




































INDIAN JOURNAL OF FINANCE AND BANKING 11(1) (2022), 1-14 

1 

 

                       FINANCE AND BANKING 

                                                                  IJFB VOL 11 NO 1 (2022) P-ISSN 2574-6081  E-ISSN 2574-609X 
                                                  

        Available online at https://www.cribfb.com 

                                                                                                                                           Journal homepage: https://www.cribfb.com/journal/index.php/ijfb 
                                                                                                                                                                                                   Published by CRIBFB, USA 

IMPACT OF COVID-19 PANDEMIC ON FINTECH AND FINANCIAL 

INCLUSION IN INDIA          

 
 Megha Gupta (a)    Suhasini Verma (b)1    

 

(a) Research Scholar, Department of Business Administration, Manipal University Jaipur, India; E-mail: meghagupta.jai@gmail.com  
(b) Associate Professor, Department of Business Administration, Manipal University Jaipur, India; E-mail: verma.suhasini@gmail.com 

 

 
A R T I C L E I N F O 

 
 

Article History: 
 

Received: 10th September 2022 

Accepted: 20th October 2022 

Online Publication: 2nd November 2022 

 
Keywords: 

 

Covid-19, FinTech,  

Digital Payment, Financial Inclusion, 

Financial Literacy 

 

 
JEL Classification Codes: 

 

      F65, O32, Q55, H80, M10 
 

  

 
A B S T R A C T 

 
The study seeks to investigate how the pandemic of Covid-19 has impacted customer engagement in 

using Fintech services and resultantly the status of financial inclusion in India. This study is empirical 

and analytical in nature. Digital payment is taken as a proxy of FinTech. The data is collected from 

primary and secondary sources. To understand what persuades a customer to use FinTech services, the 

response to a survey questionnaire has been obtained from 310 respondents through e-mail and hand 

collection. Factor analysis is used to investigate the factors that impacted customer engagement in 
digital payment, before and after the Covid-19 pandemic. The factors used in this model are access, 

usage, technology, and financial literacy. Results show that there is a significant positive relationship 

between all the factors and the use of FinTech services. There is a significant positive relationship 

between FinTech and financial inclusion, as already established by the previous studies. The findings of 

this review are pivotal as they can serve as useful input for the ongoing debate directed towards 

increased use of FinTech in achieving greater financial inclusion. The findings suggest that by advancing 

the technology and increasing financial literacy, access, and use of FinTech services can be increased 

which in turn will increase financial inclusion in developing countries. 
 

 

© 2022 by the authors. Licensee CRIBFB, USA. This article is an open access article distributed 
under the terms and conditions of the Creative Commons Attribution (CC BY) license 
(http://creativecommons.org/licenses/by/4.0/).                           

 

INTRODUCTION 

The pandemic of Covid-19 has impacted every walk of life in a great way. The finance sector has also been greatly impacted 

by this pandemic, because of lockdown they could transact in cash. This situation called for an environment, where the 

entire population have a bank account, so that they may transact electronically. Unfortunately, this is not the case with 

India. India is a developing country, and its population is 1380 million. Around 20% people of in India do not have bank 

accounts (Statista, 2020) and millions more do not use their bank accounts regularly (Ernst & Young, 2019). Financial 

inclusion in India till now is 80% and the second largest-unbanked population in the world. According to the World Bank's 

Global FinDex database report, "when we dug deep, we discovered that approximately 48 percent of the country's bank 

accounts have seen no transaction records." The data indicates the grave issue in achieving financial inclusion, which is one 

of the frameworks through which Inclusive growth can be accomplished in developing countries like India (Morgan & 

Pontines, 2014). “Financial inclusion is intended to pull the “unbanked” people into the official financial system, with a view 

to providing financial services covering from payments, savings, and transfers to credit and insurance.” Financial inclusion 

encompasses access to financial products and services such as bank insurance, bank accounts payment services & 

remittance, financial consultancy, etc. (Durai & Stella, 2019).  

Sustainable Development Goals (2030) financial inclusion is positioned noticeably as an enabler of other 

developmental goals, with a target in eight of the seventeen goals. SDG 1 is about eliminating poverty; SDG 2 is about 

achieving food security, ending hunger, and promoting sustainable agriculture; SDG 3 is about profiting from health and 

well-being; SDG 5 is about achieving gender equality and economic empowerment of women; SDG 8 is about promoting 

jobs and economic growth; SDG 9 is about supporting innovation, industry, and infrastructure; and SDG 10 is about 

reducing inequality (Truby, 2020). Furthermore, there is an implied role for greater financial inclusion in SDG 17 on 

improving the means of implementation through increased savings mobilization for investment and consumption, which 

                                                      
1Corresponding author: ORCID ID: 0000-0001-5795-5412 

© 2022 by the authors. Hosting by CRIBFB. Peer review under responsibility of CRIBFB, USA.  

https://doi.org/10.46281/ijfb.v11i1.1815 
 

To cite this article: Gupta, M., & Verma, S. (2022). IMPACT OF COVID-19 PANDEMIC ON FINTECH AND FINANCIAL INCLUSION IN INDIA. 

Indian Journal of Finance and Banking, 11(1), 1-15. https://doi.org/10.46281/ijfb.v11i1.1815 

https://orcid.org/0000-0001-5795-5412
mailto:verma.suhasini@gmail.com*
http://creativecommons.org/licenses/by/4.0/)
http://creativecommons.org/licenses/by/4.0/)
https://doi.org/10.46281/ijfb.v11i1.1815
https://orcid.org/0000-0002-7763-1375


Gupta & Verma, Indian Journal of Finance and Banking 11(1) (2022), 1-14 

 

2 

can stimulate growth. Financial inclusion is a process of providing access to the financial services and products for the most 

vulnerable groups such as people from low-income and weaker sections of society at a very low affordable cost in a proper 

and transparent way by the recognized institutional participants (RBI Report, 2022). In order to increase the rate of Financial 

Inclusion in India, the government introduced a very promising scheme, named Pradhan Mantri Jan Dhan Yojana (PMJDY) 

in 2015. The primary reason for this scheme is that each resident of India should have easy access to open saving accounts 

and the advantages of this scheme such as RuPay debit and credit cards, zero balance accounts, and a simple loan option. 

