Perception,Adoption,and Pattern of Usage of FinTech Services by Bank Customers: Evidences from Hojai District of Assam

Abstract

With the advent of technology, banking and financial services have widened their scope. India achieved FinTech adoption rate of 87 percent as against the global average of 64 percent mostly contributed by FinTech startups aiming for providing access to financial services even in the remotest areas. Realizing the potential of FinTech to contribute toward financial inclusion and stability, the Governments have taken requisite steps toward digital transformation and promote FinTech ventures. In order to meet the customers’ needs, collaborative moves with FinTech firms have been initiated by financial institutions as well. This article aims to investigate the relationship between different demographic profiles, the adoption of FinTech services, the perception, user pattern, and constraints faced by the bank customers in using FinTech services. The results based on survey of 215 respondents reveal significant association between usage of FinTech services and different demographic profiles. However, the awareness and use of such services is found more among millennials and generation Z as compared with generation X and baby boomers. While the FinTech companies gained the popularity in payment space, it is observed that misconception is an important factor that hinders the growth of technology-based services among respondents.

Keywords

Finance adoption perception finTech financial institutions government

Introduction

Financial technology (popularly known as FinTech) refers to the use of technology to upgrade and automate the design and delivery of financial services. FinTech firms provide a variety of services under a single umbrella such as money transfer, financing start-ups, wealth management services, and insurance. FinTech services have also foreyed into the banking services such as deposits, payments, and collection. FinTech firms are increasingly made instrumental for financial inclusion in India. The Government of India, through the introduction of India Stack, encouraged the growth of FinTech ventures which create unified software platform with the purpose of bringing India’s population into the digital age. With the ever-increasing population of smartphone user (about 500 million by 2020), the digital banking space is expected to witness exponential growth (PwC & Startupbootcamp, 2017). The consumers’ preference toward the variety of FinTech services and the Government’s steps to improve the access by rolling out payment banks and upgrade digital transformation are positive moves. In recent years, various financial institutions have taken a digital route and a collaborative move with the FinTech firms to meet the customers’ needs. The ICICI bank has 1 billion fund for FinTech partnerships and has also developed mobile applications for various segments of the customers, that is, iMobile (a banking app), iPal (an artificial intelligence powered chat box), iBiz (a mobile application for corporate and small and medium enterprises), and Mera iMobile (an e-wallet for the purpose of rural lending) (Hetankar, 2018). State Bank of India (SBI) has also developed apps to provide user-friendly services to its customers which include YonoLite and SBI’s chat box SIA that is designed to handle queries. Thus, embracing of technology in banking, financial services, and insurance sector will help in reaching the unreached segments of the population and will provide better and innovative experience to bank customers and assist the banks to flourish.

The Context

The development of technology has resulted in flexible payment channels and it provides the bank customers with user-friendly bank services. People use mobile wallets such as Paytm, MobiKwik, Unified Payment Interface (UPI) to perform their payment operations. According to EY Global FinTech Adoption Index (2019), India and China are way ahead with an adoption rate of 87 percent which is higher than the global average of 64 percent. Although the adoption rate is more in urban areas, significant steps have been taken by the Government to augment FinTech usage in rural areas. The customers are able to make payments, purchase insurance, manage assets, and avail loans with the help of financial technology. Thus, the use of financial technology in the banking sector revamps banking services and provides better user experience. The North East India by nature is a disadvantaged region in terms of physiological and infrastructural front and financial infrastructure in terms of number of banks, and number of population per bank is also much lesser compared with other regions of the country. As per Reserve Bank of India report (2018), there are 4,612 functioning offices of commercial banks in the northeastern region of India for the quarter ended December 2018, whereas the functioning offices of commercial banks in other regions of the country are very high in number, that is, northern region (27,306), eastern region (25,170), central region (29,958), western region (22,699) and southern region (41,744). It will also not be wise to set up brick and mortar branches of the banks in every village of North East because of high cost and economies of adverse scale. In this case, FinTech has an important role to play to mitigate the gap of financial access in the region. The current study is done in newly formed Hojai district (till August 15, 2015, it was under Nagaon district of Assam). It is one of the fastest growing districts in Assam in terms of trade and small-scale industries. It is the center of Agar (Aloes wood) perfume industry, an important wholesale market of rice, and known for its trade hub. As Hojai is an important business center, it is important to study the adoption, perception, and pattern of usage of technology-based financial services by the people in this district.

