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Financial Inclusion and Gender Equality 1

How can M-pesa model be implemented in Pakistan to financially involve the lower-bottom of the income group

pyramid?

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Abstract

Studies are available on mobile payment (MP) from most emerging markets, yet there is sparse research from Pakistan on how it can improve financial inclusion and equality. This qualitative study explores the socioeconomic conditions in Kenya and Pakistan, respectively. It examines how to utilize the successful strategy of M-Pesa to contemplate a MP Service that is accessible to all levels of society. We analyze the influencing factors in Pakistan through market analysis, semi-structured interviews and surveys conducted with rural women. We argue that in order to improve financial inclusion and gender equality in Pakistan, the penetration rate of the MP Service must be able to reach critical mass amongst all income levels and social strata. Furthermore, our findings reveal that there is a gender digital divide due to technophobia and the lack of gender-friendly technology, which leaves the poor population and especially women financially excluded. Therefore, to improve financial inclusion and gender equality one must consider the specific socioeconomic context and provide a MP Service that is able to reach all residents. Our work provides researchers with a societal context when addressing the digital and financial divide, and sheds a light on the unbanked and disenfranchised population of Pakistan.

Key words: Mobile payment, financial inclusion, gender equality, bottom of the pyramid, Kenya, M-Pesa, socioeconomic factors, gender analysis, women, rural population, Pakistan.


1. Introduction

In developing countries, a large part of the population is financially underbanked and unbanked besides there are various mobile services are available. The need for financial inclusion has prompted emerging economies to embrace technological development, showing rapid growth in mobile phone penetration (Prahalad, 2005) and enabling the market for mobile payment platforms to evolve and expand (Gallup, 2011). There are studies available on mobile banking and person-to-person transactions from most emerging markets, yet, there is sparse research from Pakistan on how mobile banking adoption can improve financial inclusion and equality for the disenfranchised population.

The most noteworthy development within mobile payment (MP) and financial inclusion is accredited to the Kenyan MP solution, M-Pesa, created by Safaricom (Mas & Ng‟weno, 2009). Despite the success in Kenya, a similar country such as Pakistan struggles to provide financial inclusion to its population. Thus, the research in this paper is motivated by the underlying reasons for why Kenya was able to successfully implement a MP Service that improves financial inclusion and gender equality for a significant part of its rural and poor residents, when a comparable country such as Pakistan struggles to achieve similar results. This leads to the following puzzling questions:

What barriers are preventing a higher uptake of mobile pay accounts considering the limited access to formal banking in Pakistan?

Why is there a significant gender gap in terms of financial inclusion in Pakistan?

While we examine the socio-religious, economic and technological disparities between two countries, we will dwell on our following research question:

Whether M-Pesa’s strategy of Kenya be used for financial inclusion in Pakistan?


2. Theoretical Background

Numerous operators around the world have attempted to develop their own service, yet few have come close to the success of M-Pesa. In order to determine why the existing services have not achieved a similar success to M-Pesa and if such a solution could be applied in Pakistan, it is necessary to identify significant differences in the respective societies that could pose barriers towards its implementation. In order to do so, it is significant to realize that all organizations as well as products and services exist in a context of a complex technological, economic, social and cultural world. This external environment is composed of variables that exert influence on a given product or service and give rise to opportunities and barriers when attempting to implement these (Cornelissen, 2008). Therefore, this paper employs the DESTEP analysis, as it examines the external environment and clarifies how to best deal with such macro-economic factors and how to adjust one‟s strategy accordingly (Van Vliet, 2010). But before we start with the in-depth analysis, it‟s important to understand the intrinsic characteristics of M-pesa, the prevailing conditions of the mobile money market and the reasons behind M-pesa‟s unprecedented success.

KENYA PAKISTAN

Company Date of Launch

Market Share

Company Date of Launch

Market Share

Safari-Com: M-Pesa

March 2007 65% Telenor

EasyPaisa October 2009 64%

Airtel Money November

2010 18%

Mobilink Mobicash

November 2012 20%

Equitel July 2015 7% UBL-Omni April 2010 14%

Mobikash July 2011 6.7% Ufone Upaisa November 2009 1%

Tangaza Pesa January 2011 1.9% Zong Timepey December 2012 0%

Orange Money

November 2010

0.7% MCB Lite July 2014 1%

2.1. M-Pesa – Kenya

Safaricom‟s MP solution, M-Pesa, has around 20 million users in Kenya alone (Mas & Ng‟weno,

2009). The initial idea of M-Pesa was to enable the population to handle the financial

obligations of micro-loans (Pirson, 2011). When developing the service, Safaricom invested

massively in a marketing campaign with a single message: Send Money Home. Moreover,

Safaricom utilized focus-groups of women to explore their usage patterns and needs;

consequently the female and rural penetration rate was a large part of M-Pesa‟s success (Mas &

Ng‟weno, 2009). M-Pesa‟s significant improving of gender equality and financial inclusion is the

reason Kenya is chosen as the base country. Moreover, Kenya is focusing on the most

marginalized segments of its society, namely girls, by combating illiteracy through mandatory

primary school (UNICEF, 2014) and advancing girls‟ education through ICT4D (Information

Table 1: Mobile Money Market Comparison - The Dominant Solutions


Communication Technologies for Development) initiatives such as mLearning (Mobile

Learning) (ICT4D.org, 2016). The extraordinary growth has continued ever since, with M-pesa

now holding in excess of 65% market share of the Kenyan mobile money market. (CA Kenya,

2016).

2.2. Mobile Payments in Kenya – Competition and Market Players

With the advent of Mobile Payments system by M-pesa, companies offering conventional credit-transfer services greatly suffered. Gikunju (2009) examined the financial statements of Kenya‟s Postal Corporation‟s Postpay money transfer service and found out that their revenues and profits had significantly declined. Likewise, Western Union‟s and Moneygram‟s profits (see Appendix) also declined. He concluded that despite cutting their commission rate from 7% in 2003 to 3% in 2010, these companies were still unable to match M-pesa‟s competitive structure and convenience.

Table 2: Kenya Mobile Money Market 2016

An examination of current structure of Kenya‟s mobile money market emphasizes the sheer magnitude of M-pesa‟s dominance over its rivals. M-pesa leads the way with more than 17 million subscribers and a market share in excess of 65%. M-pesa‟s closest rival, Airtel Money‟s market share of 18.5% epitomizes the lead M-pesa has established over its competitors (CA Kenya, 2016).

2.3. Development & Evolution of M-pesa in Kenya

Prior to M-Pesa‟s launch, transferring money securely and instantaneously was a distant dream for many Kenyan families (Mbiti & Weil, 2011). M-pesa originated with a core service offering of P2P payments, overtaking the conventional methods of money transfers such as personal trips, public transports and relatives (Mas & Radcliffe, 2011). The figure below [FSD-Kenya (2007a and 2009a)] reflects how M-pesa revolutionized the Money transfer market in Kenya, with all sources seeing a substantial dip in the use of their services.