This scheme gives them trust in a superior tomorrow (Joshi & Rajpurohit, 2016). After all these steps taken by the 

Government of India, there is uneven access to financial services with 20% of the population being unbanked and in 80% 

of financial inclusion, half of them or half of the bank accounts are inoperative means they are not using their accounts or 

no transactions since long (World Bank Report, 2020; Statista, 2020). 

To address this problem, Financial Technology (FinTech) is one of the most widely researched areas at the present 

time. FinTech is the use of modern innovation in the field of finance. It is fundamentally the utilization of creative and 

disruptive innovation for offering financial services (Rabbani et al., 2020). The term “FinTech” refers to corporations or 

company representatives combining financial services with new innovative technologies (Dorfleitner et al., 2017). Vasiljeva 

and Lukanova (2016) “They look like banks, they talk like banks, but are not regulated like banks.” Furthermore, the 

expression FinTech is fresh to the new development and integration. In the banking business, there are several innovations 

and developments that are transforming customers’ behavior and their knowledge of financial services. Firms are offering 

novel digital solutions as alternatives to traditional banking services (Senyo & Karanasios, 2020). The more extensive 

objective of financial technology is to meet the unmet demand of those, whose financial needs are not being fulfilled by 

traditional financial players. So, in a way, FinTech expects to add to the more extensive objective of financial inclusion 

(Popescu, 2019). Mehrotra (2019) FinTech is helping women, the poor, farmers, and youngsters to avail of financial services 

riding on the technology of smartphones, network coverage, mobile-based banking, and financial solutions and thus bringing 

them under the ambit of financial inclusion. Nair et al. (2021) the FinTech Revolution creates new avenues for financial 

inclusion. This applies specifically to the       utilization of digital money, mobile accounts, e-wallets, and the formation of 

biometric smart cards (Naumenkova et al., 2019).  

The COVID-19 epidemic has forced adjustments in many segments of the economy and business plans, along with 

customer behavior in a wide range of fields, including day-to-day payment patterns. Many digital solutions have enabled 

cashless payments. The links between payments, pandemics, and technology are becoming clearer, particularly since the 

COVID-19 epidemic has been identified as a driver of the digital transition (Huterska et al., 2021). The Pandemic has given 

rise to the need for contactless payment and this fact has significantly increased the use of digital payment. As a result, the 

use of alternative payment methods is increasing. The mobile wallet has been one of the tools in use. Mobile payment 

methods have provided convenient and simple services to a multi-functional network. Mobile payment refers to a specific 

payment method performed on mobile devices. There are several types of mobile payment services available. In addition, 

due to the Covid-19 outbreak and the virus's rapid global spread, various procedures such as alternative payment options 

instead of cash have been modified. Several experts advise decreasing the use of cash so that consumers can apply alternate 

techniques (Alwi et al., 2021). Prior research has been heavily focused on opportunities and challenges, trends, and growth 

in the payment system (FinTech) same country or across countries (Suryono et al., 2020; Nurfadilah & Samidi, 2021; 

Tonuchi, 2020; Tripalupi & Anggahegari, 2020). The impact of FinTech on financial inclusion in the setup of a covid-19 

pandemic is a less explored area and very limited research available on this. To fill this void, this research attempts to 

specifically understand the impact of digital payment on financial inclusion in India under a covid-19 situation.  

The study is empirical and analytical in nature and depends on both primary and secondary data. 310 respondents 

completed a self-administered questionnaire in primary data, and secondary data were obtained from the RBI Report (2022), 

Global FinTech reports, FinTech company’s reports, articles, blogs, and other scholastic journals during the year 2018-2021. 

The study employed factor analysis to assess the impact of the Covid-19 epidemic on India's payment system, FinTech, and 

financial inclusion. This result indicates there is a significant and positive relationship between digital payments and 

financial inclusion. Covid-19 has caused a tremendous amount of volatility and has changed the segment for good. Access, 

Usage, Technology, and financial literacy are the factors significantly contributing to increasing the use of FinTech and 

ultimately the rate of financial inclusion. Our study suggests that financial literacy is a very crucial factor in accelerating the 

growth of financial inclusion. Policymakers must emphasize to increase the rate of financial literacy to achieve the objectives 

of financial inclusion and inclusive growth.  

The rest of the work is organized as follows: First part gives an overview of the subject matter. Then we conducted 

a literature review on covid-19 surrounding FinTech, digital payment, and Financial Inclusion. The third section consists 

of research methodology, formulation of objectives, and hypothesis development. The fourth part includes testing of 

hypothesis, analysis of data, and discussions. Lastly, the fifth part highlights the research outcomes, conclusion, limitations, 

and further research. 

 

Objectives of the Study 

 To study the adoption of payment systems before, during, and after the lockdown. 

 To identify the reasons for the shift towards digital payments. 

 To evaluate the impact of Covid 19 pandemic on FinTech and Financial Inclusion in India. 

 To analyze the growth of FinTech and Financial inclusion in India during Covid 19. 

