Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 939 https://internationalpubls.com An Evaluative Study on Internet Banking usage among Middle Age and Youngsters Ms. Karmjeet Kaur1, Dr. Sahil Bhalla2 1A Research Scholar (Commerce) CT University, Ludhiana, India E-Mail : karamjitkaurrakhra@gmail.com 2Assistant Professor CT University, Ludhiana, India E-Mail : drsahil24158@ctuniversity.in@gmail.com Article History: Received: 12-12-2024 Revised: 25-01-2025 Accepted: 05-02-2025 Abstract: Today’s era is of technology. Technology, especially the internet, has changed how people and businesses behave. Banking industry mostly depends on information technology (IT) to gather, process, and distribute data to all pertinent clients. The way banks operate, deliver, and compete with one another is revolutionized by the smart use of Internet technology. These technological and operational changes have an effect on different age group population Banking, groups, and individuals must comprehend these effects on different age group population in order to effectively conduct e-banking. The purpose of this study is to analyze the socio - economic profile of internet banking user of middle aged (41-65 years of age) and youngster (21-40 years of age). The sample size is 500. Self made questionnaire is used in this research to collect first hand information from the internet banking services users. Purposive and convenient sampling strategies were used to choose the sample. Four locations were chosen to include both urban and rural settings. The data has been gathered through interviews and questionnaires. The statistical techniques like frequency, mean, and chi-square etc. are used for analysis. The finding of the study reveals that middle age users use internet banking services for different activities as compared to youngsters. Convenience, Knowledge and Support, trust and security are the major reasons for using Internet Banking by the users, while the non-users mentioned unawareness, in convenience and security concerns as reasons for not using. Keywords: internet banking, technology, customer satisfaction and risk INTRODUCTION Every facet of contemporary society has been impacted by technology in recent decades, and people's daily lives are increasingly including the usage of many technologies. Many services and resources are now only available through digital methods due to the ongoing technical advancement that has resulted from this. It also affects financial services market.( Raza, S. A., Jawaid, S. T., & Hassan, A. 2015) Banking operations have changed from a traditional system to an electronic banking (e-banking) system due to the growing growth of digital technology, especially the usage of the Internet for commercial transactions (Tasmin. R, Aliyu, A. A. and Takala, J. (2012). The practice of conducting financial transactions using an automated information system, either with mailto:karamjitkaurrakhra@gmail.com mailto:drsahil24158@ctuniversity.in@gmail.com Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 940 https://internationalpubls.com or without bank customers physically present at bank branches or specified sites, is known as e- banking/ internet banking. Banking channels and other financial technology are made available to consumers at their convenience through e-banking, which eliminates the need for them to physically visit the bank's location. These days, bank users can use e-banking to do almost all banking tasks, including money transfers, online payments for goods and services, bills, bank statement enquiries, phone voucher top-ups, and many more.( Rammaiya, V. and Prakash, G. 2019). A common form of e-banking is internet banking, which is made possible by the ease of using an online account. Internet banking refers to the process of conducting financial transactions via an automated information system, either with or without the actual presence of bank customers at designated locations or bank premises. Internet banking eliminates the requirement for clients to physically visit the bank's location and provides financial technologies (banking channels) at their leisure. ( Almaiah, M.A. et.al.2022) OBJECTIVE To analyze socio economic profile of middle age and young users. LITERATURE REVIEW Suh and Han. (2002) revealed that trust is one of the fundamental presumptions affecting a customer's attitude towards using Internet banking. The TAM proposed that attitude was significantly influenced by customer views of usefulness and usability. The behavioural desire to use Internet banking was highly connected with attitude, perceived utility, and trust. Customers rely on trust in online environments that manage sensitive data, according to these results. Pfeil, at al. (2009) provided fascinating insights into the characteristics and age-related differences of MySpace users, as well as the different ways in which these two user groups build and maintain social capital in this setting. Comparing samples of older and teenage users, we found some significant findings