BB Players Agents SubscriptionsNumber of

Transactions

Value of

Transactions

(Ksh)

Mobile

Commerce

Transactions

Value of Mobile

Commerce (Ksh)

P2P Transfers

(Ksh)

M-Pesa 107,936 17,120,278 307,993,348 807,087,001,206 168,511,133 323,188,944,204 366,025,969,054

Airtel Money 13,944 4,853,869 8,864,578 10,897,099,926 8,864,578 10,897,099,926 5,983,016,437

Orange Money 18,518 193,831 33,000 191,440,000 1,388 803,544 4,290,879

Equitel 0 1,860,647 56,912,705 138,525,612,300 49,952,916 70,085,121,850 63,305,627,780

MobiKash 16,733 1,772,466 2,068,425 373,539,114 25,107 24,523,365 118,753,106

Tangaza 1,596 503,556 - - - - -

Total 158,727 26,304,647 375,872,056 957,074,692,546 227,355,122 404,196,492,889 429,454,640,819

Kenya Mobile Money Market - June 2016

Figure 1: Money Transfer behaviour before and after M-Pesa


M-pesa‟s adoption was widely helped by the absence of reliable money transfer facilities, with majority relying on unauthenticated and unregistered local options such as hand-to-hand and bus transfers. Since these options were unlicensed and unsecured, there was considerable risk that these payments may not reach their rightful recipients on time. Similarly, Kenya‟s premier formal service, Kenya Post, was considered to be slow and expensive. Thus the lack of strong existing alternatives also allowed potential customers to swiftly switch to a newer alternative.

Taking into account the many positives of M-pesa, such as payment security and convenience, Safaricom opened up M-pesa to institutional payments avenue, thereby allowing firms to make institutional payments such as salaries and bill payments. Apart from P2P and institutional payments, M-pesa can also be used for microfinance loan disbursements, humanitarian aid distribution and international money transfers. It can be thus said that M-pesa has now evolved into a multi-purpose retail payments platform, rather than a standard money transfer scheme. (Eyring & Johnson, 2011)

2.4. Reasons behind M-Pesa’s success in Kenya and other developing countries

Latent Demand, reliable service quality, security and strong brand presence were some of M-Pesa‟s strongest suites (Mas & Morawczynski, 2009). Even before M-pesa‟s launch, Safaricom already had a 77% market share in voice telephony in Kenya, with more than 13.3 million subscribers. Safaricom capitalized on their strong market presence and customer base, by venturing into the mobile money market. Strong branding scheme ensured that existing airtime resellers or agents became exclusive M-pesa agents. Similarly, the idea communicated to the public was very simple: „send money home‟, enabling people to better understand the service. The simplistic nature of the service was also matched by the efficient usability feature of the mobile application. Safaricom also maintained a strong control over retail agents through awareness campaigns and training programs, ensuring that the consumer experience remained consistent. An important feature of M-pesa success was ensuring that agents had sufficient working capital to meet customers‟ need for cash withdrawals and deposits. This was managed by master agents, who helped balance out net cash requirements of other agents. The master agents did this by transferring money from agents with surplus or positive accounts to agents with negative cash balances. The registration process was also simple to execute, with customers required to only register themselves once by filling a simple personal details form; the rest was carried out by the agent. Likewise, the charges were also transparent and straight-forward, with customers knowing in advance the amount that would be deducted for each transaction. Also, to increase service take-up, the M-Pesa users were allowed to send money to non-users, while also requiring no minimum balance conditions. Thus it can be said that M-pesa‟s success cannot be attributed to a single factor. In fact, it was consistent and thorough planning and execution that can best explain its popularity and success.

2.5. Mobile Banking Landscape of Pakistan

Currently, nearly 80% of Pakistanis have access to a mobile phone. However, there is a considerate gender gap of 42% in ownership of a mobile phone (80% men vs. 38% women) (Intermedia Pakistan FII Tracker, 2014). Moreover, 9 out of 10 families have access to a SIM card (Intermedia, 2013). Though, despite a quite robust mobile market, six years after the launch of the first branchless banking service there are only 7% registered mobile money users, of these only 0, 4% are active accounts. Furthermore, only 11% of men and 3% of women have ever used mobile money. The low number of female users could in part be due to that only 57% of women are aware of mobile money (compared to 72% of men); however, social restrictions on women could also pose a barrier (Intermedia Pakistan FII Tracker, 2014). The low number of active accounts is not caused by the lack of services, as the five largest mobile operators in Pakistan have each developed a MP Solution (Kemal & Yan, 2015). The dominant of these


services, with 13 million users, is Easypaisa created by Telenor Pakistan (McCarty & Bjaerum, 2013). A significant part of Telenor‟s strategy was the introduction of Over-The-Counter (OTC) MP services – a model that did not require registration or use of an e-Wallet. However, the OTC solution has limitations for all parties involved. Notably, a digital ecosystem will not be developed, which results in the market staying limited and costumers being left without the benefits of more advanced financial products, such as lack of savings and credit (McCarty & Bjaerum, 2013).

3. Methodology and Case Description The motivation for this study is to investigate why Kenya was able to successfully implement a mobile pay service that significantly improved its financial inclusion and gender equality while Pakistan struggles to achieve similar results. Therefore, we intent to examine the socioeconomic conditions in Pakistan in order to determine how to develop a mobile payment service that will be accessible by not solely the population living at the BoP, but by all income levels and social strata.

3.1. Theoretical Approach The research approach we find most appropriate in this paper is pragmatism. The research question does not unambiguously suggest a certain research philosophy, therefore pragmatism is chosen as it encourages studying areas of interest in different ways that bring about positive consequences within one‟s value system (Tashakkori & Teddlie, 1998). Moreover, pragmatism holds that the most important determinant of the epistemology chosen is the research question. Through the gender analysis, this paper uses some aspects of interpretivism and attempts to adopt an empathetic stance. Thus, we gain insight into the social world of the research subjects to understand their external environment and needs from their point of view (Saunders et al., 2009). In order to answer our research question we chose deductive reasoning as the most suitable research approach. However, as this paper does not provide law-like results, we present conjectures as opposed to hypotheses. To answer our research question we present the following conjectures:

C1: Whether it is necessary to contemplate the particular societal context when designing a mobile payment service?

C2: Is it important that the penetration rate of the mobile payment service reaches critical mass amongst all income levels and social strata in order to improve financial inclusion and gender equality in Pakistan?

C3: Whether educational and IT literacy must be improved in order to ensure successful proliferation of mobile money services in Pakistan?

C4: Whether Economic & financial conditions restrict the proliferation of mobile money services?

3.2. Data collection

Our study can be classified as explanatory research as we aim to establish causal relationships between variables. We do so by conducting a multi-method qualitative study utilizing several methods for collecting and analyzing qualitative data. The secondary data primarily stems from databases and annual reports collected from the World Bank, USAID, WEF and the Bill and Melinda Gates Foundation. Moreover, we utilize data from the State Bank of Pakistan, Economics Survey of Pakistan, Pakistan Bureau of Statistics as well as case studies focusing on the gender roles in Kenya and Pakistan. Using these sources we examined the socioeconomic


factors in Pakistan through macro and micro lens. On a macro-level, we did this through the DESTEP analysis. However, we also integrate the HAF gender analysis as we do not deem the DESTEP analysis sufficient in examining the socio-cultural forces in Kenya and Pakistan, respectively.

The reason for using semi-structured interviews is partly because these women are a hard-to-reach target group as many of them would not be able to receive or respond to a self-administered survey. Furthermore, we chose semi-structured interviews as the questions may lead the conversation into areas that had not originally been considered, but which are significant to address in order to answer the research question (Saunders et al., 2009). The interviews were conducted in Urdu; notes were taken during the interviews that were then translated to English. Thereafter, the interviews were summarized into a template based on the tools of the HAF for gender analysis1. A condensation of these summaries is presented and discussed further on in this paper.