 



Gupta & Verma, Indian Journal of Finance and Banking 11(1) (2022), 1-14 

 

3 

LITERATURE REVIEW 

The pandemic Covid-19 has had a substantial effect on speeding up the trend toward a cashless society everywhere. In the 

context of this pandemic condition, the tendency toward financial technology transactions has intensified. In their financial 

transactions and activities, consumers are aiming to reduce the use of cash. They are exploring alternate contactless payment 

techniques, without any physical intervention, to execute this electronically (Abu Daqar et al., 2021). Although conventional 

banking procedures have been questioned, COVID-19 has been used in digitization and novel ways such as mobile e-wallets 

as an important step in individual banking and in cash. World Health Organization (WHO) warns individuals not to utilize 

cash as much as possible since coronavirus remains alive. The disease will therefore continue to spread. This has encouraged 

bankers to take imaginative and new payment options such as e-wallets into consideration (Alwi et al., 2021). Tut (2020) 

worked on pandemic evidence on electronic payment systems and find that consumers are moving away from the more 

expensive modes of payment and toward less expensive modes of payment. The first step toward financial inclusion is 

to have an account. A genuine inclusion necessitates the ability to use these accounts conveniently and safely (payments, 

digital payments via a mobile phone, or the internet) (Kasradze, 2020). The Global FinDex dataset includes information on 

who holds the account, as well as whether people make payments from these accounts. 1/5 of accountholders indicated 

that in the last 12 months they have been unable to put or withdraw money from their accounts and these accounts are 

therefore regarded inactive and, of course, cannot be seen as supporting financing inclusion (Ozili & Arun, 2020). Despite 

the mammoth efforts of the government, the problem of financial exclusion is still haunting. 

To solve this issue, FinTech is widely used nowadays by different countries. The term Financial Technology 

(FinTech) is the use of modern innovation in the field of finance. It is fundamentally the utilization of creative and disruptive 

innovation for offering financial services (Rabbani et al., 2020). The word “FinTech” refers to companies or representatives 

of companies that integrate financial services with advanced and modern technologies (Dorfleitner et al., 2017). FinTech 

functions in the finance industry are obvious and are aimed at offering cheaper prices, and greater and better access to all 

financial services (24/7) (Tam & Hanh, 2018). Senyo and Karanasios (2020) find that FinTech leverages existing 

infrastructure, acts as an aggregator and innovator, and uses a combination of strategies of competition and cooperation to 

solve the problem of financial inclusion. FinTech is the primary engine for financial inclusion in developed and emerging 

countries with the growth of Industrial Revolution 4.0 (Duvendack & Mader, 2019). Conducted a meta-analysis to 

understand the impact of FinTech on financial inclusion and found that the result was positive but not transformative. 
 

Table 1. Selected Research on Payment, FinTech, Covid-19, and Financial Inclusion in India and Worldwide 
 

Years Author of the 

study/ Report 

The subject of the study Main findings of the study 

2022 Chowdhury et al., 

2022 

The goal of this study is to 

determine E-Banking customers' 

faith in the influence of customer 

satisfaction on the E-Banking 

infrastructural facility and E-

Banking Communication 

environment. 

 It is found that the private bank's E-Banking 

Customer Trust value is much greater than that of 

the public banks. Customers, both male and 
female, have equal faith in the constantly 

expanding E-Banking transaction procedure. 

 In the event of a Covid-19 pandemic, the E-
Banking transaction procedure should swiftly 

expand in the future to ensure good health. 

2021 Latta &  Sarkar, 2021 This paper examined the role of 

the digital economy prior to and 

during COVID19, and also 

discuss the scope of digital use in 

the economy in various sectors 

and domains. 

 The pandemic caused terror in people's thoughts as 
financial bills may be considered to convey the fatal 

infection. This made more complicated 

transactions for the common person. 

 Mobile banking has been very useful in promoting 

social distancing policies and offering clients 24/ 7 

financial services during times like COVID-19. 

 

2021 Huterska et al., 2021 The aim was to discover the 

elements that cause customers to 
select cashless payments in retail 

and service locations during the 

COVID-19 epidemic using card 
payments. 

 The extraordinary circumstances of the COVID-19 

outbreak influenced consumer behavior. It has 
been a driving force behind greater consumer 

acceptance of non-cash payments by emphasizing 

the significance of factors that were previously 
overlooked in customer choice and 

payment preferences research. 

2021 Vasenska  et al., 2021 The study is to use the financial 
technology of individual consumers 

in Bulgaria before and after the 

crisis. A questionnaire survey by 
242 individual respondents is 

included in the approach. 

 The results acquired from the current research 
show that most people do not yet know whether 

using         FinTech instruments for financial 
transactions in banks or non-banks will influence 

the financial stability of economic objects during 

this crisis. 



Gupta & Verma, Indian Journal of Finance and Banking 11(1) (2022), 1-14 

 

4 

2021 Puthusserry et al., 
2021 

This study looks into a very 
essential but underutilized channel 

and focuses on its function in 

overcoming the multilayer mental 
distance 

experienced

 
by 

Internationalizing SMEs 

originating in an emerging 
economy. 

 They consider board members' roles in solving key 
internationalization difficulties, especially PD 

mitigation. Even when compared to global trends, 

the Indian Fintech sector, which is characterized by 
creative start-ups, is seeing dramatic and quick 

expansion. 

2021 Purba et al., 2021 To make an attempt by developing 

an approach for evaluating the 
digital innovation viewpoint in the 

use of Financial Technology by 

buyers, particularly in the period of 

the Covid-19 epidemic in Indonesia 

in 2020. 

 With the presence of digital application 

technology, consumers can be placed using a 
financial technology installment stage just as a 

food conveyance include. 

 This innovation can be introduced in the two IOS 

and Android cell phones to give safe, pleasant, 

beneficial, and efficient online ordering. 

2021 Sharma et al., 2021 The research investigates the 

possible benefits and problems 
associated with contextual 

variations between and within 

nations. During the Covid-19 
scenario, self-help groups were 

critical in empowering their 

members by offering options for 
livelihood support and money 

generation. 

 It is implausible to commemorate the arduous and 

heroic efforts made by all volunteers to achieve 
vital needs during the COVID-19 epidemic. 

Volunteer organizations/individual volunteer 

support agencies work tirelessly to provide food 
and other necessities to such persons. 

 The SHG movement in India has grown from 
micro savings and credit organizations that sought 

to empower poor rural ladies into one of the 

world's largest forums for the underprivileged. 

2020  Mogaji, 2020 To address financial vulnerability as 
a specific challenge for nations, 

institutions, and, individual citizens 
in the aftermath of Covid-19. 

