




































Asian Finance & Banking Review 

Vol. 5, No. 1; 2021 

ISSN 2576-1161    E-ISSN 2576-1188 

Published by CRIBFB, USA 

  

38 

ECONOMIC CONSEQUENCES AND VARIABLES 

INFLUENCING THE UPTAKE OF MOBILE FINANCIAL 

SERVICE IN UNBANKING POPULATION LIKE PAKISTAN 

 

Zara Younus 

MBA in Finance 

Karachi University Business School 

University of Karachi, Pakistan 

E-mail: zara44younus@gmail.com 

 

Dr. Sohaib Uz Zaman 

Assistant Professor  

Karachi University Business School 

University of Karachi, Pakistan 

E-mail: sohaibuzzaman@uok.edu.pk 

 

 

ABSTRACT 

The growth of digital mobile devices enables the world to integrate and enables the masses to 

access and use services with optimism, speed and efficiency. These developments are on the rise 

in Pakistan. Market opportunities for digital financial services in Pakistan are projected to 

exceed $ 36 billion by 2025, which will increase GDP by 7%, create four million new jobs and 

generate $ 263 billion in new deposits. This power can only be achieved through a robust and 

efficient DFS environment. Although Pakistan has a DFS environment, it is unfortunate that so 

far no research has been done to determine and analyze the economic impact of mobile banking 

services as well as factors affecting their use in developing countries like Pakistan, to this end, 

the methodology part will be divided into two parts: the first part will focus on the secondary 

data to analyze and determine the impact of mobile banking activity on GDP, employment, 

government taxes for support to reduce non-banking figures in Pakistan. The second part will 

focus on the primary data that will be used to investigate the influencing variables on the usage 

of mobile banking services. A self-administered questionnaire has been developed with 250 

respondents, which will be distributed to mobile money users to get their ideas on mobile 

banking services. Its results will be evaluated using the Pearson correlation and multiple 

regressions. Affective factors are assessed under five factors: risk, perceived trust, cost-

effectiveness, accessibility and reliability using biometric analysis method in mobile banking. 

The study revealed that mobile financial services had positive impact on the economic indicators 

whereas factors like perceived trust, convenience and perceived risk had a significant influence 

on the adoption of mobile banking services but perceived cost and reliability were said to have 

insignificant influence on its adoption. 

 

Keywords: Mobile Financial Services, Adoption, Economic Impact, Pakistan. 

 



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INTRODUCTION 

Individuals in need of capital may be unable to receive it due to a lack of access to financial 

services (Johnston & Murdoch, 2008). More inclusive financial institutions can help the poor 

smooth their cash flows and safeguard them from economic vulnerability due to disability, 

accidents, theft, and unemployment. It may enable people to save and borrow, acquire assets, and 

make investments to change their lives (World Bank, 2012)”.It can also help individuals improve 

their credit risk profiles, lowering the rates they have to pay for financial services, reducing 

personal stress, and providing access to lower-cost lending sources (Caskey, 2002)”. “As a 

result, increasing access to financial services is crucial for development since it can boost 

economic growth and minimise wealth gaps. However, more than half of the world's population 

is still unbanked, which means they lack access to official financial institutions for saving and 

borrowing (Chala et al., 2009)”. This was corroborated by a 2012 World Bank study, which 

discovered that just around half of the world's adult population (51%) held accounts with a 

formal financial institution. Lower rates are found in middle-income (43%) and low-income 

(23%) countries (World Bank, 2012). Because of the rising use of mobile phones in developing 

countries, there has been a lot of interest in using mobile phones to reach the unbanked, 

particularly through the implementation of mobile phone-based financial services. . For example, 

it was stated in 2009 that 1 billion people lacked access to banks but did have access to mobile 

phones, with this figure predicted to climb to 1.7 billion by 2012 (Picken, 2009; Islam & Salma, 

2016). In recent years, there has been a lot of investment in mobile phone-based financial 

services technologies, as well as debate about the potential support for the poor and financially 

excluded (Porteous, 2006; Porteous & Wishart, 2006; Vodafone, 2007; Bengens & Soderberg, 

2008). One of the expected benefits of using mobile financial services is the ability to send 

money over vast distances, particularly little amounts of money, at a lesser cost than other 

options available to the poor. Furthermore, it was thought that by providing financial services to 

the financially excluded via mobile phone networks, the poor would benefit from higher savings 

rates, higher income, and greater financial stress, among other things (Donner & Tellez, 2008). 