Further, in September 2016, we conducted 500 semi-structured interviews in small cities, villages and towns of three major provinces of Pakistan to get a better understanding of the ground realities and the problems being faced by the people residing in these areas. The interviews were conducted in Punjab, Sindh and Khyber-Pakhtunkhawa (KPK), with an equal representation of men and women ensured. The interviews comprised of wide-ranging subjects that were primarily meant to examine their digital literacy and access to financial services. They were questioned about their use and knowledge of cellular and financial services, their personal details such as family size and income, their transactions‟ details and their decision-making powers. The results of the survey will be discussed later in the paper.

4. Results and Findings

4.1. DESTEP Analysis of Kenya and Pakistan

4.1.1. Demographic Kenya: Kenya is an East African country that is made up by 569.140,0 km2 with a population of 44million, whereof 76% live in rural areas (World Bank, 2014). The unemployment rate in Kenya is around 40% (UNICEF, 2013), which encourages rural-urban migration (Mas & Ng‟weno, 2009). Furthermore, Kenya has a high female work participation rate of 62% (World Bank, 2014) and a high adult literacy rate of 87% (UNICEF, 2013). Pakistan: The Islamic Republic of Pakistan, situated in South Asia, consists of 770.875,0 Km2 with a population of 185 million (World Bank, 2014), whereof 61% of the residents are classified as living in rural Pakistan (Ministry of Finance, 2014). Furthermore, the national literacy rate is 60% (Bureau of Statistics, 2014), with a low of only 3% female literacy rate in Khyber Pakhtunkhwa Province 2 (KP), which is the lowest in all of South Asia (USAID, 2012). Furthermore, the employment rate is 60% of the total population, however there is a female work participation rate of only 25%. Due to high unemployment, rural-urban migration occurs in a number of families (Pakistan Ministry of Finance, 2014).

2 Khyber Pakhtunkhwa (KP) Province consists of 25 districts that include 20 settled area districts and the

Provincially Administered Tribal Areas (PATA). The overall incidence of poverty is 44 percent, making KP the poorest province in Pakistan with the lowest human development indicators after Balochistan (USAID, 2012)


Global Gender Gap Report (GGGR) Rankings– World Economic Forum 2015

Measure Pakistan Kenya

Global Ranking 144 48

Educational Attainment 135 113

Economic Participation and Opportunity 143 25

Wage Equality for similar work 88 87

Estimated Earnings - Female to Male Ratio 140 11

Literacy Rate 136 107

Health and Survival 125 85

Political Empowerment 87 62

Women in Ministerial Positions 141 27

4.1.2. Economic

Kenya: Kenya has, due to economic growth, advanced from being classified as a lower income country to a lower-middle income country. The GDP per capita is $1.358, 3 (World Bank, 2014). Furthermore, the penetration rate of formal banking is quite low in Kenya. In 2006 there only existed 600 ATMs nationwide, and still in 2009 only 19% of the Kenyan population had access to formal financial institutions. This forced many people to rely on hand-to-hand delivery of remittances along with postal and bus deliveries that carry with them high risks (FinAccess, 2009). However, in 2014, 92% of the adult population used a mobile payment service to send domestic remittances, while 66% hand delivered and only 9% used money transfer operators (World Bank, 2014). Furthermore, 75% of the adult population had an account of any kind while 58% had a mobile account (Demirguc-Kunt et al., 2015; Demirguc-Kunt and Klapper, 2012).

Pakistan: Pakistan is classified a lower-middle income country with a GDP per capita of $1.334, 1 (World Bank, 2014). Pakistan has a highly unbanked population, even though it offers 8077 ATMs and a reasonable selection of financial institutions, amounting to 11.153 branches nationwide (SBP Statistical Supplement, 2014). Yet only 13% of the total population had a bank account in 2014 (Demirguc-Kunt et al., 2015), and 6% had a mobile account (Demirguc-Kunt, 2015; Demirguc-Kunt and Klapper, 2012). Even though, there is a significant unbanked market and a high access rate, in 2013, only 5% of the population was registered with a mobile money platform, such as Easypaisa. Moreover, of these 5 %, 95 % of the users were men (Intermedia, 2013)

4.1.3. Socio-Cultural

Kenya: The vast majority of Kenyan population comprises of Christians, with Islam being the second major religion of Kenya. Majority of the Kenyan Muslims identify themselves as Sunnis (Bell, 2012). Despite not suffering from the same religious constraints,

Kenyan women are subjected to similar

Kenya – Population (%) by Religion

Christianity 83%

Muslim 11.2%

None 2.4%

Other (Hindu, Budhists, Sikhs)

1.6%

Traditionalist 1.7%

Unspecified 0.2%


patriarchal constraints as many Pakistani women. According to a report published by CEDAW in 2011, only 3% of the land is owned by women with social conditions restricting a woman from inheriting land in many regions of Kenya. Likewise, due to inherently weak financial position, women also have lesser access to credit than men. Although the female-male ratio till primary education is almost level, the ratio falls as we move higher to secondary and tertiary levels (GGGR, 2014). Although there haven‟t been many recent surveys in this field recently, reports by AfDB (2007) suggest that in the agriculture sector, women are responsible for 80% of food production, 90% of weeding and 60% of harvesting and marketing of crops.

Gender roles in Kenya tend to vary depending on the ethnic groups and if they are rural or urban.

Nevertheless, women in Kenya are underrepresented in decision-making positions, and they have less access to education, land and employment (USAID, 2014). Kenya ranks 147th out 187 countries on United Nations Development Program‟s (UNDP) 2013 Human development Index (HDI), which measures life expectancy, literacy, education and standards of living. Moreover, the country ranks 122nd on the Gender Inequality Index (GII) with a combined percentage loss of 55% (the world average score on the GII is 45%) to achievements in reproductive health, empowerment and labor market participation (World Bank, 2013; Clausen et al., 2015). In order to identify and further examine the gender roles in Kenya, this analysis includes the components of the Harvard Analytical Framework.

The Activity Profile, The Access and Control Profile and the analysis of Influencing Factors:

In many areas of Kenya, the division of labor is segmented by gender. Most rural areas rely on agriculture, which accounts for 70% of the labor force, where women make up 75% of that workforce (Mwangi, 2008). Moreover, the labor demand for reproductive work spatially restrict women, due to their childcare responsibilities, as many women cannot work far from home (World Bank, 2006). Furthermore, men control access to most productive assets. In 2011, only 3% of the land was owned by women, even though it became legal in 2010 for women to have their name on a land deed. This is due to men still having control over women‟s access to land (CEDAW, 2011). However, in recent years, many gender-related laws have been passed, including a new constitution in 2010 granting equal rights regardless of gender (CEDAW, 2011). Between 2009 and 2011, Kenya was in fact the country with most improvement in gender equality laws (World Bank, 2013). Though Kenya has a highly literate population compared to other developing countries, 30% of rural women cannot read a simple sentence in their primary language (Kenya DHS, 2010). Education has since become a priority in Kenya, where primary school now is mandatory for both boys and girls (UNICEF, 2014; Clausen et al., 2015).