 Changes in personal circumstances, like being 
made unemployed, can make people financially 

vulnerable, leading them to change their financial 
behavior and interact in gambling activities to get 

more money or use payday loans, which are not 

sustainable. 

2020 Al Nawayseh, 2020 The purpose of this research is to 

look into the influence of FinTech 

apps in building resilience during the 
COVID-19 disease outbreak. The 

study 

examines empirically the elements 
that influence Jordanians' desire to 

adopt FinTech applications. 

 

 This suggests that a user's willingness for using 

FinTech apps is influenced by his or her

 perception of societal impact, 
benefits, and beliefs. Customers' risk perceptions 

did not affect their intention to utilize FinTech 

apps during the COVID-19 pandemic, but they did 
affect their belief in the service. 

2020 Sheng et al., 2021 This paper gives an outline of 

methodological advances in the 

study of big data analytics and how 

they might be better applied to 

contemporary hierarchical concerns. 

 Concerning these promising regions, they 

discussed various freedoms that will arise for the 

administration to research local areas to utilize 

different logical ways to deal with help global and 

local endeavors to manage the extraordinary 

difficulties achieved by the COVID-19 epidemic 
and its fallout, which will have long haul 

suggestions for the worldwide economy. 

2019 Wonglimpiyarat, 
2019 

This paper examines the spread of 
financial technology, or FinTech, in 

the banking industry. 

 They draw insightful conclusions from the fact 
that the systemic characteristics of the innovation 

process change over time. Along the stages of 

innovation, innovators may employ various 
strategies for exploiting the innovation, and this 

process determines the systemic nature of the 

innovation. 

Source: Researcher’s Compilation 

 

Hypothesis of the Study 

H1: Access, (AC1, AC2, AC3, AC4) Usage, (US1, US2, US3, US4, US5, US6) Technology (TH1, TH2, TH3, TH4) and 

Literacy (LT1, LT2, LT3, LT4) are positively related to the use of FinTech and Financial Inclusion. 

 

MATERIALS AND METHODS 

This study is empirical and analytical in nature. Digital payment is taken as a proxy of FinTech. The data is collected 

from primary and secondary sources. For gathering the primary data convenience sampling was conducted using a self-

administered questionnaire, completed by 310 respondents and this study employed both an offline (face-to-face) and 

an electronic (online) strategy to collect applicable data with the plan of viewing the image from two viewpoints- 

Firstly, the researcher used Google Forms to distribute questionnaires to Indians through several social media 

channels (Facebook, WhatsApp, Email, and Telegram, among others). Second, the researcher targeted responses 



Gupta & Verma, Indian Journal of Finance and Banking 11(1) (2022), 1-14 

 

5 

from market wage earners, taxi drivers, street vendors, unemployed individuals, and among others. Secondary data has 

been collected from RBI Report (2022), Global FinTech reports, FinTech company’s reports, articles, blogs, and other 

scholastic journals. The factor analysis is conducted to examine the relationship between the factors and financial 

inclusion. The factors used in the model are access, usage, technology, and literacy. The duration of the study is 2018-

2021. The Cronbach’s alpha is 0.699/0.7, proving its reliability and validity. This test was pursued with relevant data 

analysis and evaluation. To conduct this statistical test, IBM Statistical Package of Social Sciences (SPSS) statistics 

28.0.1.0 (142) is used. 
 

RESULTS 

Analysis of data is separated into two sections which are a) Analysis of Demographic and b) Factor Analysis. 

Descriptive Statistics is used to analyze data. The data collected is significant because the study has collected 310 

responses. For one variable, the minimal sample size proposed was five; additionally, a sample size of one hundred is 

satisfactory, but a sample size of more than two hundred is considerably more acceptable to complete the factor analysis 

(Hassan et al., 2012). Factor analysis is conducted to comprehend the relationship between Access, (AC1, AC2, AC3, 

AC4) Usage, (US1, US2, US3, US4, US5, US6) Technology (TH1, TH2, TH3, TH4), and Literacy (LT1, LT2, 

LT3, LT4) and financial technologies and financial inclusion. 

 

Descriptive Analysis 

The number of respondents who participated in this study was 310, out of which respondents 41.6% were between the 

ages of 25-35 years, 39.4% were between the ages of 15-25 years, were 13.5% between the ages of 35-45 years, 3.9% 

between the ages of 45-55 years, 1.6% between the ages of 55-65 years and 0% above the age of 65 years. According 

to their gender, 58.1% are males, 41.9% are females and 0% are others. In terms of, educational qualifications 25.5% 

are Undergraduates, 27.4% are post-graduates & most of the respondents 47.1% are Graduates. According to the 

employment status of the 310 respondents, 26.8% are students, 31.0% are self-employed, the highest 41.3% are 

employees, and 1.0% are retired. The greatest part of the responder’s income level is less than 20000Rs P/m (51.6%), 

pursued by 25.8 percent who have an income of 20000-40000 Rs. P/m, 10.00 percent who have an income of 40000-

60000 Rs. P/m, 5.2 percent who have an income of 60000-80000 Rs. P/m, and 7.4 percent who have an income of more 

than 80000 Rs. P/m. As for the place of residence 47.4% lives in the village followed by 21.3% of people who lives in 

the city with a population over 500000 followed by 16.8% of people who live in the city with a population up to 500000 

and followed by 14.5% people lives in the city with population up to 100000. 

 

Table 2. Demographic Profile of 310 Respondents 
 

Demographic Frequency Percentage 

Age 
15-25 years 

25-35 years 

35-45 years 
45-55 years 

55-65 years 

Above 65 years 

 
122 

129 

42 
12 

5 

0 

 
39.4% 

41.6% 

13.5% 
3.9% 

1.6% 

0 

Gender 

Male 
Female 

Others 

 

180 
130 

0 

 

58.1% 
41.9% 

0 

Education  
Under-Graduate 

Graduate 

Post-Graduate & Above 

 
79 

146 

85 

 
25.5% 

47.1% 

27.4% 

Employment Status 

Student 
Self-Employed 

Employee Retired 

 

83 
96 

128 

3 

 

26.8% 
31.0% 

41.3% 

1.0% 

Income 

Less than 20000Rs P/m  

20000-40000 Rs P/m 
40000-60000 Rs P/m 

60000-80000 Rs P/m 

80000 & Above Rs P/m 

 

160 

80 
31 

16 

23 

 

51.6% 

25.8% 
10.0% 

5.2% 

7.4% 

Place of Residence 

Village 
The city with a population of up to 100000  

The city with a population of up to 500000  

The city with a population of over 500000 

 

147 
45 

52 

66 

 

47.4% 
14.5% 

16.8% 

21.3% 

Source: Primary Data, the author created the questionnaire. 