Objectives

To analyze the adoption of FinTech services across different demographic profile.

To examine the perception and to analyze the pattern of usage of FinTech services by bank customers in the area of the study.

To ascertain the constraints faced by the customers while using various technology-based financial services.

Research Methodology

Type of research: The research is empirical in nature based on primary data.

Area of the study: The area of the study covers Hojai district of Assam. For the purpose of collecting the data, the customers of a private bank, that is, ICICI Bank, a public sector bank, that is, SBI and a Regional Rural Bank, that is, Assam Grameen Vikas Bank (AGVB) are selected. The list of banks that has been selected for the study has been given in Table 1.

Technique of data collection: Mainly primary sources are used for collecting data, and a structured interview schedule is used for collecting primary data. Supporting secondary data are also collected from various reports and journals.

Sample size: The sample size includes 215 respondents who are the customers of SBI, ICICI bank, and AGVB. Responses from 25 respondents are collected from each of the four branches of SBI and three branches of ICICI and responses from 20 respondents are collected from each of the two branches of AGVB.

Sampling technique: Convenience sampling.

Data analysis technique: Data is analyzed using percentage method, chi-square test, and weighted mean.

Profiling of the Respondents

A total of 215 respondents have been interviewed for the purpose of this study. A structured interview schedule was prepared for the survey and the data were collected from the customers of SBI, ICICI, and AGVB.

Table 1.

List of Banks Selected for the Study

Bank Name	Total Branches in the District	Number of Bank Branches Selected for the Study	Respondents Interviewed
SBI	7	4	100
ICICI	3	3	75
AGVB	7	2	40
Total			215

Source: Total number of branches in the district obtained from State Level Bankers’ Committee report (2019).

Table 2.

Different Demographic Characteristics of the Respondents

Demographic Characteristics		Percentage
Gender	Male	53
	Female	47
Age	18–28 years	25
	29–39 years	25
	40–50 years	27
	Above 50 years	23
Annual income	Up to ₹ 250,000	29
	₹ 250,000–₹ 500,000	21
	₹ 500,001–₹ 750,000	23
	₹ 750,001–₹ 1,000,000	15
	Above ₹ 1,000,000	12
Occupation	Businessmen	21
	Agriculturist	8
	Government service/PSUs	13
	Private service	19
	Professionals	7
	Student	11
	Housewife	19
	Retired person	2
Educational qualification	Below or till 10th standard	21
	12th standard	24
	Graduate	27
	Postgraduate	23
	Did not attend school	5

Source: The authors.

From Table 2, it can be observed that the percentage of male and female respondents is 53 and 47 percent which is approximately same with the sex ratio of the Indian population as per Census 2011. With regard to the annual income of the respondents, it is seen that 50 percent of the respondents belong to the income group up to ₹ 500,000, followed by almost one-fourth of the respondents with annual income ranging from ₹ 500,000–₹ 750,000 and little above one-fourth of the respondents belong to the income category above ₹ 750,000. It is also revealed from the table that most of the respondents are businessmen, private service holders, and housewives and the educational qualification of most of the respondents, that is, 27 percent is graduation.

Data Analysis and Interpretation

Demographic Characteristics and Adoption of FinTech Services

Generally, FinTech service usage is influenced by demographic characteristics. This section aims to trace the relationship between demographic characteristics of sample respondents and adoption of FinTech services. In relation to objective number one, the following hypotheses have been formed.

H_A: There is no association between gender and adoption of FinTech services.

While examining the association between gender and the adoption of FinTech services, it is found that 57.6 percent of male respondents regularly use FinTech services as compared with 36.3 percent of female respondents (see Table 3). Hence, the adoption of FinTech services is found more among males. This is also justified by chi-square test where p < 0.05, which shows that there is significant association between gender and the adoption of FinTech services; hence, the null hypothesis is rejected at 0.05 level of significance.

H_B: There is no association between age and adoption of FinTech services.

Table 3.

Gender and Adoption of FinTech Services

Gender	Adoption of FinTech Services					Chi-Square Test	df	P Value
Gender	Never (%)	Rarely (%)	Sometimes (%)	Often (%)	Frequently (%)	Chi-Square Test	df	P Value
Male	16.8	13.3	12.4	37.2	20.4	21.539	4	0.000
Female	43.1	14.7	5.9	27.5	8.8

Source: The authors.