Pakistan: Pakistan is a predominantly Muslim majority country, with an overwhelming proportion of the total population comprising of Sunni Muslims. As a country formed in the name of religion, Pakistan‟s laws are understandably based on the foundations of Islam. Sadly, despite a number of steps taken to alleviate the prevailing gender inequality situation in Pakistan, the ground reality still remains far from ideal. The discriminatory rights conferred upon men still elevate them over women, thereby excluding women of some of the fundamental human rights in many cases. Unfortunately, policies undertaken to ameliorate the deteriorating gender inequality crisis in rural areas fail to add much substance beyond official papers (Shaheed, 2009) .

Pakistan – Population (%) by Religion

Muslim 96.28

Christian 1.59

Hindu (Jati) 1.60

Qadiani (Ahmadi)

0.22

Scheduled Castes

0.25

Others 0.07


Similarly, the discrimination permeates into the financial inclusion segment too. For example, banks in Pakistan require two male guarantors, who are not family members, to consider a woman‟s loan application. Females are barred from acting as guarantors, whereas all women are also required to get their husband‟s permission before applying for a loan. (Safavian, 2012). In many cases, women are also made to pay higher interest rates and are likelier to receive lower loan amounts. (Beck, et al., 2013).

Gender roles in Pakistan vary depending on the local norms, which differ in urban, rural and tribal areas. The Constitution of Pakistan gives men and women equal rights to own property, operate a business and to affirm their citizenship rights. Nonetheless, Pakistani women remain unequal to men in the areas of education, health, economics and politics (USAID, 2012). Pakistan ranks 146th out of 187 countries on the UNDP‟s 2013 HDI. Moreover, the country ranks 127th on the GII with a combined percentage loss of 56% to achievements in reproductive health, empowerment and labor market participation (World Bank, 2013). Poverty is predominantly present in rural areas with women suffering the most. They have little access to resources, services or assets of their own, as a result of systematic gender discrimination (IFAD, 2014). However, the concept of women‟s empowerment has recently gained more attention from policy-makers and researchers (Pakistan DHS, 2013). Furthermore, in 2010 the parliament passed seven laws protecting the rights of women and promoting gender equality (USAID, 2012; Clausen et al., 2015).

The Activity Profile, The Access and Control Profile and the analysis of Influencing Factors:

In rural areas of Pakistan, women are involved in agriculture, animal husbandry and in some areas, women work outside the home as paid laborers (USAID, 2012). However, women‟s involvement depends on several factors, one being the male economic migration. Due to unemployment, many Pakistani men migrate to urban parts of Pakistan or to neighboring countries in order to send money home to rural areas (Ministry of Finance, 2014; Clausen et al., 2015). In rural areas such as the Federally Administered Tribal Areas 3(FATA) or the KP, men are the earners and providers. Therefore, men control all important household and financial decisions in particular, while women and children must ask for permission in all matters (USAID, 2012). This however, depends on the local and family customs. On a national basis, more than half of currently married women who earn a cash-income decide independently on how to use their earnings (Pakistan DHS, 2013). Nonetheless, in the majority of rural and tribal areas, the local code, customs and religious views shape gender identities. According to the customary code, women are the guardians of family honor and the bearers of the symbolic collective identity. Restrictions to mobility, gender segregations and early marriages are all precautions to ensure that no transgressions occur. However, newer technological developments such as the mobile phone and the Internet are slowly decreasing these restrictions (USAID, 2012).

Furthermore, in areas such as FATA and KP, many children must travel for more than an hour to reach their school, and there are very few schools accessible for female students, which forces them to travel even greater distances. Therefore, there is a rather low level of schooling beyond primary school, particularly among female students (Pakistan Bureau of Statistics, 2014). This lack of education causes a lack of mobile literacy, which is a challenge for women‟s usage of mobile phones, as some women do not even know how to dial a number (Siegmann, 2009). Moreover, the overall lack of information among men and women leads to women and girls

3 The Federally Administered Tribal Areas (FATA) is a belt of seven semi-autonomous tribal agencies and six smaller areas that separate the tribal agencies from the rest of Pakistan. Ninety-seven percent of FATA‟s approximately four million people live in rural areas. FATA is much poorer than Pakistan as a whole, as indicated by their performance on human development indicators (USAID, 2012).


often being required to ask for permission to use a mobile phone, as the use of mobile phones as well as other electronics by women is stigmatized (Siegmann, 2009).

4.1.4. Technological Kenya: Kenya has proven to be a fast growing country in terms of technological development and innovation. Mobile phone penetration has reached 81% in Kenya (CA, 2014) with an access rate of 87% (Siddiqui, 2014). Furthermore, 95% of the geographic area has mobile network coverage, leaving only 5% of the country without network access (GSMA, 2013). However, the proportion of the Kenyan population covered by electricity is only 23% (CA, 2014) Pakistan: Pakistan has shown considerable growth within technological development. The overall mobile penetration rate in Pakistan has amounted to 73%, where 94% of the urban population and 52% rural population have access to mobile phones. Nonetheless, only 25% urban women and 9% rural women have access to a mobile phone (Intermedia, 2013). Moreover, the power quality in Pakistan is considerably low, with unstable streams of electricity; formal electricity is especially rare in rural communities (USAID, 2013).

4.1.5. Ecological Kenya: There is a growing wave of financial inclusion initiatives (Kerr, 2011), as emphasized by the United Nations Millennium Development Goals (MDG). The MDGs deemed information and communications Technology (ICT) to be an important tool in improving social and economic conditions in the world‟s poorest countries (Pirson, 2011). Several companies have already begun targeting low income consumers, as we have seen in Kenya with M-Pesa, which succeeded in including BoP consumers. M-Pesa, thereby shows that providing financial inclusion can positively impact a society and create profits for stakeholders.

Pakistan: Though CSR is a relatively new phenomenon and is mostly practiced as relief work (Paryani, 2010), the initiatives for financial inclusion has started to emerge in Pakistan. An example hereof, is Easypaisa‟s cooperation with the Benazir Income Support Program and CARE International (Minischetti, 2014). Easypaisa has engaged in an area where it can make a difference in society while making profits, as it gains goodwill and more customers.

4.1.6. Political

Kenya: Regulation of mobile money can help secure trust in new a mobile money solution. Nonetheless, regulation may constrain the implementation of a mobile money application by limiting the solutions operator‟s freedom in structuring the business model, service proposition, and distribution channels (Mas & Radcliffe, 2010). However, since mobile money was a new phenomenon when introduced in Kenya Safaricom, had a “first mover advantage” with M-Pesa (Oyebode, 2014). Safaricom had a good working relationship with the Central Bank of Kenya and was given regulatory space to design M-Pesa in a manner that suited its market, without having to adapt its business model to fit within an existing regulatory model (Mas & Radcliffe, 2010). Furthermore, when considering the political forces in Kenya, the level of corruption is quite relevant. Kenya is ranked 145th out of 175 on the Corruption Perception Index (CPI), where 1 is the least corrupt country. This means that Kenya is a highly corrupt country (Transparency Int., 2013) Pakistan: The State Bank of Pakistan (SBP) was motivated to support financial inclusion in Pakistan, as this could lead to large amounts of informal international remittances being moved

Shortlisted Provinces for Survey

Punjab Sindh Kpk

Taunsa Sharif Dadu Domel

Kot Addu Nawabshah Naurang

Ferozwala Paharpur

Sohawa

Hasilpur


into the formal banking sector. Therefore, SBP started working on new branchless banking regulations, which were introduced in 2008, before any market initiative had appeared. However, SBP have made it a prerequisite to have a banking license, therefore mobile operators must adapt their business models, as Easypaisa did by gaining 51% ownership of Tameer Microfinance Bank. Different types of branchless banking accounts have since been introduced with proportional “Know Your Customer (KYC)” efforts and reduced risks (Minthe, 2015). Moreover, in regards to the political forces in Pakistan, the level of corruption must be included. Transparency International ranks Pakistan 126th out of 175 countries on the CPI, which makes Pakistan a corruption-prone country (Transparency International, 2015).