Note: This review's demographic analysis of all responders is presented in this table. Appendix A contains a list of all the questions. 



Gupta & Verma, Indian Journal of Finance and Banking 11(1) (2022), 1-14 

 

6 

Factor Analysis 

First Factor – Access 

(Table 3) Factor first, is referred to as the primary factor, and it is the most important and fundamental factor that 

accounts for the largest variance percentage (27.922). The variables and their loadings are tabulated below- 
 

Table 3. Significant loadings of variables for Factor 1- Access 

 
SN. Statement Variables Significant 

Loadings 

1 Do you own a smartphone? AC1 0.730 

2 Do you operate a bank account? AC2 0.798 

3 Do you use your smartphone for any financial 

transactions? 

AC3 0.622 

4 Do you have an ATM card? AC4 0.737 

Note: The table shows the results of the questionnaire's access level. Appendix A contains a list of all variables. 
 

Under this factor, a total of four variables were loaded. This major factor seems to have a high loading on 

the majority of commonly developed variables. The affirmative loading indicates that all variables are significantly 

connected with one another, implying the importance of customer access to financial information. 

 

Second Factor – Usage 

(Table 4) There are so many variables connected to usage has significantly positive loadings in the subsequent factor. 

A positive correlation between variables causes positive loading. This second component is responsible for the 

second-most percentage of variance, 6.395. 

 

Table 4. Significant loadings of variables for Factor 2- Usage 

 
SN. Statement Variables Significant 

Loadings 

 What are the advantages of using digital payment 
over conventional payment during a lockdown? 

  

1 User Friendly US1 0.892 

2 Secured US2 0.872 

3 Faster Settlements US3 0.879 

4 How many times have you made online 
transactions 

through digital platforms before lockdown, in a    

week? 

US4 0.831 

5 How many times have you made online 

transactions through digital platforms during the 

lockdown, in a   week? 

US5 0.825 

6 How many times you are using digital payments 

post lockdown, in a week? 

US6 0.855 

Note: The table shows the results of the questionnaire's access level and the total factors were 6. Appendix A contains a list of all variables. 

 

There is a total of six variables that loaded relatively in this factor. Based on the data in the above table, we 

can conclude those usage variables are positively related to one another.                         

 

Third Factor– Technology 

(Table 5) The third factor accounts for 5.752 of the total variances. This factor has significant positive loadings as 

well. Below is a list of variables and their significant loadings. 
 
 

Table 5. Significant loadings of variables for Factor 3- Technology 

 
SN. Statement Variables Significant 

Loadings 

 Why was there a shift in preference from offline to online payment 

during a lockdown? 

  

1 Fast and convenient TH1 0.906 

2 Safe and secured TH2 0.889 

3 No physical contact in making payments TH3 0.864 

4 Rewards TH4 0.696 

Note: The table shows the results of the questionnaire's technology factor. Appendix A contains a list of all variables. 
 

In this factor, four variables were heavily loaded. The variables' positive loadings indicate that they have a 

positive relationship with one another.  

 

Fourth Factor– Literacy 

(Table 6) The fourth factor accounts for 5.564 of the total variances. This factor has significant positive loadings as 

well. Below is a list of variables and their significant loadings. 



Gupta & Verma, Indian Journal of Finance and Banking 11(1) (2022), 1-14 

 

7 

Table 6. Significant loadings of variables for Factor 4- Literacy 

 
SN. Statement Variables Significant 

Loadings 

 What factors hampered the use of digital payment systems 

during a lockdown? 

  

1 Digital illiteracy LT1 0.722 

2 Lack of Infrastructure LT2 0.717 

3 Security LT3 0.816 

4 Do you feel digital literacy is a must for using a digital payment system? LT4 0.897 

Note: The table shows the results of the questionnaire's literacy factor. Appendix A contains a list of all variables. 
 

In this factor, four variables were heavily loaded. The variables' positive loadings indicate that they have a 

positive relationship with one another. 

 

KMO Statistics- Validity of Test 

(Table 7) This table displays two tests that indicate our data's eligibility for structure detection. The Kaiser- Meyer-

Olkin Measure of Sampling Adequacy is a statistic that mirrors the level of fluctuation in our variables that could be 

clarified by basic variables. High scores (around 1.0) imply that factor analysis may be effective with our data. If the 

value is less than 0.50, the factor analysis results are unlikely to be meaningful (Chan & Idris, 2017). 

Bartlett's sphericity test examines the hypothesis that the correlation matrix is a personality framework, 

indicating that our variables are inconsequential and accordingly unsatisfactory for structure location. Little upsides of 

the significance level (under 0.05) show that a factor analysis might be beneficial to our information. 

 

Table 7. Result of KMO and Bartlett’s Test 

 
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .853 

   Bartlett’s Test of                   Approx. Chi-Square 

Sphericity        df 

           Sig. 

7066.620 

595 

.000 

 

The Kaiser-Meyer-Olkin Measure of Sampling Adequacy for these data is 0.853, which is in the Meritorious 

category. As a result, the data's validity has been confirmed. Furthermore, Bartlett's test of sphericity is highly 

significant (P<0.001), indicating that factor analysis will be appropriate. 