This initiative was intended to expand access to formal credit while lowering the cost of 

providing them. It was also intended to improve payment system efficiency and reduce 

dependency on cash as a transactional medium (Porteus, 2006). 

Pakistan's financial inclusiveness rate has recently reached 15%. This means that 

currently, 85 percent of adults in Pakistan lack access to formal financial services. Among the 

remaining 15%, 5% are fully banked, which means they have access to a full range of financial 

services (including savings, insurance, and credit), and 10% are economically inactive, which 

means they have just minimal access to financial services such as a savings account. 

Furthermore, even among the financially involved, critical services such as insurance and credit 

are underutilised, and MFS is almost non-existent. Financial inclusion, or the supply of low-cost 

financial services to a community, has been connected to a country's fulfilment of crucial 

economic and social goals. The provision of financial services attracts credit to the banking 

system, resulting in greater GDP. It encourages entrepreneurship by enhancing domestic capital 

formation. It also enhances the depth of a country's private sector, which leads to the creation of 

new jobs. These financial innovations diminish a country's total income disparity, increase 

income growth among the poorest quintile of the population, and accelerate poverty reduction. 

Overall, the focus of this study will be on the economic benefits of mobile financial 

services, as well as the numerous factors that influence their utilization. Previous research has 

found a correlation between mobile banking usage and trustworthiness (Bhattacherjee, 2002). 



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Lee (2009) found a strong relationship between mobile banking usage and Perceived Risks but 

no link between mobile banking usage and Security Risk. Along with these factors, (reliability) 

is expected to have a significant impact on how individuals use mobile financial services. A 

consumer must be confident that the system is reliable, that it protects their security, privacy, and 

data integrity, and that it provides a secure authentication method for mobile banking. As a 

result, this study will concentrate on the potential use of detection authentication to alleviate 

security issues while boosting the dependability and trustworthiness of mobile financial services 

for clients. 

  

LITERATURE REVIEW 

Mobile Financial Services and Economic Growth 

Absence of capital, obligation assortment, liquidity, income execution, and low deals are the 

critical part of pecuniary (financial) limitations for private companies in non-industrial nations 

(Bngens & Söderberg, 2011a). Chale and Mbamba (2015) concurred with Bngens and Söderberg 

(2011b) that mobile money improves small companies in Tanzania in an assortment of ways, 

including deals exchanges, stock buys, installment receipts, products and service installment, all 

of which bring about worked on economic execution. Andrianaivo and Kpodar (2012) found that 

in nations where mobile money has been sent, there is a positive connection between financial 

inclusion (as characterized by advance records per individual) and economic growth. In this 

manner it forms the following hypothesis: 

 

H1: Mobile financial services would have a significant and favorable impact on the country's 

economic growth 

 

Mobile Financial Services and Factors Influencing Its Adoption 

Technology acceptance model have been truly examined and endorsed, and they are the most 

consistently used models for depicting how clients recognize new advancement (Venkatesh & 

Davis, 2000; Omwansa et al., 2012; Masinge, 2010). These examinations utilized the original 

TAM components along with different variables like risk, trust, and cost of mobile monetary 

services. From literature review and for the purpose of this study, the study framework comprises 

of the elements that are affecting the reception (acceptance) of mobile banking services 

dependent on TAM approach as explanatory variable and reception of mobile monetary services 

as a predicted variable. 