4.2. Unbanked Population Interviews

In terms of primary data, we initially conducted 29 semi-structured interviews in October 2015. These interviews were carried out with women living in rural and semi-rural areas in the Punjab region. The women were targeted because the rural population and especially women were a large part of M-Pesa‟s success. Moreover, the findings in the DESTEP analysis suggested that the gender roles in Pakistan could pose a significant barrier for the implementation of mobile payment and therefore needed to be investigated further. The women interviewed were between 23-50 years of age. A majority of 86% were married while the remainders were divorced, widowed or un-married. While 55% were completely illiterate, 10% had a primary level education and 34% had an education above the primary level. Furthermore, 55% of the women were employed and brought in the income solely or collectively with their husbands. Though many women were illiterate and extremely poor, 100% had access to a mobile phone, yet not all had control of their usage or owned their own phone.

4.3. Unbanked Population Survey

The second wave of surveys was conducted in September 2016. A total of 500 interviews were conducted, with unbanked population being the focal point of our survey. The interviews were conducted in villages and smaller cities, targeting people belonging to the lower ebb of the economy. A total of 500 interviews were conducted in three major provinces of Pakistan, i.e. Punjab, Sindh and KPK. 50 interviews each were conducted in 5 towns of Punjab, 2 of Sindh and 3 of KPK. Our literature review and DESTEP analysis earlier had strongly suggested that it was important to understand the gender roles of Pakistan, as the intrinsic characteristics of Pakistani society could act as a possible impediment in the proliferation of mobile financial services. Therefore, we insured that the interviews recorded had an equal representation of men and women. The respondents were mainly quizzed about their personal details, Occupational skills, digital literacy, decision-making opportunities, education status and access to financial services.

We targeted middle-aged population ranging between 26 and 50 years, with 63% of the respondents under 35 years old. In accordance with the usual conventions of larger family size in rural areas, only 35% of the population had equal or less than 5 family members, with 16% reported having family members in excess of 10. Despite having large families, the number of working individuals in the family was not proportionately high, as 63% had 2 or less working members. 96% of the population was employed, engaging in numerous activities including farming, shop-keeping and working in a government institute or a factory. Understandably, the income levels were also low, with nearly 70% reported earning less than rupees 20,000 per month. The total household income also followed a similar trend, with 71.1% of the population earning less than 35,000 rupees monthly. The earned income was spent on usual expenses including groceries, utility bills, health and education. Almost the entire population had some sort of education, though only 33.7% of the population had education beyond high-school level. A vast majority of the population could read and write Urdu, but only 39% of the population had complete command over English. 55% of the population said they couldn‟t operate a computer,


though 94% reported that they could operate a mobile phone. 63% of the population reported lack of internet access, though 52% reported that they knew how to use the internet. 52.2% were using internet for social networking or entertainment purposes only. Interestingly, 88% of the respondents reported owning a cell phone and having complete access to it. Due to a lack of internet knowledge and 3G/4G services, it is understandable that majority did not possess a smartphone. In excess of 60% of the population said that they had the decision-making power to study or to go to work. 21% of the respondents used mobile money for paying bills, though majority preferred the conventional methods of going to bank or post office to pay their fees. Interestingly, mobile money was the most used method of money transfers between cities, as 54% reported using it. The average amount of transactions was mainly under 10,000 rupees and 9.5% reported sending an average amount of more than 20,000 rupees too. However, high charges were acting as a hindrance in the use of these services, as 70% were of the opinion that they found transaction charges expensive. There was an acute lack of banking services use and knowledge, as 20% did not possess a banking account. Only 11% had a mobile money account, whereas 66% were not even aware of mobile banking facilities. A significant majority of the respondents relied on a mobile money agent in their region to carry out their banking transactions. Considering the lack of banking knowledge, it is no surprise that majority of the population reported having no ATM machine in their region. It was also interesting to note that the nearest bank for nearly 80% of the population was a government bank.

5. Discussion and Analysis

5.1. Identifying the Gaps

To be able determine how we can adapt M-Pesa‟s strategy to Pakistan, it is vital to identify the areas wherein the countries differ. These differences are likely to be the reasons why a service such as Easypaisa has not been as successful as M-Pesa. From the DESTEP analysis, we can use a data comparison of the socioeconomic factors to identify the gaps within the markets and cultures in Kenya and Pakistan, respectively.

Data Comparison - Identifying the Gaps

Attribute Kenya Pakistan

Area (KM2) 2015 580,370 796,100

Population (in Millions, 2015) 46.05 188.92

Rural population (% of Total Population, 2015) 74 61

Literacy rate (% of Adult Population, 2015) 78% 58%

GDP per Capita (in US$, 2015) 1376.7 1429.0

Human Development Index (out of 187, 2014) 145 147

Gender Inequality Index (out of 187, 2014) 126 121

Corruption Perception Index (out of 175, 2015) 139 117


Accounts at a financial Institution (% of Population 15+, 2014)

55.2 8.7

Mobile Accounts (% of Population 15+, 2014) 58.4 5.8

Mobile Penetration rate (% of Total Population) 90% 60.7%

M-Pesa accounts (in %, 2015) 65% -

Easypaisa accounts (in %, 2015) - 64%

Table 2: Data Comparison of DESTEP Analysis

Most noticeably, we can see that the countries are quite similar in several aspects. The rankings on the HDI, GII, and CPI (Transparency Int. 2014; World Bank, 2014), show that both nations suffer from low development and high levels of gender inequality and corruption. Moreover, the GDP categorizes the countries as lower-middle income economies with a high amount of the populations living in rural areas, and a high mobile penetration rate (World Bank, 2014). Therefore, it is highly interesting to investigate why the existing mobile payment solutions in Pakistan have not achieved as high a success rate as M-Pesa has, and why M-Pesa‟s strategy in Kenya cannot simply be replicated in Pakistan. The areas in which Kenya and Pakistan differ noticeably are within literacy and financial inclusion. The literacy rate in Pakistan is low compared to other developing countries. Particularly children and women in rural areas suffer from a lack of education, which also severely affects their mobile literacy, as some women cannot even dial a number. This general lack of knowledge and information leads to a distrust and misperception of new technology. Women and girls are perceived as the carriers of the family honor, therefore they are often segregated from men, and additionally technology in their hands is stigmatized and considered a threat. This restricts their mobility and significantly affects their possibilities for education, employment and financial inclusion. Furthermore, in Kenya, the percentage of the adult population with any kind of bank account is substantially higher than in Pakistan, which also applies to mobile accounts (Demirguc-Kunt et al., 2014). Moreover, the lack of financial inclusion for women is especially noticeable. This is an evident restraint to women‟s financial and gender equality.