 

Table 8. Communalities of 34 items 
 

  Initial Extraction 

1 Do you own a smartphone? 1.000 .746 

2 Do you operate a bank account? 1.000 .717 

3 Do you use your smartphone for any financial transactions? 1.000 .747 

4 Do you have an ATM card? 1.000 .636 

5 Do you have access to financial inclusion mechanisms like Self 

Help Groups, Microfinance Institutions, Banks, Post Office, etc.? 

1.000 .628 

6 Tick the first financial institutions you have interacted with- 1.000 .534 

7 Do you have an internet facility in your smartphone? 1.000 .680 

8 Are you using any payment Apps (Applications)? 1.000 .844 

9 What are the applications you are using most? 1.000 .667 

10 If you are using the application, since how long you are using. 1.000 .726 

11 If you are not using any application, it’s because, 1.000 .648 

12 What are the advantages of using digital payment over 

conventional payment during a lockdown? (Ranking, 1 – Least and 5 – High) 

[User Friendly] 

1.000 .853 

13 What are the advantages of using digital payment over conventional payment 

during a lockdown? (Ranking, 1 – Least and 5 – High) [Secured] 

1.000 .830 

14 What are the advantages of using digital payment over 

conventional payment during a lockdown? (Ranking, 1 – Least and 5 – High) 

[Faster settlements] 

1.000 .839 

15 How do you typically pay your bills? 1.000 .473 

16 Why do you use cash for transactions? 1.000 .621 

17 How many times you made online transactions through digital platforms before 

lockdown, in a week? 

1.000 .810 

18 How many times you made online transactions through digital 

platforms during a lockdown, in a week? 

1.000 .822 

19 How many times you are using digital payments post lockdown, in a week? 1.000 .850 

20 Do you like to test new technologies? 1.000 .727 



Gupta & Verma, Indian Journal of Finance and Banking 11(1) (2022), 1-14 

 

8 

21 Have you registered for any new E-wallet transactions during a lockdown? 1.000 .660 

22 Do you prefer using digital payment for high-value transactions? 1.000 .544 

23 Why was there a shift in preference from offline to online payment during a 

lockdown? (Ranking, 1- Least and 5- High) [Fast and convenient] 

1.000 .865 

24 Why was there a shift in preference from offline to online payment 

during a lockdown? (Ranking, 1- Least and 5- High) 

[Safe and secured] 

1.000 .844 

25 Why was there a shift in preference from offline to online 

payment during a lockdown? (Ranking, 1- Least and 5- High) [No 

physical contact in making payments] 

1.000 .818 

26 Why was there a shift in preference from offline to online 

payment during lockdown? (Ranking, 1- Least and 5- High) 

[Rewards] 

1.000 .653 

27 How do you rate the security of digital payment? 1.000 .703 

28 Do you think the government should mandate digital payment in 

place of cash payments post lockdown? 

1.000 .481 

29 What factors hampered the use of digital payment systems 

during a lockdown? (Digital illiteracy) 

1.000 .772 

30 What factors hampered the use of digital payment systems during a 

lockdown? (Lack of Infrastructure) 

1.000 .618 

31 What factors hampered the use of digital payment systems during a 

lockdown? (Security) 

1.000 .743 

32 What factors hampered the use of digital payment systems 

during lockdown? (Additional Charges) 

1.000 .632 

33 What factors hampered the use of digital payment systems 

during lockdown? (Others) 

1.000 .641 

34 Do you feel digital literacy is a must for using a digital 

payments system? 

1.000 .825 

 
TOTAL 1.000 .991 

Note: Extraction Method: Principal Component Analysis. 
 
 

(Table 8) The principal component analysis is based on the fundamental assumption that all variance is shared 

prior to the extraction of the communalities. The level of variance in every factor that is represented is shown by 

networks. Introductory communalities are assessments of the change in every factor that can be clarified by the parts 

in general or factors. For correlation analysis, this is dependably equivalent to 1.0 for principal component extraction. 

The amount of variance explained by the retained components in each variable is indicated by the 

communalities after extraction, which demonstrates that loadings less than 0.6 are minimized in the conclusion. 

Extraction communalities are assessments of the change in every factor that the parts represent. Because the sample 

size is more than 300, the average communalities in this table are greater than 0.7, indicating that the extracted 

components accurately represent the variables. 

 

Table 9. Total Variance of Factors 

 

Components Initial Eigenvalues Extraction Sums of Squared      Loadings Rotation Sums of Squared Loadings 

Total % Of 

Varia

nce 

Cumulative 

% 

Total % Of 

Variance 

Cumulative 

% 

Total % Of 

Variance 

Cumulative % 

1 11.448 27.922 27.922 11.448 27.922 27.922 7.975 19.452 19.452 

2 2.622 6.395 34.317 2.622 6.395 34.317 3.257 7.944 27.396 

3 2.358 5.752 40.069 2.358 5.752 40.069 3.127 7.627 35.023 

4 2.281 5.564 45.633 2.281 5.564 45.633 2.175 5.305 40.327 

5 1.761 4.295 49.928 1.761 4.295 49.928 1.878 4.580 44.907 

6 1.655 4.036 53.964 1.655 4.036 53.964 1.818 4.434 49.341 

7 1.307 3.187 57.152 1.307 3.187 57.152 1.719 4.194 53.535 

8 1.214 2.960 60.111 1.214 2.960 60.111 1.684 4.106 57.641 

9 1.149 2.802 62.913 1.149 2.802 62.913 1.408 3.435 61.076 

10 1.115 2.718 65.631 1.115 2.718 65.631 1.399 3.413 64.489 

11 1.032 2.517 68.148 1.032 2.517 68.148 1.326 3.235 67.723 

12 1.006 2.453 70.602 1.006 2.453 70.602 1.180 2.879 70.602 

13 .908 2.215 72.817       

14 .895 2.183 75.000       

15 .826 2.014 77.014       

16 .782 1.907 78.921       

17 .732 1.786 80.707       

18 .689 1.682 82.389       



Gupta & Verma, Indian Journal of Finance and Banking 11(1) (2022), 1-14 

 

9 

19 .636 1.552 83.941       

20 .621 1.514 85.455       

21 .577 1.407 86.863       

22 .555 1.354 88.217       

23 .505 1.232 89.449       

24 .484 1.180 90.629       

25 .462 1.126 91.755       

26 .420 1.024 92.779       

27 .403 .982 93.761       

28 .368 .899 94.660       

29 .329 .803 95.463       

30 .307 .749 96.212       

31 .265 .646 96.858       

32 .247 .603 97.462       

33 .210 .513 97.975       

34 .185 .451 98.426       

35 .151 .367 98.794       

36 .139 .338 99.132       

37 .120 .292 99.424       

38 .102 .249 99.673       

39 .084 .204 99.877       

40 .050 .123 10.000       

Note: This table displays the Extraction Method: Principal Component Analysis. 