as well as differences between the two groups. Because this process was automated, we were able to collect data from a sizable sample of user profiles. Kaur, Navpreet et.al. (April 2015) examined that online banking solutions allow clients to reach a larger audience. Feedback is readily available on the internet due of its virtual nature. It is possible to win over customers' loyalty. The bank offers its clients both individualised attention and first-rate service. Excellent customer service, a larger audience, time-saving client loyalty, easy access to information, 24/7 availability, less paperwork, the elimination of cash transactions, straightforward online applications, and more are just a few of the many advantages of using an online banking system that we learnt about. Balakrishnan and Bharthvajan R.(2020) concluded that overall, e-banking has made our lives simpler and more comfortable while enabling us to affordably access premium services. We found it to be quite comfortable to use on a daily basis. It also yielded time-saving and efficient methods. The Internet was also the least expensive way to supply banking products because it allowed the organisation to reduce branch networks and service personnel. The Internet has broadened banks' horizons and enabled them to transcend national and global borders. Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 941 https://internationalpubls.com SAMPLING AND METHODOLOGY The sample size is 500. Self made questionnaire is used in this research to collect first hand information from the internet banking services users. Purposive and convenient sampling strategies were used to choose the sample. Four locations were chosen to include both urban and rural settings. The data has been gathered through interviews and questionnaires. ANALYSIS AND INTERPRETATION The statistical techniques like mean, correlation and Chi- square etc. are used for analysis. Table1: Demographic characteristics of the youngsters user and Middle- age user Youngsters user (n=250) Middle-aged user (n=250) Total (n=500) Freq. Percent Freq. Percent Freq. Percent Gender Male 122 48.8 124 49.6 246 49.2 Female 128 51.2 126 50.4 254 50.8 Education levels Matric 27 10.8 40 16.0 67 26.8 Higher Secondary 68 27.2 81 32.4 149 59.6 Graduate 108 43.2 66 26.4 174 69.6 Postgraduate 47 18.8 63 25.2 110 44.0 Residence Amritsar 63 25.2 63 25.2 126 25.2 Ludhiana 62 24.8 62 24.8 124 24.8 Firozpur 63 25.2 62 24.8 125 25.0 Mansa 62 24.8 63 25.2 125 25.0 Occupation levels Govt. Employee 45 18.0 38 15.2 83 16.6 Private Employee 34 13.6 53 21.2 87 17.4 Business 20 8.0 83 33.2 103 20.6 Student 126 50.4 24 9.6 150 30.0 Housewife 20 8.0 38 15.2 58 11.6 Any Other 5 2.0 14 5.6 19 3.8 Income levels less than 25,000 51 20.4 55 22.0 106 21.2 25,000 - 40,000 58 23.2 73 29.2 131 26.2 40,000 - 60,000 34 13.6 48 19.2 82 16.4 Above 60,000 15 6.0 45 18.0 60 12.0 None 92 36.8 29 11.6 121 24.2 Table 1 represents the characteristics of youngsters user and Middle- aged user who used internet banking. The distribution of Gender: The result shows that majority of females (50.8%) compared to males (49.2%) among all youngsters user and Middle- aged users who used internet baking. Further, it has been seen that the in younger Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 942 https://internationalpubls.com users, there is a slightly higher percentage of females (51.2%) compared to males (48.8%). However, in the middle-aged user group, females make up the majority (51.2%) compared to males (48.8%). The distribution of male and female between youngsters user and Middle- aged user who used internet banking is shown in Figure 1 The distribution based on education level: Majorities of user were graduate (69.6%) followed by higher secondary (59.6%), postgraduate (44.0%) and few users were matric (26.8%) respectively. In youngsters user, education levels were as graduate (43.2%) followed by higher secondary (27.2%), postgraduate (18.8%) and few users were matric (18.8%) respectively. In middle aged user majorities of respondent were higher secondary (32.4%) followed by graduate (26.4%), postgraduate (25.4%) and few users were matric(16.0%) respectively. The distribution of levels of education among user is shown in Figure 2. Figure 2: The distribution of education level among youngsters user and Middle- age user The distribution based on residence : Equal sample with 25 percent each Youngsters user and Middle- aged user taken from each Amritsar, Ludhiana, Firozpur and Mansa districts. 