 

Perceived Trust 

According to Dass and Pal (2011a), trust is a mental assumption that a believed part won't act 

sharply. Thus, when the client's confidence in the services provider rises, so it will build their 

eagerness to take part in versatile mobile financial transactions (Masinge, 2010). As indicated by 

Bengens and Söderberg (2008), a financial framework and its entertainers should be trusted, and 

they should chip away at rules that cultivate customer trust. Dass and Pal (2011b) found that in 

their investigation on rural unbanked adoption of mobile financial services, villagers preferred 

channels that could be trusted to conduct monetary transaction. As per considers, trustworthiness 

impacts the uptake of mobile banking services (Masinge, 2010; Amin, Baba, & Mohammed, 

2007; Horne & Nickerson, 2013; Chitungo & Munongo, 2013; Lule, 2008). 

 



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41 

H2: Perceived trustworthiness in mobile financial services will have a beneficial impact on 

mobile financial service adoption 

 

Convenience 

Convenience is connected to the yield that comes from utilizing innovation (Amin et al., 2007). 

As indicated by Davis (1989), convenience is how much an individual thinks that utilizing a 

specific strategy will work on their exhibition. Various examinations have shown that perceived 

usefulness essentially affects the acknowledgment of mobile banking services (Aboelmaged in 

Gebba, 2013; Chitungo & Munongo, 2013; Davis, 1989; Li, 2010; Sayid et al., 2012). Chitungo 

and Munongo (2013) in their review on the acknowledgment of mobile banking in Zimbabwe 

tracked down that ease of use decidedly affects the acknowledgment of mobile money services. 

Based on these studies the following hypothesis is proposed: 

 

H3: Convenience will have a beneficial impact on mobile banking service adoption 

 

Perceived Risk 

Perceived risk addresses vulnerability, a forthcoming misfortune, or a security break that could 

bring about a financial misfortune (Chitungo & Munongo, 2013; Lee, 2009). Monetary danger, 

security or protection hazard, social danger, time hazard, and execution hazard are for the most 

part instances of perceived risk (Lee, 2009). It is contended that the utilization of mobile 

financial services raises worries about monetary misfortunes, secret word security, network 

issues, hacking, and individual data misfortune. Therefore, it is said that perceived risk adversely 

affects mobile financial take-up. 

 

H4: Perceived risk will have a detrimental effect on mobile financial service adoption 

 

Perceived Cost 

How much an individual accepts that utilizing mobile financial will cost cash is portrayed as cost 

(Chitungo & Munongo, 2013). The expense might incorporate transactional costs, for example, 

service charges, mobile communication charges (like SMS or information), and cell phone costs 

(Chitungo & Munongo, 2013). Dass & Pal (2011a) found that monetary expense unfavorably 

affects the take-up of digital financial services. Moreover, cost contemplations might deter 

people from accepting mobile banking services in case they are restrictively costly, yet in case 

they are sensible, it tends to be an inspiration for quicker reception (Tobbin & Kuwornu, 2011). 

In light of the above literature review, the accompanying hypothesis is proposed as: 

 

H5: The perceived cost of mobile financial services will have a major negative impact on the 

adoption of mobile financial services 

 

Reliability 

Reliability can likewise be considered as a predictor variable in the reception and utilization of 

digital banking services that can be included in TAM system since client acknowledgment is the 

super basic part in the reception of innovation like mobile money services without which any 

innovation can be outdated so for this reason solid and secure technique can be consider like bio 

metric instrument for accomplishing the client trust and acknowledgment in online payments 

through cell phone. Buckley and Nurse (2019) appear to demonstrate that fingerprint scanning is 



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42 

a widely used authentication mechanism. Finally, a 2015 South Korean study found that 

consumers are more inclined to utilise methods that are less secure but easier to use, such as 

fingerprint scanning. Finally, arguably the most concerning finding from their survey was that 

83% of respondents believed biometric authentication methods are equally secure as passwords. 