Focusing on the differences that we have identified through the DESTEP analysis, we find it necessary to further investigate the specific socioeconomic factors that must be considered when designing and implementing a mobile payment service that aims to financially include the unbanked population. The rural population, and especially women, played a large part in the success of M-Pesa, and as the female financial inclusion in Pakistan is extremely low, our discussion moves forward with the findings from the semi-structured interviews focusing on the gender roles in Pakistan.

5.2. Societal Context

A condensation of the gender analysis conducted on the basis of the 29 semi-structured interviews with rural/ semi-rural women highlights that there are several factors that pose barriers as well as opportunities for a potential mobile payment service.


Table 3: Influencing Factors - Barriers and Opportunities

5.2.1. General-and Socio-Cultural Issues

The interviews reveal that most of the women face similar daily challenges. These challenges are mostly related to their income and their demographic location. The rural population faces daily issues such as water scarcity, unstable electricity and gas shortages that especially affect the women, as they are in charge of reproductive activities. These challenges are often costly and time-consuming for the women. Furthermore, infrastructure and physical insecurities pose barriers against women travelling to work and places of education. This has also manifested in the cultural norms where some women and particularly young girls have their mobility restricted. Most women interviewed, especially from very poor families, travelled freely by public transportation to their place of employment despite infrastructural difficulties and safety concerns, as it was necessary for them to earn an income. However, in families where women aren‟t required to work outside of the household, we can see that the mobility of women or young girls in the family is restricted. This can either be due to safety concerns or cultural norms. However, these are not unrelated, as we also uncovered in the DESTEP analysis, young girls are the bearers of the family honor. As one of the women explains, young girls are expected to get education and settle down as soon as possible. Moreover, girls are not allowed to own their own mobile phone, and there is a stigmatization of women using technology (Interview no. 29 – S, 23). Though all the women interviewed had access to a mobile phone and a number owned their own phone, a vast majority of women explained that generally in their community women are not allowed to neither own nor have control of a mobile phone. In many instances, it was explained that women have access to mobile phones but they cannot contact unknown people, while young girls are not allowed to use a mobile phone on their own.

General Issues Social-Cultural Issues

Financial Issues: creating

savings

Mobile Payment usage

Creating Awareness

Insufficient finances for daily expenses (Food, clothes, shelter, education, healthcare), Saving for children‟s weddings, Water scarcity, Unstable electricity, Sewage issues, Transportation difficulties, Physical insecurities, Gas shortages,

Mobility restrictions on women/ girls, Technophobia – girls cannot use mobile phones on their own; Women can often not own their own phone. Stigmatization of women using technology. Women manage reproductive activities; Mostly Men (Though occasionally collectively with women) manage productive activities.

Insufficient finances, Theft of cash, Paying bribes, Women do not have access to the household finances, or Male family members control the financial decisions.

Lack of awareness, Lack of information on the service, Lack of education (Illiteracy), Insufficient finances, No access to finances, Lack of skills – cannot understand the user menu, Lack of confidence that they can use the service, Stigmatization of women using the service. Do not find it relevant.

The women need the process explained in person in order to understand it or because traditional media outlets do not reach them. Some prefer the process to be explained by a friend or family member. Others can be made aware through TV, Radio, Poster ads, or Newspapers.


5.2.2. Financial issues: Creating Savings

Furthermore, all the women explained that women must manage the reproductive tasks, while both men and women can be engaged in productive tasks, such as working and managing the household finances. A majority share of 55% of the women were employed and brought in the income solely or collectively with their husbands. Moreover, 82% managed the finances solely or collectively with male family members. Though, in some cases the women were only in charge of buying groceries or paying bills and were not included in major financial decisions, such as prioritizing the money or deciding when and how to create savings. One woman stated that she manages the household, while solely her husband provides the income and manages all household finances. She cannot create savings due to the male family members dominating the financial decisions (Interview no. 22 – A, 35). However, for 66% of the women, the problems with creating savings were due to insufficient finances. Furthermore, 20% saved money in cash at home whenever possible, and 17% used a bank account to store their money. Those that could save money explained that their main issues were due to theft of cash (Interview no. 20, 24 & 28), having to pay bribes (Interview no. 19) or male family members dominating the financial decision (Interview no. 22 & 29).

5.2.3. Mobile Payment usage

Additionally, the women were asked about their mobile payment usage. Even though, the women interviewed were between 23-50 years of age with various levels of income and education, 0% of the women used Mobile payments to transfer money. A majority of 86% answered that they would use hand-to-hand delivery when needed, whereas 13% would use bank transfers. However, one woman responded that she uses mobile payment to pay utility bills, but since she does not know how to use it herself she uses OTC through her local shopkeeper (Interview no. 9 – S, 45). When asked why the women did not use mobile payments, the vast majority simply answered that they did not have any awareness of it. If they did have some awareness of it, they faced other problems such as a lack of information about the service, and lack of education and skills to use it.

Even though, we interviewed women with various levels of education spanning from none to a Master‟s degree, 55% were completely illiterate. The women that were illiterate and who had a significantly low income explained that the main barriers they faced in regards to using mobile payment were lack of awareness and insufficient finances. However, when we interviewed women with a better financial standing that had some awareness of the service further issues arose, such as lack of information about the service and lack of skills to use it. They simply do not understand the user menu. Still, some of these women were either illiterate or had a low level of education. Therefore, it was quite interesting to speak to women with a higher level of education including Bachelor‟s and Master‟s degrees who earned a substantial higher income than most of the women interviewed. These women explained the main barriers for using mobile payment was that they did not have the skills to understand it or the confidence to use it. Moreover, there exists a stigmatization of women using technology (Interview no. 24, 26 & 29).

Furthermore, the women were asked how they could be made aware of a potential mobile payment solution. A majority of women answered that they need the process to be explained to them in person. It could either be due to a lack of skills or confidence that they could not understand it on their own, or because traditional media outlets, such as TV, radio and poster ads do not reach them. Some literate women preferred to be informed through newspapers or poster ads, and moreover, a part of the women preferred the process to be explained to them by someone they trust such as a friend or family member.

Nonetheless, it is quite evident that there is a need for financial inclusion in Pakistan. Only 13% of the population has a bank account, whereas merely 6% have a mobile payment account. From


these around 95% are male users, therefore it can easily be argued that many women could benefit from using mobile payment. However, there is a gendered digital divide present. As the women explained, men mostly use technology and they are usually the owners of mobile phones. Consequently, we can argue that technology such as mobile pay is not gender-friendly. Even educated and employed women do not understand the user menu or they do not have the confidence to even try it, since it is aimed at men and the women fear a stigmatization of using technology. As uncovered in the DESTEP analysis a lack of education and information often leads to technophobia, which mainly restricts women but also severely affects the less educated and poor population, as it leaves them unbanked and financially excluded.

5.3. Mitigating the Gaps – Identifying Solutions

5.3.1. Education and Digital Literacy

Pakistan has historically had low literacy levels. The current literacy rate of 58% is corroborated by our survey, where 60% of the population did not have any education beyond high school level. In the modern age of Information and technology, having an advanced educational system and strong research base are pre-requisites for societal progression. Ineffective educational policies and low literacy rates have often been the cause of plight in many developing countries. Likewise in Pakistan, digital literacy and financial services access are some of the most overlooked topics in development policies. The contribution of basic educational services in poverty alleviation, economic growth and general public awareness is well-documented through research (Govinda, 1997). In fact, “education ranks at or near the top in the social priorities of all countries” according to Hayes (1987). Given the importance of education in virtually every field of work, low literacy rates are arguably one of the primary reasons for Easy-Paisa‟s supposed failure. An increase in education levels will go a long way in mitigating the technical barriers that act as a crucial impediment towards cellular financial services proliferation.

