile balances. Table 5 shows the results of a simple logit model of savings

choice amongst those who use M-PESA. The dependent variable equals ‘1’ if the individual has

savings of any kind, and equals ‘0’ if the individual has no savings. The results are highly

significant. As one might expect, savings are more likely for individuals with higher levels of

education, monthly income and wealth. More strikingly, the odds of saving are 24 percent

higher for men than women. In addition, the odds of married couples saving are 54 percent

higher than for unmarried individuals. Complex intra-household relationships, roles and relative

status have an impact in determining these effects. While only significant at the 10 percent level,

the odds of mobile savings in rural areas are 29 percent higher than the odds in urban areas.

Table 6 shows the results of a multinomial logit model on three mutually exclusive categories:

individuals with only M-PESA accounts, individuals with M-PESA accounts in addition to other

savings accounts (including M-KESHO), and individuals with only other savings accounts.

“Other” savings accounts include bank accounts (including microfinance institutions), ROSCAs,

SACCOs and ASCAs. The base outcome is other savings accounts.

The results show that relative to those with only traditional savings accounts, those individuals

using only M-PESA accounts are likely to be young, with lower levels of education, lower

wealth and lower monthly income. M-PESA may therefore provide a savings alternative to

younger, poorer individuals that enables them to enjoy services that they would otherwise not be

able to enjoy elsewhere. These results are robust across both definitions of savings, as reflected

in the second panel of Table 6. The analysis shows that those who use a combination of M-

PESA and other accounts do not differ significantly from those who use only other accounts.

Table 7 runs a simple OLS regression of average M-PESA balances. The results show that

average M-PESA savings increase with household income, wealth and education. We estimate a

simple logit model that determines the probability that a given individual uses M-KESHO in

Table 8. The results show that take-up of M-KESHO is higher amongst wealthier and older

individuals, and also amongst those who save more frequently on M-PESA. Take up is also

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higher amongst men and married couples. M-KESHO is a relatively new product in the market,

and therefore the results are only suggestive.

7 Conclusion

In this paper we have performed a first analysis of mobile savings in Kenya. We have

introduced the concept of cash mobile savings, which refer to simple cash balances maintained

on mobile phones, and performed a relative analysis of these types of savings with innovative

new bank-integrated mobile savings products in Kenya, as well as with traditional types of

savings. We have shown that mobile money savings have increased rapidly since the mobile

money market was created, and savings levels are rapidly approaching those of existing

traditional instruments. Additionally, a majority of the population of M-PESA users keep

positive mobile balances even though they do not consider these balances as savings. These

users enjoy savings-like characteristics such as secure storage while still maintaining access to

liquidity.

We find despite the benefits of access to mobile savings, our lowest wealth quintile of those who

use M-PESA saves on average KSh. 704 per month. This suggests that mobile savings are still

not accessible to the poorest individuals, who perhaps may not be able to afford mobile phones,

or for whom mobile transactions costs are still prohibitively high. However, we have also shown

that of those who have access to mobile savings, those who use only mobile savings are younger,

less educated and less wealthy. By implication, these services are offering additional utility to

some individuals for whom other formal or informal types of savings are relatively costly.

Mobile savings are new and continue to expand rapidly by geography and sophistication.

Regulatory concerns are a key issue to address as credit over mobile phones is offered through

products such as M-KESHO. The M-PESA platform itself may present skewed incentives for

mobile service providers’ other departments if failure of the platform would present systemic

risks to the economy. Risk-taking in vending mobile products may be encouraged if the

government offers an implicit guarantee against failure to mobile service providers.

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Further research is necessary to gain a clearer understanding of the impacts of mobile savings on

access and welfare. Our results suggest that take up of mobile savings is higher for men and

married couples, but additional research is necessary to shed light on the disparities in uptake.

Further, a more detailed study of the take up of mobile savings amongst the poorest individuals

is necessary as our findings suggest these individuals are still excluded.

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8 Bibliography

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Appendix

Figure 1: Mobile Money Person-to-Person Transfers as % of GDP

Transfers and GDP data are provided by Safaricom, Zap, and the Central Bank of Kenya.