 

(Table 9) Total Variance explained is shown in the above table, while Eigenvalue really represents the quantity 

of extricated factors whose aggregate ought to be equivalent to the quantity of things exposed to factor analysis. 

Primarily inspired by Initial Eigenvalues and Extracted Sums of Squared Loadings for examination and understanding. 

The presence of eigenvalues is more noteworthy than one is needed for perceiving the quantity of parts or factors 

communicated by chosen factors. The proportion of variance column indicates how much variance within the concept 

that component accounts for. 

A total of 12 factors are identified from the data, with the eight factors accounting for over 60% of the variance 

within the construct. 

 

Rotated Component Matrix 

(Table 10) The rotational component matrix assists us in determining what the components stand for. The goal of the 

rotation is to minimize the range of factors that have strong loadings on the variables under consideration. The rotation 

has no effect on the analysis itself, but it simplifies interpretation. 

 

Table 10. Rotated Component Matrixa 

 

                                                 Component 

1 2 3 4 5 6 7 8 9 1

0 

1

1 

12 

Do you own a 

smartphone? 

      .34

3 

 .73

0 

   

Do you operate a bank 

account? 

      .79

8 

     

Do you use your smartphone for 

any financial transactions? 

  .62

2 

         

Do you have an ATM card?       .73

7 

     

Do you have access to 

financial inclusion 

mechanisms like Self Help 

Groups, Microfinance 

Institutions, Banks, Post 

offices, etc..? 

    .47

9 

       

Tick the first financial 

institutions you have 

interacted with- 

    
 

  -

.6

28 

    

Do you have an internet 

facility in your smartphone? 

    
 

   .7

61 

   

Are you using any payment 

Apps  

(Applications)? 

  .7

04 

 
 

       



Gupta & Verma, Indian Journal of Finance and Banking 11(1) (2022), 1-14 

 

10 

What are the applications you 

are using most? 

  .7

05 

 
 

       

If you are using the 

application, since how long 

you are using? 

.

4

5

8 

.4

17 

  
 

-

.3

52 

      

If you are not using any 

application, it’s because of, 

    
 

    .7

92 

  

What are the advantages of 

using digital payment over 

conventional payment during 

a lockdown? (Ranking, 1– 

Least and 5 – High) [User 

Friendly] 

.

8

9

2 

   
 

       

What are the advantages of 

using digital payment over 

conventional payment during 

a lockdown? (Ranking, 1– 

Least and 5 – High) 

[Secured] 

.

8

7

2 

   
 

       

What are the advantages of 

using digital payment over 

conventional payment during 

a lockdown (Ranking, 1 

– Least and 5 – High) [Faster 

settlements] 

 

.

8

7

9 

   
 

       

How do you typically pay 

your bills? 

  .3

17 

 
 

    .3

27 

  

Why do you use cash for 

transactions? 

    
 

  .6

57 

    

How many times you made 

online transactions through 

digital platforms before 

lockdown, in a week? 

 .8

31 

  
 

       

How many times you made 

online transactions through 

digital platforms during a 

lockdown, in a 

week? 

 .8

25 

  
 

       

How many times you are 

using digital payments post 

lockdown, in a   week? 

 .8

55 

  
 

       

Do you like to test new 

technologies? 

.

5

9

4 

   
 

       

Have you registered for any 

new E-wallet transactions 

during 

A lockdown? 

  .6

15 

 
 

       

Do you prefer using digital 

payment for high-value 

transactions? 

  .4

10 

 
 

.4

00 

      

Why was there a shift in 

preference from offline to 

online payment during a 

lockdown? (Ranking, 1- 

Least and 5- High) [Fast and 

convenient] 

.

9

0

6 

   
 

       

Why was there a shift in 

preference from offline to 

online payment during a 

lockdown? (Ranking, 1- 

Least and 5- High) [Safe and 

secured] 

.

8

8

9 

   
 

       



Gupta & Verma, Indian Journal of Finance and Banking 11(1) (2022), 1-14 

 

11 

Why was there a shift in 

preference from offline to 

online payment during a 

lockdown? 

(Ranking, 1- Least and 5- 

High) [No physical contact in 

making 

payments] 

.

8

6

4 

   
 

       

Why was there a shift in 

preference from offline to 

online payment during a 

lockdown? (Ranking, 1- 

Least and 

5- High) [Rewards] 

.

6

9

6 

   
 

       

How do you rate the 

security of digital payment? 

.

5

8

4 

   
 

       

Do you think the government 

should mandate digital 

payment in place of cash 

payments post 

lockdown? 

  .6

16 

 
 

       

What factors hampered the 

use of digital payment 

systems during a lockdown? 

(Digital illiteracy) 

    .72

2 

       

What factors hampered the 

use of digital payment 

systems during a lockdown? 

(Lack of 

Infrastructure) 

    
 

.7

17 

      

What factors hampered the 

use of digital payment 

systems during a lockdown? 

(Security) 

    
 

     .8

16 

 

What factors hampered the 

use of digital payment 

systems during a lockdown? 

(Additional Charges) 

    
 

.6

21 

      

What factors hampered the 

use of digital payment 

systems during a lockdown? 

(Others) 

     

-

.75

0 

       

Do you feel digital literacy is 

a must for using digital 

payments 

system? 