5.3.2. Reducing Transactions Cost

One of the primary reasons for M-pesa‟ success was its low transaction costs. Before the advent of M-pesa, transaction costs for sending $100 through legal channels ranged between $12 and $20, while the cost of sending money through slower, conventional methods, such as bus or postal orders ranged between $3 and $6. M-pesa revolutionized the money transfer system, by introducing a secure, and more importantly, cheap method of money transfer. The cost of sending $100 through M-pesa was $2.50 (2.5%) for a non-registered user while it was even lower for a registered user (Kabucho et all, 2003). In contrast, the cost of sending 1000 rupees is as high as 60 rupees (or 6%). Though the regressive charges system means that the cost declines as the amount transferred increases, the relative transfer cost for $100 (or roughly 10,000 Pakistani rupees) is still higher through Easypaisa than M-Pesa. These facts were further substantiated through our survey, where 70% of the respondents found the transaction charges expensive. Despite guaranteeing safety and convenience, mobile financial services providers in Pakistan will find it hard to penetrate in the lower segments of the society, if the charges remain an issue for potential customers.

5.3.3. Technical deficiencies

As discussed earlier, lack of education breeds a number of problems, especially in the technological domains. The women interviewed in 2015 revealed that despite having access to cellular services, they could not operate them or use for money transfer. Many lacked the confidence, or the know-how to carry-out the seemingly simple procedures themselves. Likewise, technophobia also acted as a deterrent to smooth service expansion. Our survey results revealed that majority of the respondents did not know how to operate a computer or use the internet. Interestingly, our survey results also indicated that though 94% of the population


said that they could operate a cellphone, the women interviewed argued that they lacked the skills to use mobile financial services. Overly complicated financial products can thus lead to financial exclusion, ideally thus, it is important to create products that are easily understandable, especially for people with little prior education.

5.3.4. Creating Awareness

The interviews highlighted the need for better awareness through BTL activities. Many of the women belonged to lower tier of the society, having no access to electric appliances. Thus mass-scale advertisements were of little help, as they neither reached the target audience nor allayed the fear of technology use. Similarly, many respondents in the interviews argued that they would prefer the money transfer system to be explained to them personally instead of via electronic communication. Thus, in order to improve the use of mobile financial services, it is crucial that the message communicated to the customers emphasizes on ease of use and comfort.

5.3.5. Clearing Misconceptions

Due to the intrinsic societal barriers of the Pakistani rural family system, many women are barred from the independent use of cell phones even though they have access to cellular services. Technology has often been stigmatized as an instrument for women to break through these barriers. Similarly, many women argued that they do not see any use of these services and would rather prefer using these services through conventional transfer facilities such as bus or hand-to-hand transfer. A research by Agarwal (2009) revealed that due to the self-service feature and technical difficulties, functional risk was high in developing countries as because of low literacy, the risk of a failed transaction was high. Hence, clearing these misconceptions through targeted marketing by stressing on innocuous nature of mobile financial services will help alleviate the misconceptions that shroud the services.

5.4. Government Initiatives

As we discuss the solutions to financial problems people belonging to the lower segment are facing, its important to look into some of the welfare schemes that the government has taken over the years. The current federal and provincial governments in Pakistan have launched several schemes for the poverty alleviation, jobs creation, provision of better health facilities and improvment in education standards in the country. Some of the major developments initiatives are given below along with their outcomes.

4 http://youth.pmo.gov.pk/

4Prime Minister's Programme for Youth

Schemes Date of launch

Objective Specification Region Outcome

Prime Minister's Youth Business Loan Scheme

2013

Loan is offered to the unemployed youth, especially educated youth looking for establishing or extending business enterprises.

Up to Rs. 20 lacs

50% quota of women borrowers

6% markup

8 years tenor

Nationwide

Up till now loan of amount Rs. 7.517 billion is disbursed to 7,916 people


5 http://www.bisp.gov.pk/

Prime Minister's Interest Free Loans Scheme

2014

This Micro-finance facility aimed at helping the poorest of the poor people in less privileged areas of the country. For enhancing the entrepreneurial competencies and lives standards.

Rs.25, 000 to RS 50,000 are given to applicants.

50% quota of women borrowers

No markup

3 years tenor

Nationwide

3,430.812 million is disbursed among 161, 840 people till now.

Prime Minister's Youth Training Scheme

2016

Aim is to train educated youth of Pakistan through 1-year paid internship in private and public sector offices

50,000 interns are selected annually and Rs.12, 000 for 12 months are paid to them.

Private and government firms are offered the services of interns.

Nationwide

Placement letters to 44000 successful interns have been awarded.

Prime Minister's Youth Skills Development Programme

2013

Unemployed youth is trained so that they can find better employment opportunities.

25,000 people are selected annually and they are awarded Rs.2500/month and for FATA its 3500/month.

Nationwide

49721 people are trained under this program.

Prime Minister's Youth Laptop Programme

2014

Aimed at promoting higher education and research among students by bridging the digital divide.

100,000 laptops are allotted every year.

Nationwide

HEC has so far distributed 110919 laptops to different students.

Prime Minister's Fee Reimbursement Scheme

2014

To promote higher education among students from less developed areas through financing of their tuition fees paid directly to universities.

Average Rs.40, 000 per year allocated to each student. Almost 50,000 students are selected every year.

Nationwide

20,337 students have granted free reimbursement in fiscal year of 2014-15.

5Benazir Income Support Programme


5.4.1. Prime Minister's Programme for Youth

Prime Minister Nawaz Sharif launched several schemes under this program, details given in the table. Indeed the program has good impact over the youth population. According to the Economic Survey of Pakistan, government has provided options to youth to initiate their own enterprise by taking loan from the bank. Moreover for enhancing the research skills among students government is distributing laptops among students of higher education and no doubt huge number of students are being benefited by this facility. Several training and internships programs have also been introduced for improving the skills among youth.

5.4.2. Benazir Income Support Programme (BISP)

World Bank is one of the partners of BISP and bank has remained committed to support this program because despite of criticism the progress of this program is quite appreciable. According to the World Bank, BISP is playing vital role for the women empowerment and reducing the level of poverty in the society.

6 http://www.pmhealthprogram.gov.pk/

7 http://psdf.org.pk/

Cash Grant 2008

This project was initiated for poverty alleviation and women empowerment among the socially and economically marginalized sections of Pakistan

Rs.1,500 per month on quarterly basis

Nationwide

5.4 million, people are getting benefits from this scheme.

6Prime Minister’s National Health Program

Pakistan Sehat Card

2015

To ensure that the identified under-privileged citizens across the country get access to their entitled medical health care in a swift and dignified manner without any financial obligations.

250,000 PKR for priority health care services and 50,000 PKR for secondary health care services.

It can be used for treatment of any disease

Islamabad, Muzaffarabad, Quetta and Kotli.

It‟s still in launching phase

7Punjab Skills Development Fund

Skills for Punjab Growth Strategy

2010

Objective is to provide quality skills and vocational training opportunities to the poor and vulnerable populations in order to improve livelihood prospects for them.

Vocational trainings with stipends and course expenses.

