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. 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