 

H6: Reliability will have a significant impact on the use of mobile financial services 

 

Research Problem 

This study focuses on the economic impact of mobile financial services and the factors that 

influence their use in developing countries such as Pakistan, where the majority of the population 

does not use mobile internet or have access to formal financial services, putting them at risk of 

missing out the economic benefits of digital transformation. Gender, regional, economic, and 

literacy barriers all contribute to the exclusion gap. In Pakistan, for example, women are 37% 

less likely than men to own a cell phone. Addressing the issue of service access and consumption 

is critical to optimising the impact of mobile-enabled digital transformation in Pakistan. Thus it 

addresses the following questions to be answered: 

 

Question 1: Does mobile financial service has positive effect on country’s economic growth? 

Question 2: What factors will influence its usage? 

 

Research Gap 

It is obvious that a vision of a technologically advanced financial inclusive ecosystem cannot be 

realised without the deployment of technologically innovative financial systems and solutions 

that provide unrestricted access to financial services to all citizens in the country. The idea is to 

leverage mobile financial services to create markets so inclusive that even tiny businesses in 

Pakistan, such as women who prepare fruit relishes in rural areas, can sell their products online 

across Pakistan and collect revenue digitally in their mobile wallets. Though Pakistan has a 

nascent and transformational role in the MFS ecosystem, the economic ramifications and factors 

that impact its use have been understudied thus far. As a result, it is deemed necessary to fill the 

gap by researching the connectivity of mobile financial services with the implications of 

economic factors and factors such as (perceived risk, trust, convenience, perceived cost, and 

reliability) that affect its usage when widely adopted in lower-middle income countries such as 

Pakistan. 

 

Significance of the Study 
The importance of this study is that mobile banking is not intended to replace the banking system 

today; rather, they aim to expand it and create more employment opportunities for many. 

Communication companies have a clear advantage in providing customers who have difficulty 

accessing traditional mobile banking services. The carrier (mobile operator) has a pre-existing 

relationship with customers who have purchased the required mobile phone, and it is a well-

known brand and trusted with a large secure server. With its vast experience serving many 

customers and answering their needs, the user is also able to focus on long tail customers. 

Traditional financial institutions often focus on people with large finances, high profits, and long 

stays. 

 

 



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RESEARCH METHODOLOGY 

As mentioned before, Pakistan has gained a dynamic role in mobile money services, but the 

economic implications and factors influencing the usage of mobile money services have yet to be 

thoroughly investigated. To solve this diagnostic problem, this study will focus on primary and 

secondary data. The secondary data will describe a graphical representation of the impact of 

MFS (mobile financial services) on the economic benefits on which first alternative hypothesis is 

based upon as its reference is given in the literature review. To test the remaining five 

hypothesis, primary data (questionnaire) will be used to study TAM (technology acceptance 

process) such as risk assumptions, trust assumptions, perceived cost, reliability, accessibility 

which will affect the use of mobile money services. 

 

 Theoretical Structure 

 

 

Data Collection 

Data will be collected using an automated questionnaire that was provided to respondents who 

have access to mobile financial services for initial data collection. A closed-ended questionnaire 

was used, respondents were asked to give their views on the statement examining the structure at 

five point Likert scale, with 1 indicating strong disagree, 2 indicating disagree, 3 equal to neutral, 

4  equal to agree and 5 equal to strongly agree. Mobile money makers was the target market for 

the study with a sample size 250, depending on the rule of thumb that the rate of change in size 

should be  more than 200 (Brown, 2006). Respondents were selected by using a purposive 

sampling technique. This process was used to get responders with mobile phones and subscribers 

who use mobile money services. This study uses five independent concepts, namely: 

convenience (perceived ease of use, usefulness), risk factors, perceived trust, costs and reliability 



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to measure factors affecting the acceptance of mobile financial services. For the purpose of the 

secondary data collection, the data will be analyzed by “The economic and social impact of 

mobile services (analysis of Pakistan, India, Bangladesh, Serbia and Malaysia) by the relevant 

authorities Boston (BCG) April 2011” 

 

Research Techniques 

Regression Model 

The linear multiple regression line has been identified as follows:   

AMF = α1+ β1 PR+ β2T + β3C + β4 PC+β5 R 

AMF = Adoption of Mobile Financial service 

PR = Perceived Risk 

T = Trust 

C = Convenience 

PC = Perceived cost 

R = Reliability 

α1 = acceptance of mobile financial services without change of risk, trust, accessibility, cost and 

reliability. 