Table 4.

Age and Adoption of FinTech Services

Age	Adoption of FinTech Services					Chi-Square Test	df	P Value
Age	Never (%)	Rarely (%)	Sometimes (%)	Often (%)	Frequently (%)	Chi-Square Test	df	P Value
18–28	16.7	14.8	1.9	48.1	18.5	31.853	12	0.001
29–39	20.8	7.5	9.4	45.3	17
40–50	36.2	17.2	12.1	24.1	10.3
Above 50	44	16	14	12	14.9

Source: The authors.

Table 5.

Income and Adoption of FinTech Services

Income	Adoption of FinTech Services					Chi-Square Test	df	P Value
Income	Never (%)	Rarely (%)	Sometimes (%)	Often (%)	Frequency (%)	Chi-Square Test	df	P Value
Up to ₹ 250,000	58.5	20.7	4.9	11	4.9	101.264	16	0.000
₹ 250,001–₹ 500,000	20	8.9	6.7	55.6	8.9
₹ 500,001–₹ 750,000	9.3	7.4	14.8	48	20.44
₹ 750,001–₹ 1,000,000	5	25	10	30	30
Above ₹ 1,000,000	0	0	21.4	28.6	50

Source: The authors.

It is also found that 66.6 and 62.3 percent of the respondents belonging to the age group 18–28 years and 29–39 years repeatedly use FinTech services whereas only 34.4 percent of the respondents in the age category 40–50 years and 26.9 percent of the respondents in the age group above 50 years are regular users of FinTech services (see Table 4). Thus, the use of technology-based financial services is mainly tilted toward the younger generation. It is also observed that the p value <0.05 which is evident that there is association between age and the adoption of FinTech services; therefore, the null hypothesis is rejected at 0.05 level of significance and it can be said that the adoption of FinTech services is positively correlated with age.

H_C: There is no association between income and adoption of FinTech services

While examining the relationship between income and adoption of FinTech services, a positive relation has been found, and it is observed that the p value <0.05 (see Table 5) resulted in the rejection of null hypothesis and shed light that there is association between the income of the respondents and the adoption of technology-based financial services. Thus, the adoption of FinTech services depends on the income of the customers. It is also observed that 68.44 percent of the respondents belonging to the income group ₹ 500,001–₹ 750,000 are frequent users of FinTech services whereas 15.9 percent of the respondents in the income group up to ₹ 250,000 are regular users of technology-based financial services which mainly include students and customers with private service (see Table 5).

H_D: There is no association between educational qualification and adoption of FinTech services

There is also a positive relation observed between educational qualification and adoption of FinTech services. It is also observed that 21.2 percent respondents with educational qualification below or till 10th standard, 38.9 percent respondents with qualification up to 12th standard, 60.7 percent of graduates, and 79 percent postgraduates are regular users of FinTech services, and it is also found from the survey that the respondents who do not have any formal education have never used FinTech services (see Table 6). While trying to test the hypothesis to determine the association between education and adoption of FinTech services, it is found that p value is less than 0.05 (see Table 6) which resulted in the rejection of null hypothesis and shows that the use of FinTech services depends on consumer education. Vally and Divya (2018) in their paper stated that more educated people are expected to have positive attitude toward adoption of innovation. From the analysis, it can be seen that the usage of FinTech services is more among graduates and postgraduates.

H_E: There is no association between occupation and adoption of FinTech services

Table 6.

Educational Qualification and Adoption of FinTech Services

Educational Qualification	Adoption of FinTech Services					Chi-Square Test	df	P Value
Educational Qualification	Never (%)	Rarely (%)	Sometimes (%)	Often (%)	Frequently (%)	Chi-Square Test	df	P Value
Below or till 10th standard	46.8	23.4	8.5	19.1	2.1	71.041	16	0.000
12th standard	35.2	13	13	27.8	11.1
Graduate	13.1	18	8.2	41	19.7
Postgraduate	9.3	2.3	9.3	48.8	30.2
Did not attend school	100	0	0	0	0

Source: The authors.

Table 7.