Figure 2: Population Age 15+, Mobile Phone Subscriptions, and Mobile Money Customers

in Kenya

Mobile subscriber statistics are provided by Safaricom, Zain, yu, and the Communications Commission of Kenya.

Population and age distribution statistics are taken from the World Development Indicators. The dotted lines

indicate projections based on recent growth rates. A large jump in mobile money customers in July 2010 occurred

during the month when the Government of Kenya initiated the requirement that all SIM cards be registered. It is

likely that the jump occurred because many people took the opportunity of registering their SIM card to sign-up for

mobile money accounts.

0%

5%

10%

15%

20%

25%

2007 2008 2009 2010

Monthly Value of Person-to-Person Transfers as % of GDP

0

5

10

15

20

25

Mill

ions

Population age 15+Mobile phone subscriptionsMobile money customers

21

M-PESA Users Entire Sample 2009 Census

Gender% Male 54% 50% 49%

Setting% Urban 40% 32% 38%

Age Group18 - 24 27% 30% 29%25 - 34 36% 32% 32%35 - 44 13% 19% 19%45 - 54 15% 12% 12%55 - 64 8% 7% 7%

Wealth Quintile% Poorest 13% 28%% 2nd Poorest 17% 18%% Middle 21% 18%% 2nd Wealthiest 22% 18%% Wealthiest 27% 18%

Province% Central 13% 12% 13%% Coast 7% 9% 9%% Eastern 18% 16% 15%% Nairobi 11% 9% 12%% Nyanza 15% 15% 14%% Rift Valley 27% 28% 26%% Western 9% 12% 11%

Marital Status% Married 61% 55%% Single 35% 36%

Number of obs. 2692 5980

Table 1: Comparison of the M-PESA sample to the 2009 census data

Source: Authors' analysis of FSD-Kenya survey data.Notes: 2009 census percentages are for individuals between the ages of 18 and 64. 2009 census percentagesexclude North Eastern province to allow comparison with the sample, which excluded North Eastern province dueto insecurity. Kolmogorov-Smirnov tests by age and wealth index are rejected at the 1 percent level ofsignificance for the M-PESA sample against the entire sample.

22

Stated cash mobile savings

Positive average cash mobile

balancesBank-integrated mobile savings

Other types of savings accounts

Average 37% 74% 6% 48%

GenderMale 38% 75% 7% 49%Female 35% 72% 4% 47%

SettingUrban 34% 78% 6% 53%Rural 39% 71% 5% 45%

Age18 - 24 37% 71% 6% 36%25 - 34 37% 75% 6% 51%35 - 44 40% 76% 6% 56%45 - 54 36% 72% 6% 53%55 - 64 31% 75% 1% 52%

Wealth Quintile% Poorest 33% 70% 3% 29%% 2nd Poorest 42% 70% 2% 34%% Middle 37% 70% 6% 42%% 2nd Wealthiest 38% 77% 5% 56%% Wealthiest 34% 79% 9% 66%

ProvinceCentral 45% 79% 7% 61%Coast 25% 72% 7% 45%Eastern 33% 65% 5% 51%Nairobi 23% 78% 4% 50%Nyanza 41% 75% 6% 50%Rift Valley 37% 72% 5% 41%Western 51% 85% 5% 39%

Number of obs. 2692 2425 2658 2692

Table 2: Summary statistics of stated cash mobile savings, positive average cash mobile balances, and bank-integrated mobile savings

Source: Authors' analysis of FSD-Kenya survey data.Notes: Stated cash savings correspond to respondents who answer "yes" when asked whether they save on M-PESA.Positive average cash mobile balances correspond to individuals who on average have a balance greater than zero on theirM-PESA accounts. Bank-integrated mobile savings correspond to Pesa Pap, KCB Connect, Pesa Chap Chap,ZAP/Standard Chartered, NIC Bank M-PESA Link, Co-op Bank M-PESA Link and M-KESHO. Other types of savingsaccounts include Bank, SACCO, ASCA, ROSCA and microfinance accounts. Other types of accounts are recordedindependent of M-PESA accounts.