β1 = Partial changes in the acceptance of mobile banking services as a result of a change in the 

perception of risk while other factors persist.   

β2 = The partial change in the adoption of mobile financial services as a result of one unit 

change in the Trust variable when all other variables remain constant. 

β3 = The partial change in the uptake of mobile financial services as a result of one unit change 

in the Convenience variable while other things remain constant. 

β4== A partial acceleration in the uptake of mobile financial services as a result of a one-unit 

change in the Perceived cost variable while other factors remain constant. 

β5 = The partial change in mobile financial service uptake as a result of one unit change in the 

Reliability variable while other things remain constant 

 

Correlation 

The correlation method is used to determine the strength of the relationship between the two data 

sets. Algorithms provide ratings from -1 to 1, while 1 indicates the best association. Significant 

negative association was demonstrated by the value of -1. Zero results indicate no association. 

 

 DATA ANALYSIS OF PRIMARY DATA 

Reliability Testing (Pilot Testing) 

 
Case Processing Summary 

 N % 

Cases 

Valid 250 100.0 

Excludeda 0 .0 

Total 250 100.0 

a. List wise deletion based on all variables in the 

procedure. 



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Reliability Statistics 

Cronbach's Alpha N of Items 

.957 78 

 

The Cronbach alpha was used to evaluate the internal consistency of the variable (Cronbach, 

1951). For this reason, an experiment was conducted to determine the consistency of the 

variables. The results revealed that all the variables produced were reliable, with an alpha rate of 

more than 0.70, or 0.957, as suggested by Nunnally and Bernstein (1994). 

 

Results of Factors Affecting the Adoption of Mobile Financial Services 

Correlation 

 

The correlation between the variables was between r -0.018 and r 0.0684. The strongest 

correlation between predictor variables was found between trustworthiness and accessibility as 

convenience (r = 0.684) indicating strong correlation between variables. Results showed that 

trustworthiness had a positive correlation with convenience (r = 0.684 and p <0.01) and 

reliability (r = 0.627 and p <0.01). Perceived risk has a significant relationship with only cost as 

independent variable. The significant values of the correlation between predictor and predicted 

variables ranged from r = -0.142 to r = 0.701. The results shown in Table 2 show that 

trustworthiness and accessibility had a strong and significant relationship with the adoption of 

mobile financial services with  r 0.701 and 0.680 at a significant p <0.01  higher than the other  

independent variables. Reliability also showed a positive correlation with the acceptance of 

mobile money services at p <0.01. The perceived risk showed a significant negative association 

with adoption at the p <0.05 level. It was revealed that perceived cost has insignificant influence 

on the adoption of mobile financial services. 



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Regression Analysis (Hypothesis Testing) 

Model Summary 

Model R R Square Adjusted R 

Square 

Std. Error of the 

Estimate 

1 .762a .581 .573 .44917 

a. Predictors: (Constant), PERCEIVEDCOST, PERCEIVEDTRUST, 

PERCEIVEDRISK, RELIABILITY, CONVENIENCE 

 

R Square gives a record of the measure of changeability in the predicted variable represented by 

the predictor variable (Bordens & Abbott, 2011). So for this situation the above table shows that 

the worth of R is 0.762 which is illustrative of the relationship esteem between explanatory and 

response variable. The above model shows that value of R2 is 0.581 which shows variability of 

predictor variable on predicted variable. 0.573 Adjusted R square and St. Deviation Error of the 

Estimate = 0.44917 fluctuation of forecast. The correlation value is positive and depicts a good 

strength of relationship between the dependent and independent variables. The R Square value 

is 0.581 which is explaining that diversified results are 41.1% of variation in dependant variable 

which is adoption of mobile financial services. It means that 58.1% of variability shows how the 

current factors like perceived risk, perceived trust are affecting adoption of mobile financial 

services and whether it is dependent on other factors not given in this study but they have 

impact on its adoption. 