Occupation and Adoption of FinTech Services

Occupation	Adoption of FinTech Services					Chi-Square Test	df	P Value
Occupation	Never (%)	Rarely (%)	Sometimes (%)	Often (%)	Frequently (%)	Chi-Square Test	df	P Value
Businessmen	2.2	6.5	15.2	52.2	23.9	135.671	28	0.000
Agriculturist	78.9	21.1	0	0	0
Government service/PSUs	17.9	25	10.7	32.1	14.3
Private service	17.8	6.7	6.7	53.3	15.6
Professionals	0	0	20	33.3	46.7
Student	20.8	29.2	4.2	33.3	12.5
Housewife	75	15.6	9.4	0	0
Retired person	83.3	16.7	0	0	0

Source: The authors.

Figure 1.

Source: Authors’ analysis.

While determining the frequency of usage of FinTech services among the respondents with different occupation, it is found that 76.1 percent businessmen, 46.4 percent government/PSU service holders, 80 percent professionals, 45.8 percent students regularly use FinTech services. However, it is also observed that agriculturist, housewives, and retired persons are skeptical toward adopting technology-based financial services; according to the results of the survey, 21.1 percent agriculturists, 15.6 percent housewives, and 16.7 percent retired persons (see Table 7) rarely use FinTech services and the reason behind the low use is the lack of education and most importantly the misconception toward the FinTech services. It is also evident from the chi-square test where p < 0.05 that there is association between occupation and the adoption of FinTech services. Hence, the null hypothesis is rejected at 0.05 level of significance.

Purposes for the Use of Debit/Credit Cards

The respondents use banking cards to withdraw money from ATMs. However, 68 percent (see Figure 1) respondents also use banking cards to make payment at Point of Sale (PoS), to make purchases from e-commerce companies, to make payment at malls/ restaurants, and also to make online purchase of flight, railway, and bus tickets. This can be apparently seen that the use of digital payments in the area of the study is increasingly supplanting cash payments. However, cash still dominates the payment of fees in both private and government schools and colleges; thus, the schools and colleges in the area of the study should also promote cashless modes of payment.

It is also observed that 15 percent (see Figure 1) of the respondents belonging to marginalized section uses banking cards to withdraw cash from business correspondents’ outlet and not for other purposes; thus, this section of the bank customers should be educated and motivated to use banking cards while making purchases rather than only withdrawing cash. The wider growth of technological innovations and mobile penetration contributes to a transformation in the payment ecosystem, and adequate knowledge and preparedness for these changes both by the urban and rural people are imperative to reap the benefits of seamless payments.

Perception About Technology-based Financial Services

It can be observed from the figure that most of the respondents, that is, 87, 86, and 100 percent (see Figure 2) perceive that the technology-based financial services are convenient and user friendly, provide fast and quick services, provide a spending analysis, reduce cost of financial services, and reduce the burden of handling cash. It is also seen that 55 percent of the respondents did not favor the fact that the apps can be used only for larger amount of transactions. In addition, 86 percent of the respondents did not support the fact that the apps are convenient for educated only whereas only 14 percent of the respondents perceive that the technology-based services are suitable for educated which includes the respondents belonging to the age group above 50 years (see Table 8). Out of 23 percent respondents who perceive that the technology-based financial services are unsecure, most of them belong to the age category 40–50 years and above 50 years (see Table 8). However, it is also observed that 56 percent of respondents belonging to the age group above 50 years perceive that the apps are unsecure as compared with 3.8 and 31 percent respondents belonging to the age group 29–39 years and 40–50 years (see Table 8). Thus, it can be understood that when it comes to generational preferences millennials or generation Y and generation Z mostly use and trust technology-based financial services. The millennials look for new digital products that are pertinent to their day-to-day lives (Mcanley & Weiner, 2015). However, generation X and baby boomers have low trust on FinTech services and prefer visiting bank branches. It is also seen that some older generation respondents also use these services but the percentage is very low. The advancements in technology resulted in the generation of various services for the benefit of the people, for example, Abaris is an online marketplace for annuities which provides retirement planning tools and educational content for the benefit of the customers (Mcanley & Weiner, 2015). The advancement in technology is bringing lots of benefits, and to acquire such advantage trust and knowledge about technology-based services by all the generations are of primary importance. However, over reliance is something different from trust and to avoid cyberattacks the customers should eschew sharing personal financial information and safeguard themselves from risks.