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Daily Once a week Every two weeks Once a month Less often

Average 4% 21% 18% 35% 21%

Age

Less than 20 10% 8% 7% 58% 17%20 - 29 4% 21% 16% 39% 20%30 - 39 4% 19% 25% 30% 23%40 - 49 3% 24% 19% 28% 26%50 and above 7% 27% 17% 29% 20%

Gender

Male 5% 23% 20% 31% 21%Female 3% 19% 17% 39% 21%

Source: Authors' analysis of FSD-Kenya survey data.

Table 3: M-PESA savings frequency by age group and gender

Wealth quintile

Average monthly savings

(KSh)

Average monthly savings given any

type of account (KSh)

Average monthly savings given

MPESA account only (KSh)

Average MPESA account balance

(KSh)

Average Monthly Income

(KSh)Poorest 704 1,333 1,412 749 6,862 2nd Poorest 908 1,551 1,048 761 7,709 Middle 1,361 2,314 1,256 711 7,512 2nd Wealthiest 1,583 2,320 1,409 1,020 7,875 Wealthiest 2,940 3,954 1,956 1,777 13,419

Average 1,673 2,619 1,364 1,066 9,220

Source: Authors' analysis of FSD-Kenya survey data.

Table 4: Average savings statistics by wealth decile

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Rural 0.2574 *

(0.1366)Male 0.2146 **

(0.1029)Age 0.0076

(0.0057)Married 0.4299 ***

(0.1109)Education 0.0869 ***

(0.0173)Wealth quintile 0.1204 **

(0.0516)Log household income 0.3363 ***

(0.0782)

Number of observations 2266

Table 5: Logit model of consumer savings choice

Source: Authors' analysis of FSD-Kenya survey data.Notes: The dependent variable is denoted by 1 if theindividual has any stated cash mobile savings, and zerootherwise. An individual has savings if he responds "yes"when asked whether he saves on M-PESA.

25

Rural 0.1622 0.3211 * -0.1103 -0.0029(0.2152) (0.1908) (0.2597) (0.2141)

Male 0.1769 0.1079 0.0878 -0.0217(0.1584) (0.1214) (0.1829) (0.1475)

Age -0.0374 *** -0.0101 -0.0221 ** 0.0033(0.0088) (0.0068) (0.0097) (0.0082)

Married 0.0410 0.2173 0.1802 0.3519 *

(0.1740) (0.1444) (0.2057) (0.1807)Education -0.0979 *** -0.0036 -0.0701 ** 0.0544 *

(0.0257) (0.0224) (0.0314) (0.0285)Wealth quintile -0.2559 *** 0.0390 -0.0594 0.2244 ***

(0.0761) (0.0664) (0.0904) (0.0844)Log household income -0.3875 *** -0.0475 -0.4513 *** -0.0804

(0.1219) (0.1066) (0.1540) (0.1510)

Number of observations 1523 1409

Source: Authors' analysis of FSD-Kenya survey data.Notes: The base outcome is "other accounts", which include bank accounts, SACCOs, ROSCAs, M-KESHO and ASCAs. All observations corresponding to no savings are excluded.

Table 6: Multinomial Logit models for stated cash mobile savings and positive average cash mobile balances

M-PESA OnlyM-PESA and Other Accounts M-PESA Only

M-PESA and Other Accounts

Stated cash mobile savings Positive average cash mobile balances

26

Rural -423.57(436.05)

Male 306.54(286.10)

Age 15.43(12.20)

Married 197.18(341.54)

Education 114.83 **

(50.73)Wealth quintile 269.87 **

(127.45)Household income 0.05 **

(0.03)Savings frequency 0.81

(2.05)Bank account -24.90

(280.04)SACCO account -822.02

(574.95)ROSCA account 1293.93

(861.36)

Number of observations 787R-squared 0.07

Source: Authors' analysis of FSD-Kenya survey data.

Table 7: OLS regression of average M-PESA balance

27

Rural -0.0201(0.0222)

Male 0.0430 ***

(0.0163)Age -0.0015 *

(0.0009)Married 0.0489 ***

(0.0177)Education 0.0041

(0.0025)Wealth quintile 0.0058

(0.0075)Log household income 0.0392 ***

(0.0135)Log savings frequency 0.0124 *

(0.0071)

Number of observations 826Adjusted R-squared 0.05

Source: Authors' analysis of FSD-Kenya survey data.

Table 8: Logit estimates for M-KESHO users