ANOVA 

Model Sum of Squares Df Mean Square F Sig. 

1 

Regression 68.036 5 13.607 67.445 .000b 

Residual 49.026 243 .202   

Total 117.062 248    

a. Dependent Variable: MOBILEFINANCIALSERVICEADOPTION 

b. Predictors: (Constant), PERCEIVEDCOST, PERCEIVEDTRUST, PERCEIVEDRISK,  

RELIABILITY, CONVENIENCE 

 

Table ANOVA test shows the level of significance and F-Status value. The results of this test 

show that factors like perceived risk, perceived cost, reliability etc. are significantly contributes 

towards the adoption of mobile financial services that is (F=67.445 & P=0.000) which also 

means that overall regression model is showing a good model fit. 

Coefficientsa 

Model Unstandardized Coefficients Standardized 

Coefficients 

T Sig. 

B Std. Error Beta 

1 (Constant) .815 .227  3.585 .000 

PERCEIVEDTRUST .380 .057 .401 6.639 .000 

CONVENIENCE .351 .064 .344 5.488 .000 

PERCEIVEDRISK -.124 .049 -.115 -2.541 .012 



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RELIABILITY .083 .059 .083 1.407 .161 

PERCEIVEDCOST .043 .040 .049 1.070 .286 

a. Dependent Variable: MOBILEFINANCIALSERVICEADOPTION 

 

Perceived Trust 

The idea of trustworthiness hypothesis proposes that this independent variable can altogether 

affect the uptake of mobile money, the result of this analysis also reveal the same thing (â = 

0.380, p = 0.000).  The results are correspondent with the previous researches that show 

trustworthiness has beneficial impaction on the reception of mobile money services (Dass & Pal, 

2011b; Chitungo & Munongo, 2013; Marumbwa & Mutsikiwa, 2013).  

 

Convenience 

The regression analysis found that perceived usefulness and perceived ease of use have a 

significant influence on mobile financial service uptake at p 0.01 significance level with â= 

0.351. These findings support the hypothesis that convenience has a major beneficial impact on 

mobile financial service adoption. The null hypothesis that convenience has no effect can be 

rejected because the p-value is less than 0.01. Discoveries are harmonious with Davis' (1989) 

idea of Technology Acceptance Model (TAM), which depends with the understanding that 

convenience is the prime factor in influencing new innovation acknowledgment. Different 

researhers, including Chitungo and Munongo (2013) in Zimbabwe, Lule (2008) in Kenya, 

Marumbwa and Mutsikiwa (2013) in Zimbabwe, and Dahlberg, Mallat, and örni (2004) also 

found that convenience was significant in evaluating clients' reception behavior in new 

technology and testing it with different factors in contrast with Davis' first reception innovation 

model (1989).  

 

Reliability 

With â=0.083, p>0.01, the discoveries of this review demonstrated that reliability essentially 

affected the take-up of mobile money services. It follows that the utilization of a biometric finger 

impression scanner can't be a solid and safe strategy of making installments or moving cash 

through digital financial services. The discoveries negate past research, which found that 

Buckley and Nurse (2019) seem to suggest that unique mark checking (bio metric) is a broadly 

utilized verification strategy in mobile banking. 

 

Perceived Risk 

The risk as predicted variable contrarily affected the reception of digital financial services (â = 

00.124, p = 0.012 <0.05), as per the hypothesis. Different researches on risk factor show that it 

has detrimental effect on the uptake of mobile money services (Marumbwa & Mutsikiwa, 2013; 

Dass & Pal, 2011a; Dahlberg, Mallat, & örni, 2004) support the legitimacy of this review. 

 

Perceived Cost 

The past discoveries demonstrated that cost had insignificant effect on the reception of digital 

financial services at the P >0.01 significance level with â = 0.043. Other examination (Tobbin & 

Kuwornu, 2011; Marumbwa & Mutsikiwa, 2013; Dahlberg, Mallat, & örni, 2004; Dass & Pal, 

2011b) uncovered that cost actually affect this predicted variable. 