Awareness and User Pattern of Bank Customers Regarding Various Technology-based Financial Services

While determining the usage and awareness of various technology-based financial services among the bank customers, it is seen that most of the respondents, that is, 79 percent are aware about Paytm, 63 percent about Google Pay and UPI, and 77 percent about net banking. It can also be observed from Figure 3 that the awareness about Policybazaar (24 percent), Capital Float (7 percent), LendingKart (2 percent), NeoGrowth (1 percent), and RevFin (0 percent) is very low. In mobile banking space, the awareness about iMobile app of ICICI bank (42 percent), Yono app of SBI (42 percent), and Axis (37 percent) and HDFC mobile banking (40 percent) is satisfactory whereas the awareness about FinoBpay (1 percent), RBL MoBank 2.0 (1 percent), and AGVB mobile banking (20 percent) is low (see Figure 3). Thus, the awareness about mobile remittance and mobile payment app is high as compared with FinTech services working in the lending space. FinTech players are reshaping the way small businesses can access finance and help in improving financial inclusion by bridging the colossal gap in the demand and supply of SME loans, but in order to avail the benefits proper knowledge about such services is of utmost importance. Thus, FinTech firms should take adequate measures to make people aware especially in tier three and tier four cities regarding the different services provided by them. In addition, while discussing about the use of different technology-based financial services it is observed that a large number of respondents, that is, 66 percent use Paytm, 45 percent use Google Pay, and the usage of mobile wallets such as MobiKwik (6 percent), PhonePe (16 percent), FreeCharge (12 percent) is very low. The usage of net banking among the respondents is satisfactory, that is, 44 percent but the use of other FinTech services such as Policybazaar (7 percent), CapitalFloat (0 percent), LendingKart (0 percent), NeoGrowth (0 percent), RevFin (0 percent) is also very low (see Figure 4). It is also seen that the respondents are aware about mobile banking apps such as iMobile, Yono, Axis, and HDFC mobile banking but the usage is not very high. Thus, from the analysis it is found that the awareness and the usage of mobile wallets, that is, Paytm and Google Pay, are high in the area of the study while the awareness and use of other wallets such as FreeCharge, PhonePe, MobiKwik, and the FinTech services in the lending space such as Capital Float, LendingKart, and RevFin is very low.

Figure 2.

Source: Authors’ analysis.

Figure 3.

Source: Authors’ analysis.

Figure 4.

Source: Authors’ analysis.

Constraints Faced by Bank Customers in Using Various Technology-based Financial Services

In order to find out the variables that has the highest difficulty ratings, weighted scores of Likert scales have been calculated (Tables 9 and 10). The ranges to measure the constraints are grouped based on scales developed by Brown (2010). The statement-wise weighted score for difficulty level is calculated using the following formula:

\begin{array}{l} [N (SD) * (1) + N (D) * (2) + N (U) * 3 + \\ N (A) * (4) + N (SA) * (5)] / N (R) \end{array}

where

N(SD) = No. of respondents selecting strongly disagree

N(D) = No. of respondents selecting disagree

N(U) = No. of respondents selecting undecided

N(A) = No. of respondents selecting agree

N(SA) = No. of respondents selecting strongly agree

N(R) = Total number of respondents (Kostoulas, 2013).

Table 8.

Showing the Age Wise Perception of the Respondents Regarding Various Technology-based Financial Services