36 Districts of Punjab

Almost 135,000 people are trained


5.4.3. Prime Minister’s National Health Program

Although this program is still in launching phase but the rapid expansion is the evidence of its success in the country. This program is the first health scheme launched by the Nawaz‟s government. Free of cost access to hospital/indoor care to 3.1 million families will be provided.

5.4.4. Punjab Skills Development Fund

Around 135,000 people are trained under PSDF trainings and still the number is growing because of the effectiveness of the trainings. Many people have got the employment opportunities after training and many have started their own small enterprises which are very successful.

6. Conclusion

The first conjecture of our reseach was whether it is necessary to contemplate the particular societal context when designing a mobile payment service? Using the mobile money market comparison and DESTEP analysis of Kenya and Pakistan, respectively, we identified the similarities and differences between the nations. Even though the nations are quite similar in many aspects, the socio-cultural factor, which incorporated a micro-level gender analysis, presented significant differences. It was evident that a major part of M-Pesa‟s success was that it targeted both urban and rural residents with the Send Money Home campaign, and it considered the rural population and especially women in its strategic choices. Subsequently M-Pesa achieved a successful penetration rate amongst urban, rural and the female population. It is therefore permissible to conclude that our first conjecture holds.

The second conjecture of our reseach was whether it important that the penetration rate of the mobile payment service reaches critical mass amongst all income levels and social strata in order to improve financial inclusion and gender equality in Pakistan? Furthermore, as we previously described, the five largest mobile operators in Pakistan each have developed a mobile payment service. Telenor‟s Easypaisa is the front runner with 13million users. Yet, only 6% of the adult population is registered with a mobile payment account. As many of the socioeconomic factors in Kenya and Pakistan were similar, one could argue that M-Pesa and Easypaisa should be able to reach similar levels of success with regards to financially including the unbanked population. However, as the gender analysis proved, the socio-cultural factors presented several aspects that would pose significant barriers for a potential mobile payment solution. Hereunder, we discovered that there is a gender digital divide due to technology not being gender-friendly and due to cultural norms. Therefore, we conclude that our second conjecture holds.

The third conjecture of our reseach was whether educational and IT literacy must be improved in order to ensure successful proliferation of mobile money services in Pakistan? It was observed during our research that lack of education and technical knowledge acted as a significant hindrance towards proliferation of Mobile money services. A focused education policy and awareness campaign, aimed especially at improving the technical skills of the urban population, could go a long way towards increasing the penetration rate of these services. It is therefore permissible to conclude that our third conjecture holds.

The fourth conjecture of our reseach was whether Economic & financial conditions restrict the proliferation of mobile money services? Economic data indicated that both countries belong to the same income group, with similar GDP per Capita and rural population ratios. However, our interview respondents revealed that due to a shortage of state-financed welfare services and expensive utilities and food items, it was difficult for them to generate savings. As a consequence, they were left with very little disposable income to use money transfer. It is therefore permissible to conclude that our fourth conjecture holds.


Moreover, we found that Easypaisa‟s strategy was based on an OTC approach which had several limitations, however, the OTC approach was the only one used by the women. The reason for using it was that they did not know how to use mobile payment on their own. In order to utilize M-Pesa‟s successful strategy in Pakistan, it is necessary to adapt the strategy for the particular societal context. M-Pesa‟s strategy in Kenya was successful, because it understood and addressed what the population needed and it designed and implemented the service accordingly. Therefore, in order to contemplate a mobile payment solution that will improve financial inclusion and gender equality in Pakistan, one must consider the specific socioeconomic context and provide a service that is able to reach critical mass in terms of penetration rate amongst all levels of income and social strata, including the poor and unbanked women as well as men. With the conjectures confirmed in this paper, we emphasize that mobile payment, and specifically M-Pesa‟s strategy, can be used to improve financial inclusion and gender equality in Pakistan if addressed properly.

6.1. Contribution to the Field and Further Research

There is lack of research on technological development amongst the rural population and women. Often these groups are not included due to lack of finances or cultural restrictions. Therefore, we wish to contribute to the field of ICT and provide researchers with a societal context when addressing the digital and financial divide present in Pakistan. We aim to shed light on the unbanked and disenfranchised population, including the rural population and women who are otherwise overlooked.


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Appendix

Panel A: Moneygram Fees in 2003 and 2009

Panel A: Western Union Fees in 2003 and 2009


Example of an Interview summary following the HAF for gender analysis template

Harvard Tool 1: The Activity Profile

Harvard Tool 2: The Access and Control Profile

Resources & Benefits including Land,

Equipment, Labour, household finances,

Education Mobile phone, Sim card etc.

She has access and control of her finances. She owns a mobile

phone. Her children have access to education and are expected to

focus on their studies.

Harvard Tool 3: Analysis of Influencing Factors

Productive Activities

Income Generating:

Agriculture

Selling products and services

Employment outside household

Employment:

Skilled work

Business

House helper

Managing household Finances

Sending remittances

Creating savings

She is employed outside the household

Her occupation is stitching and sewing

She is widowed; therefore she solely manages all household finances.

She uses hand-to-hand delivery

She saves cash at home when possible with her low income.

Reproductive Activities

Water & Fuel related, Food preparation,

Childcare, Health related, Cleaning and

repair, Market related.

She manages the household on her own.

Community norms and social Hierarchy She does not face restrictions in regards to employment and

education.

Demographic factors Transportation is difficult in her area

Infrastructure She faces major challenges with transportation

Economic factors Her major challenges are electricity bills and medical expenses

Education (Literacy) She has a primary education and a corresponding level of literacy

Attitude of community towards

technology

Both men and women can use mobile phones but they are mostly

used by men

Income prioritization Groceries and her children’s education – she would spend more on

education if she could.

Asset (e.g. mobile phone) ownership She owns a mobile phone

Basic needs (food, clothing, shelter etc.) Paying for food and healthcare / medicine are major challenges


Survey Results

Q1: Gender

Q2: Age Group

Q3: Do you have a CNIC (Identity Card)?

Use of mobile payment No – lack of skills is her main hindrance

Barriers for using Mobile Payment in the

community

Insufficient finances and lack of skills are the main barriers

Creating awareness She would prefer that a friend or family member could explain the

process of using mobile payment to her.


Q4: Profession

Q5: What is the nature of work that you do?

Q6: Literacy Level

Q7: Literacy Skills Level


Q8: Do you know how to operate a computer?

Q9: Do you have internet Access?

Q10: Do you know how to use the internet?


Q11: Do you know how to operate a cell phone?

Q12: Mobile Phone Access

Q13: Type of Mobile Phone in use?


Q14: I have the power to decide if I want to study or not

Q15: I have the power to decide if I want to work or not

Q16: Number of family members in the family

35

49

12

4

2 to 5

6 to 10

11 to 15

More than 15


Q17: Number of working family members in the family

Q18: Income (PKR)

Q19: Your Household Income (PKR)


Q20: Majority of Income is spent on

Q21: How do you pay your bills?

Q22: How do you send/receive money from other cities/towns?


Q23: What is the average amount of money transaction?

Q24: Do you find Mobile Money transactions expensive?

Q25: Do you have a mobile Banking/Bank Account?


Q26: Do you have a mobile Money Account?

Q27: Are you aware of mobile baking facilities?

Q28: Do you have an ATM Machine in your area?


Q29: Do you have a mobile-money agent in your area?

Q30: The Nearest bank to you is?