ECONOMIC CONSEQUENCES AND VARIABLES INFLUENCING THE UPTAKE OF MOBILE FINANCIAL SERVICE IN UNBANKING POPULATION LIKE PAKISTAN

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.


INTRODUCTION
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:

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).

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:

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.

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:

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 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.

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 wellknown 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.

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 https://www.cribfb.com/journal/index.php/asfbr Asian Finance & Banking Review Vol. 5, No. 1; 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"

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.  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.

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.

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. 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)  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. 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 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.