Age (in years)	They are Convenient					The Apps are User Friendly
Age (in years)	SD	D	N	A	SA	SD	D	N	A	SA
18–28	0%	0%	0%	40.70%	59.30%	0%	0%	0%	16.70%	83.30%
29–39	0%	0%	0%	37.70%	62.30%	0%	0%	0%	5.70%	94.30%
40–50	0%	20.70%	0%	36.20%	43.10%	20.70%	0%	0%	12.10%	67.20%
Above 50	0%	30%	0%	44%	26%	34%	0%	0%	36%	30%
Age	Service provided is fast and quick					The apps provide a spending analysis
Age	SD	D	N	A	SA	SD	D	N	A	SA
18–28	0%	0%	0%	3.70%	96.30%	0%	3.80%	0%	43.40%	52.80%
29–39	0%	0%	0%	3.80%	96.20%	0%	13.20%	0%	47.20%	39.60%
40–50	0%	0%	0%	6.90%	93.10%	0%	26.30%	0%	31.60%	42%
Above 50	0%	0%	0%	10%	90%	0%	44%	0%	28%	28%
Age	The apps provides incentives and rewards					Such services are unsecure
Age	SD	D	N	A	SA	SD	D	N	A	SA
18–28	0%	0%	0%	42.60%	57.40%	0%	100%	0%	0%	0%
29–39	0%	0%	0%	49.10%	50.95%	0%	96.20%	0%	3.80%	0%
40–50	0%	0%	0%	29.30%	70.70%	0%	69%	0%	31%	0%
Above 50	0%	0%	0%	36%	64%	0%	34%	0%	56%	10%
Age	Lack of net connectivity creates hindrance					Reduces cost of financial transactions
Age	SD	D	N	A	SA	SD	D	N	A	SA
18–28	7.40%	63%	11.10%	9.30%	9.30%	0%	0%	0%	42.60%	57.40%
29–39	11.30%	43.40%	17%	11.30%	17%	0%	0%	0%	37.70%	50.90%
40–50	22.40%	51.70%	0%	6.90%	19%	0%	0%	0%	48.30%	70.70%
Above 50	24%	10	0%	42%	24%	0%	0%	0%	54%	64%
Age	No need to carry cash					It is convenient for educated only
Age	SD	D	N	A	SA	SD	D	N	A	SA
18–28	0%	0%	0%	18.50%	81.50%	7.40%	63%	11.10%	9.30%	9.30%
29–39	0%	0%	0%	20.80%	79.20%	11.30%	43.40%	17%	11.30%	17%
40–50	0%	0%	0%	39.70%	60.39%	22.40%	51.70%	0%	6.90%	19%
Above 50	0%	0%	0%	28%	72%	24%	10%	0%	42%	24%
Age	The use of such services is complicated					Apps are used for larger amount of transactions
Age	SD	D	N	A	SA	SD	D	N	A	SA
18–28	48.10%	51.90%	0%	0%	0%	85.20%	14.80%	0%	0%	0%
29–39	35.80%	64.20%	0%	0%	0%	54.70%	45.30%	0%	0%	0%
40–50	36.80%	38.60%	0%	25%	0%	31%	62.10%	6.90%	0%	0%
Above 50	6%	28%	20%	46%	0%	42%	36%	22%	0%	0%

Source: Authors’ analysis.

Table 9.

Constraints Faced by the Bank Customers in Using Various Technology-based Financial Services

	Strongly Disagree (%)	Disagree (%)	Undecided (%)	Agree (%)	Strongly Agree (%)
High service charges	11	86	3	0	0
Absence of net connectivity	31	37	0	32	0
Poor speed of internet	30	38	4	27	1
Lack of technical knowhow	15	17	2	41	24
Transaction failure	25	34	0	41	0
Problem in the server	7	22	10	36	25
Problem of hacking	32	34	10	24	0
Low security (fraud messages, calls, etc.)	18	14	1	41	26
Documentation and formalities	74	26	7	5	0

Source: The authors.

Table 10.

Weighted Average Score

Statements	Highest Frequency (in Percentage)	Weighted Average Score
High services charges	Disagree (86)	1.91
Absence of net connectivity	Disagree (37)	2.34
Poor speed of internet	Disagree (38)	2.32
Lack of technical knowhow	Agree (41)	3.43
Transaction failure	Agree (41)	2.58
Problem in the server	Agree (36)	3.53
Problem of hacking	Disagree (34)	2.25
Low security (receiving fraud calls, messages)	Agree (41)	3.42
Documentation and formalities	Strongly disagree (74)	1.26

Source: The authors.

The cutoff score of the 5-point Likert scale = (Maximum − Minimum)/Group

\begin{array}{l} = (5 - 1) / 5 \\ = 0.80 \end{array}

In order to give interpretations for the weighted means, the statements should be converted into interval of means of equal difference which is 0.80 in case of 5-point Likert scale.

1 to 1.80 (Strongly disagree)

1.81 to 2.60 (Disagree)

2.61 to 3.40 (Undecided)

3.41 to 4.20 (Agree)

4.21 to 5 (Strongly agree)

From the means of equal difference given above and ranging from 3.41 to 4.20, it is seen that the points of highest difficulties faced are lack of technical knowhow while using the technology-based financial services, problem in the server, and low security such as receiving fraud calls and messages. In this context, adequate awareness while using the FinTech services such as not to type the password more than twice if the transaction is not being processed at a time should be given to the users as this will save them from the web of hackers. Also appropriate system should be put into place which will mitigate the problem in the server and eventually improve usage. In addition, with the progression in technology the issue of cybersecurity is also growing which creates threats in the minds of the customers and they resort to traditional methods of transactions. Thus, regular monitoring of transaction will help in reducing such problems. However, a legislation of data protection is also necessary to shield the bank customers against such fraudulent practices (Reserve Bank of India, 2017). Although cybersecurity rules exist in our country, they are still under development; thus the service providers should be wary about the cyber vulnerability so that they do not harm their future prospect (Imarticus Learning Inc., 2018).