  



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DATA ANALYSIS OF SECONDARY DATA 

Economic Impact of Mobile Financial Services 

The Boston Advisory Group (BCG) examines the impact of mobile money in emerging 

economies, particularly how having access to bank accounts and credits will change the way 

people live, work and develop over the years. To guide this study, the forecast from BCG was 

used to analyze what the picture would look like by 2020. Based on BCG forecast, mobile 

banking activity could reduce financial exclusion by 5-20% by 2020. 

 

Impact on GDP 

 

Figure 1. Impact on GDP (Saskatoon, 2018) 

There is good evidence that increased investment contributes to GDP. As entrepreneurs with a 

good business idea get loans, the economy grows and creates jobs. A productive society means 

many new businesses and new jobs. With mobile money services, by adopting services, 

Pakistan's GDP could grow by $ 20 billion, or 3% by 2020. In addition, there is a kind of 

accounting benefit of saving money in the banking system, as this would promote the creation of 

other credits and investments. 

 

New job creation 

 

Figure 2. New Job Creation (Saskatoon, 2018) 



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By 2020, if MFS adoption increases by 20%, 600,000 new businesses could be created, creating 

1 million new jobs, an increase of 1.3%. That is equivalent to new jobs for 1 out of every 10 

Pakistanis currently unemployed. 

Tax Revenue Growth 

  
Figure 3. Tax Revenue Growth (Boston, 2011) 

The benefits of economic growth stimulated by MFS would increase in tax revenue. 

Corporate taxes could rise due to the creation of new businesses along the MFS value chain, 

increasing profits in existing businesses through savings from MFS, and expanding the business 

made possible by MFS. This growth in business creation could create new jobs, which means 

higher taxes and income for employees. MFS could add $ 2 billion annually to Pakistan’s 

government budget by 2020, an increase of 3%. 

 

Discussion of the Results 

On the basis of hypothesis the variables were tested, results of variables like perceived trust, 

convenience and perceived risk found consistent with earlier studies and other variables like 

reliability and perceived cost found to have no significant impact on the adoption of mobile 

financial services as their p value is greater than 0.05.Similarly data related to economic impact 

of mobile financial services is also consistent with earlier studies indicating the acceptance of 

alternative hypothesis. 

 

 SCOPE FOR FUTURE RESEARCH 

Social factors such as race, age, gender and culture in the acceptance of mobile banking services 

have not been studied. According to Lee (2009), the cognitive propensity of individuals to risk 

varies between cultures, and various demographic characteristics have interrelationships that 

may influence mobile financial services uptake. This implies that cultural differences may 

influence client adoption of mobile banking. Again, because the majority of participants were 

from Karachi, this poll was restricted to adults aged 18 to 30. Including people of diverse ages 

from both the city and the villages may result in more accurate results. Nonetheless, the risk and 



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trust issues demand a more in-depth examination in order to popularise mobile banking 

throughout the country. Because secondary data on the economic impact of mobile financial 

services was predictive, self-collected/primary data should be employed in future studies to make 

the results more precise. 

 

CONCLUSION 

This study was successful in identifying the factors influencing the use of mobile banking in 

Pakistan. According to the conclusions of this study, perceived risks, trust, and convenience are 

the factors impacting mobile users' behavioral intention to use mobile financial services in 

Pakistan. As a result of this research, banks, service providers, and software developers now 

have more knowledge and information to improve consumers' willingness to use mobile 

financial services in the future. To summarise, MFS has a lot of potential, but it also has 

significant limitations. . More than 2.5 billion people in developing countries are impoverished, 

but many have mobile phones and have formed partnerships with telecommunications 

corporations. MFS has the potential to be the most powerful economic growth weapon for all of 

the countries especially for Pakistan. A variety of factors must be developed in order for this 

potential to be realised. Finally, as the MFS ecosystem evolves, regulators must provide a 

welcoming climate that minimises risk while allowing for flexibility and innovation. 

 

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