    
 

      .897 

TOTAL .83

3 

.3

83 

 .3

10 

 

       

Note: Table displays the Extraction Method: Rotation Method and Principal Component Analysis: Varimax with Kaiser Normalization.a 

 

Rotation Converged in 10 Iterations 

There is a moderate to strong correlation between among 12 items in (Table-11) and a component of factor 1. And in 

such cases, the correlations between -0.628 and -0.750 are considered relatively tiny and are excluded from the matrix.  

 

Table 11. Component Transformation Matrix 

 

Comp onent 1 2 3 4 5 6 7 8 9 10 11 12 

1 .787 .364 -

.3

47 

.1

22 

.11

1 

-.191 -

.0

80 

.203 -.060 -.098 -

.03

2 

.035 

2 -

.34

8 

.532 .2

12 

.6

76 

-

.0

34 

-.262 -

.0

85 

.045 .013 -.066 -

.01

1 

.101 

3 .257 -

.14

4 

.6

32 

.0

06 

.48

0 

-.203 .4

23 

.018 .154 -.093 -

.04

3 

.172 



Gupta & Verma, Indian Journal of Finance and Banking 11(1) (2022), 1-14 

 

12 

4 .376 -

.44

7 

.3

80 

.4

20 

-

.4

03 

.069 -

.3

43 

-.112 -.159 .030 .0

3

1 

-.116 

5 .196 .283 .0

47 

.0

60 

-

.3

73 

.229 .4

20 

-.312 .516 .293 -

.04

8 

-.236 

6 .047 .254 .2

44 

-

.0

94 

.16

6 

.530 -

.2

92 

.129 .216 -.341 .5

2

5 

-.129 

7 .023 -

.09

8 

-

.2

06 

.2

72 

.51

2 

.062 -

.1

14 

-.381 -.034 .554 .3

7

5 

.017 

8 -

.04

2 

-

.14

1 

-

.0

32 

.1

71 

.25

3 

.286 -

.2

80 

.447 .417 .253 -

.53

4 

-.042 

9 -

.00

6 

-

.03

4 

.0

05 

.1

50 

-

.1

73 

.267 .4

31 

.605 -.312 .331 .3

0

0 

.162 

10 .093 .387 .3

28 

-

.3

07 

-

.0

44 

.262 -

.2

34 

-.190 -.333 .328 -

.28

3 

.424 

11 .017 -

.13

0 

-

.0

54 

-

.1

12 

-

.2

59 

-.265 -

.2

04 

.086 .501 .102 .3

0

3 

.654 

12 .016 -

.14

8 

-

.2

74 

.3

27 

.04

4 

.469 .2

33 

-.274 -.026 -.419 -

.17

7 

.486 

Note: Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. 

 

The variables' values are described in the table above following factor extraction using the Rotation Method: 

Varimax with Kaiser Normalization. 
 

DISCUSSIONS 

The current research looked at the relationship between customer-related factors and their impact on FinTech and financial 

inclusion in India. The findings show that there is a significant positive relationship among such variables. Ease of use, 

safety, and security of their fund; frictionless transactions, etc. are the variables that give people the confidence to involve 

in online financial transactions. The result is in the line of findings of (Daragmeh et al., 2021). The results also indicate the 

areas where more emphasis should be given to accelerate the use of FinTech services and the rate of financial inclusion. 

Though the study indicates that the use of smartphones for any financial transactions is significant, there is further room to 

create an eco-system where people can use their smartphones for almost all financial transactions. Reward system is one 

area, which can be used to persuade more and more people to use online modes of transactions. Financial literacy is 

considered a base of financial inclusion and increasing the rate of financial literacy will increase the pie of FinTech and 

resultantly financial inclusion in India. Our study confirms the outcome of (Ahmad et al., 2021). That FinTech could 

accelerate the growth of financial inclusion 
 

CONCLUSIONS   

This study is as one of the first in developing countries to cover FinTech (payment system) and Financial Inclusion, 

in the setup of the Covid-19 epidemic. The study sought to investigate how this COVID19 pandemic has impacted 

the use of FinTech services and in turn financial inclusion and concludes that the advancement of technology has 

accelerated the use of FinTech services. The study emphasizes the fact that a well-developed eco-system, with 

increased level of financial literacy can significantly boost the adoption of Fintech services and in turn financial 

inclusion. 

Albeit this investigation makes several contributions, it has limitations also, like we have taken just one 

of the factors- digital payment, as the proxy of FinTech. Most quiet that we could also focus on other FinTech 

proxies such as Micro Insurance, Lending, Equity financing, and so on, though it is a very broad part of the Fintech, 

that's why we have taken only the digital payment. Future studies will likely investigate the influence of the COVID-

19 pandemic on fintech adoption in both progressed and arising economies. Second, further study can be conducted 

to discuss how to enhance digital literacy, and last is to analyze the same situation after the Covid-19 incident to see 

whether people are using these services. 

 
 

 

Author Contributions: Conceptualization, S.V.; Methodology, M.G.; Software, S.V.; Validation, M.G.; Formal Analysis, M.G. and S.V.; Investigation, 
M.G.; Resources, S.V.; Data Curation, S.V.; Writing – Original Draft Preparation, M.G. and S.V.; Writing – Review & Editing, M.G. and S.V.; 

Visualization, S.V. and M.G.; Supervision, S.V.; Project Administration, S.V.; Funding Acquisition, S.V. and M.G. Authors have read and agreed to the 

published version of the manuscript. 

Institutional Review Board Statement: Ethical review and approval were waived for this study, due to that the research does not deal with vulnerable 

groups or sensitive issues. 



Gupta & Verma, Indian Journal of Finance and Banking 11(1) (2022), 1-14 

 

13 

Funding: The authors received no direct funding for this research. 

Acknowledgments: N/A.  

Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. 

Data Availability Statement: The data presented in this study are available on request from the corresponding author. The data are not publicly available 
due to restrictions. 

Conflicts of Interest: The authors declare no conflict of interest.      

 

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