Findings

The FinTech services are perceived to be convenient, user friendly, spending analyzer, and quick. FinTech reduces cost of transactions and the risk of handling cash. Older generation respondents (age group 50 years and above) perceived that the use of such services is complicated; also the respondents belonging to this age category believe that the FinTech services are unsecured. In addition, 29.8 percent of the respondents with educational qualification below or till HSLC find that the technology-based financial services are complicated as compared with 2.4 and 8.2 percent of postgraduates and graduates. It is observed from the study that the older generation has a misconception toward the FinTech services which is the principal reason for lack of trust and use of FinTech services. Another important factor which hinders the adoption of such services is lack of education. Thus, it is found from the study that respondents belonging to generation Y and generation Z mostly use and have positive attitude toward the technology-based services while baby boomers and generation X are trying to embrace FinTech services rather than being dependent on traditional modes of transactions but the ratio is significantly lower as compared with the younger generations.

Gender gap is observed in the use of FinTech services which is biased among males. It is found that 43.1 percent females have never used FinTech services against 16.8 percent males (see Table 3); also so far frequency of usage is concerned and similar trend is observed. In addition, businessmen, professionals, and service holders are regular users of FinTech services as compared with agriculturists and housewives. However, it is also found from the study that the retired persons are skeptical toward the adoption of FinTech services and prefer visiting bank branches. Also, while considering the age of the respondents, the adoption of such services is found more among the respondents belonging to up to 39 years of age, average among the respondents belonging to the age group 40–50 years, and low among the respondents belonging to the age category above 51 years. Thus, it is the natural association with technology and gadgets among the youth which prompts them to use FinTech services. Apart from this, lack of trust and awareness and association with technology hinder the older generation people to adopt technology-based services. The people above 50 years have used and experienced the manual financial transactions most of the time, fast change in the mode of transactions drive them out of their comfort zone which is why they do not want to indulge in FinTech. But digital payment has become a part of the game hence there is no choice but to adopt sooner or later.

The use of digital payments in the area of the study is increasingly replacing the traditional modes of payment. However, it is also observed that the respondents belonging to the marginalized sections use debit cards only to withdraw money from Business Correspondents’ outlet and cash is still influencing the payment of fees both in government and private schools in the area of the study. Although the payment-based FinTech services have received tremendous adoption in the area of the study but this is not the case with the FinTech firms working in the lending space. The sellers of those services should conduct literacy program to make people aware about such services and improve usage.

The highest difficulties faced by the respondents while using FinTech services are problem in the server, lack of technical knowhow while using the technology-based services, and also low security such as receiving fraud calls and messages. Regular monitoring of transactions can lessen the cyber vulnerability and also adequate systems should be put in place to reduce server problem.

It is also found from the study that psychological barrier, lack of confidence in the system, and inhibition in virtual transactions among the less educated and also the respondents belonging to older generation have an impact on the adoption of FinTech services.

Suggestions

The use of FinTech services is found more among the younger generation, thus new space should be provided to them to promote better and efficient use of such services. The awareness and use of FinTech services is very low among the bank customers belonging to older generation, housewives, and agriculturists and the reason for low use is unawareness and misconception. Thus, steps should be taken to improve the awareness and discern the customers that such services are dependable because there is no choice and the adoption of technology is inevitable. The banks conduct financial literacy camps where the people are taught about the benefits of opening bank accounts but such program have not been able to bring overall empowerment among the people. Thus, the banks along with the major FinTech firms, local nongovernmental organizations (NGOs), and microfinance institutions (MFIs) should try to conduct literacy program to educate people regarding the benefits of using technology-based financial services, conduct investor education camp, and also reduce the misconception among the customers regarding the FinTech services. The banks with additional remuneration to Business Correspondents can educate the rural customers regarding the benefit of using FinTech services. In addition, financial literacy kiosks may be set up at different places under the jurisdiction of bank branches and alongside the Automated Teller Machines with user-friendly software in vernacular languages, volunteers may be engaged in the local area to help the people navigating the kiosks. Also in this milieu, requisite steps should be taken to mitigate the problem of poor speed of internet and appropriate softwares should be developed to avert hacking.

Conclusion

With the smartphone penetration and outpouring of technological innovations, the bank customers have espoused to various FinTech services. The traditional cash-driven economy is now moving toward cashless and paperless mode of transactions. Consistent with the research results of Carlin, Olafsson, and Pagel (2017), it is found that the benefits of FinTech service is enjoyed more by the younger generation as compared with the baby boomers. Hence, it will be salient to improve awareness so that there is acceleration in the usage of FinTech services as it will reduce the cost of financial services and help in providing access even in the remote areas of the country. The usage of the services offered by the FinTech firms will rise only when the awareness level improves and it is pivotal for the lending-based FinTech companies to expand their services in the northeastern region of India because although the payment-based financial services are used by substantial number of customers the lending and insurance-based FinTech services are not experiencing significant extension in the area of the study. It is also consistent with the results of Hu, Ding, Li, Chen, and Yang (2019) that the users’ attitude toward FinTech services depends on their trust regarding such services. Consequently, the security should be strengthened so that the users have positive attitudes toward using such services and the users should also be careful while using the FinTech services in order to safeguard themselves from cyber threats. In summary, proper knowledge, government support, proper grievance mechanism can create positive attitude toward adoption of technology-based financial services. FinTech will ensure financial inclusion that will result in bringing the unbanked to the banking sector. This will make the formal financial system robust and will help to channelize the resources untapped so far toward the economic growth of the country.

Footnotes

Declaration of Conflicting Interest

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

References

Brown

(2010). ANR program evaluation, Iowa State University extension . Retrieved from http://www.extension.iastate.edu/Documents/ANR/LikertScaleExamplesforSurveys.pdf

Carlin

Olafsson

Pagel

(2017). FinTech adoption across generationss: Financial fitness in the information age . National Bureau of Economic Research. Retrieved from https://www.nber.org/papers/w23798.pdf

EY. (2019). Global FinTech Adoption Index . Retrieved from assets.ey.com/content/dam/ey-com/en_gl/topics/banking-and-capital-markets/ey-global-FinTech-adoption-index.pdf

Hetankar

(2018). ICICI banks’ digital push: Sets up innovation lab, enters FinTech tie-ups . Retrieved from https://www.business-standard.com/article/finance/icici-bank-s-digital-push-sets-up-innovation-lab-enters-FinTech-tie-ups-118052500580_1.html

Ding

Chen

Yang

(2019). Adoption intention of FinTech services for bank users: An empirical examination with an extended technology acceptance model. MDPI , 1–16. doi: 10.3320/sym 11030340

Imarticus Learning Inc. (2018). Challenges FinTech companies face while expanding to rural India . Retrieved from https://imarticus.org/challenges-FinTech-companies-face-while-expanding-to-rural-india/

Kostoulas

(2013). On Likert scales, ordinal data and mean values . Retrieved from https://achilleaskostoulas.com/2013/02/13/on-likert-scales-ordinal-data-and-mean-values

Mcanley

Weiner

(2015). The millenial generation and the future of finance. InnoTribe . Retrieved from https://innotribe.com/wp-content/uploads/2015/06/Millenials-and-Future-of-Finance_white-paper_Final.pdf

PwC Startupbootcamp. (2017). FinTech trends report 2017 . Retrieved from https://www.pwc.in/assets/pdfs/publications/2017/FinTech-india-report-2017.pdf

10.

Reserve Bank of India. (2017). Report of the working group on FinTech and digital banking . Retrieved from https://rbidocs.org.in/rdocs/PublicationReport/Pdfs/WGFR68AA1890D7334D8F8F72CC2399A27F4A.PDF

11.

Reserve Bank of India. (2018). Region-wise number of functioning offices of Commercial Banks at the end of Quarter . Retrieved from https://dbie.rbi.org.in/DBIE/dbie.rbi?site=publications#!17

12.

State Level Bankers’ Committee. (2019). District wise branch and ATM report of Assam in the year 2019 and quarter 3 . Retrieved from http://onlineslbcne.nic.in/distbranchManager.php

13.

Vally

K. S.

Divya

K. H.

(2018). A study on digital payments in India with perspective of consumers adoption. International Journal of Pure and Applied Mathematics , 118(24), 1–9.