48.8% 49.6% 51.2% 50.4% 47.5% 48.0% 48.5% 49.0% 49.5% 50.0% 50.5% 51.0% 51.5% Youngsters user Middle-aged user Male Female 10.8 27.2 43.2 18.816 32.4 26.4 25.2 0 20 40 60 80 100 Matric Higher Secondary Graduate Postgraduate Youngsters user Middle-aged user Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 943 https://internationalpubls.com Fig. 3 : represents the distribution on the basis of residence. The distribution based on Occupation: The majorities of user were students (30%) followed by Business (20.6%), private employee (17.4%), govt. employee (16.6%) and few were housewife (11.6%) and 3.8 % user have any other type job respectively. Among youngster users, the majority were students (50.4%) followed by govt. employee (18.8%), private employees (13.6%), Business(8%), Housewife(8%) and very few have other type job (2.0%) respectively, Where in middle-aged user, occupation were Business (33.2%), private employees (21.2%), govt. employee (15.2%), Housewife(15.2%), students(9.6%) and very few have other type job (5.6%) respectively. The distribution of levels of occupation among user is shown in Figure 4. Figure 4: Distribution of Occupation The distribution based on Income level: Out of total user, 24.2 % do not have income either students or may be staying at home, where 26.2% user have income level Rs.25000-40000, 21.2% have less than Rs 25000, 16.5% user have income 25 25 25 2525 25 25 25 0 5 10 15 20 25 Amritsar Ludhiana Firozpur Mansa Youngsters user Middle-aged user 18 13.6 8 50.4 8 2 15.2 21.2 33.2 9.6 15.2 5.6 0 10 20 30 40 50 60 Govt. Employee Private Employee Business Student Housewife Any Other Youngsters user Middle-aged user Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 944 https://internationalpubls.com level Rs.40000-60000, and 12% user have income Rs 60000 and above respectively. Youngsters user showing income level as less than Rs.25000 (20.4%), Rs.25000-40000 (23.2%), Rs.40000-60000 (13.6%), Rs. 60000 and above (6.0%) and 36.8% user do not have income and where middle-aged user showing income level as less than Rs.25000 (22.0%), Rs.25000-40000 (29.2%), Rs.40000- 60000 (19.2%), Rs. 60000 and above (18.0%) and 11.6% user do not have income. Proportion of income among youngsters and middle-aged user is shown in Figure 5. Figure5: Proportion of income level among youngsters and middle-aged user INTERPRETATION The interpretation of analyzed data is as follow Table 2: The association of characteristics between youngsters user and Middle- aged user Youngsters user (n=250) Middle- aged user (n=250) Chi- square value Df p- value Freq. Percent Freq. Percent Gender Male 122 48.8 124 49.6 0.03 1 0.86 Female 128 51.2 126 50.4 Education Matric 27 10.8 40 16.0 16.1 0.00** Higher Secondary 68 27.2 81 32.4 3 Graduate 108 43.2 66 26.4 Postgraduate 47 18.8 63 25.2 Residence Amritsar 63 25.2 63 25.2 0.02 3 0.99 Ludhiana 62 24.8 62 24.8 Firozpur 63 25.2 62 24.8 36.80% 20.40% 23.20% 13.60% 6% 11.60% 22% 29.20% 19.20% 18% 0% 5% 10% 15% 20% 25% 30% 35% 40% Nil < Rs.25,000 Rs.25,000 - 40,000 Rs.40,000 - 60,000 >Rs. 60,000 Youngsters user Middle-aged user Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 945 https://internationalpubls.com Mansa 62 24.8 63 25.2 Occupation Govt. Employee 45 18.0 38 15.2 122.5 5 0.00** Private Employee 34 13.6 53 21.2 Business 20 8.0 83 33.2 Student 126 50.4 24 9.6 Housewife 20 8.0 38 15.2 Any Other 5 2.0 14 5.6 Income less than 25,000 51 20.4 55 22.0 52.1 4 0.00** 25,000 - 40,000 58 23.2 73 29.2 40,000 - 60,000 34 13.6 48 19.2 Above 60,000 15 6.0 45 18.0 None 92 36.8 29 11.6 **p<0.01 Table 2 represents the association of various demographic characteristics between youngster users and middle-aged users, Association between Youngsters and Middle-aged users on the basis of gender Among younger users, 51.2% were female and 48.8% were males, whereas for middle-aged users, 50.4% were female and 49.6% were male. The Chi-square values (=0.03,p>0.05) showed a value that there is non -significant association between distribution of gender and users. Association between Youngsters and Middle-aged users on the basis of education level Among youngster user, majorities of user were graduate with 43.5% graduate, postgraduate with 18.8%, higher secondary with 27.2 % and 10.8% had matric-level education. Among middle-aged user, majorities of user were higher secondary with 32.4 %, graduate with 26.4%, postgraduate with 25.2%, and 16.0% had matric-level education. The Chi-square values (=16.1,p<0.01) showed a value that there is significant association between distribution of education levels and users. From above discussion we concluded that the education level showed a significant association between youngsters and middle-aged users. Association between Youngsters and Middle-aged users on the basis of residence The distribution of youngster as well as middle-aged users across cities (Amritsar, Ludhiana, Firozpur, and Mansa) was nearly with equal number, with each city contributing approximately 25% of users in both groups. The Chi-square values (=0.02, p>0.05) showed a value that there is non- significant association between residence and users. Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 946 https://internationalpubls.com Association between Youngsters and Middle-aged users on the basis of occupation Among younger users, majorities 50.4% were students, 18.0% were government employees, 13.6% were private employees, 8.0% were in business or housewives, and 2.0% users showed other occupations. In middle-aged users, 33.2% were in business, 21.2% were private employees, 15.2% were government employees or housewives, 9.6% were students, and 5.6% reports other occupations. The Chi-square value was (=122.5 with a p-value < 0.01) showed a value that there is significant association between distribution of occupation levels and users. The above discussion showed that there is significant association between occupation and age group. Younger users are primarily students, whereas middle-aged users are more likely to be in business or private employment. Association between Youngsters and Middle-aged users on the basis of income level Among youngster user, most of user were student, majority 36.8% do not have any income, 23.2% have income between Rs.25,000 -40,000, 13.6% user have income Rs.40,000-60,000, 20.4 % user have income less that Rs, 25000 and whereas 6% user have income more than Rs,65,000. Among middle-aged user, majority 29.8% user have income between Rs.25,000 -40,000, 19.2% user have income Rs.40,000-60,000, 22 % user have income less that Rs, 25000, 11.6% user have income more than Rs,65,000 and 11,6 user do not income. The Chi-square value was (=52.1, p-value < 0.01) showed a value that there is significant association between distribution of income levels and users. From above discussion it has been seen that the youngsters users are more likely to have no income, may be most of user were student, middle-aged users are more likely to have higher incomes, with a more percentage of earning above 40,000, especially above 60,000. CONCLUSION This study highlights the growing adoption of internet banking among both youngsters and middle- aged individuals, driven largely by advancements in digital technology and increasing financial literacy. The findings reveal that socio-economic factors such as income level, educational background, and occupation significantly influence the usage of internet banking. Young people are comfortable with technology and like to use their phones for banking because it's easy and fast. Middle-aged people are more careful, but they are also using online banking more. They like it because it's safe and offers many services. The study reveals that there is no difference in the usage of internet banking among male and female. Both take the benefits of internet banking services. The study also underscores the role of income and education in shaping banking behavior. Higher income groups and individuals with better educational qualifications are more inclined to utilize internet banking, as they have greater access to technology and a deeper understanding of its benefits. However, barriers such as lack of trust, concerns about cyber security, and limited digital literacy among lower-income groups persist, indicating the need for targeted awareness campaigns and user- friendly platforms. Overall, the research emphasizes the importance of bridging the digital divide and tailoring internet banking services to meet the diverse needs of different socio-economic groups, ensuring financial inclusion and wider adoption in the future. Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. ICMASD (2025) 947 https://internationalpubls.com REFERENCES [1] Ahmad,M.(2018). Review of The Technology Acceptance Model (TAM) in Internet banking and Mobile banking, International Journal of Information Communication Technology and Digital Convergence,3(1),23-41. [2] Alam, S. S. Bakar, Z., Ismail, H. B., Ahsan, N., (2008).Young consumers online shopping: an empirical study, Journal of Internet Business, 5, 81-98. [3] Almaiah, M.A., Al-Rahmi,A.M., Alturise,F., Alrawad,M. Salem Alkhalaf,S., Lutfi,A. Al- Rahmi,W.M. and Awad,A.B. (2022). Factors influencing the adoption of internet banking: An integration of ISSM and UTAUT with price value and perceived risk, Frontiers in Psychology,13, 1-19. [4] Asif, S. (2021). Study Of Internet Banking Usage: Elderly Vs Youth, Ilkogretim Online - Elementary Education Online,20(6), 3086-3101. [5] Balakrishnan and Bharthvajan R.(2020). The impact of E-Banking services in India, Malaya Journal of Matematik, 2, 3286-3288 [6] Dollinger, S.J. and Dollinge, S.M.C.(2003) Individuality in Young and Middle Adulthood: An Autophotographic Study, Journal of Adult Development,Vol. 10, No. 4, 227-236. [7] Funmilola, O. O. & Tolulope A. A.,(2020). Digital Inclusion and the Elderly: The Case of Internet Banking Use and Non-Use among older Adults in Ekiti State, Nigeria, Covenant Journal of Business & Social Sciences (CJBSS), 11(1) 20-47. [8] Kaur,N., Pathak, A., Kaur,P.(2015). Online Banking on E-Commerce in India, International Journal of Engineering Research and Applications,5(4), 39-49. [9] Khan, M. S., Mahapatra, S. S. and Sreekumar, N. (2009). Service quality evaluation in internet banking: an empirical study in India, International Journal Indian Culture and Business Management,2(1) , 30-46. [10] Lee E. J., Kwon K. N, and Schumann, D.W. (2005) Segmenting the non-adopter category in the diffusion of internet banking, International Journal of Bank Marketing, 23(5):414-437. [11] Pfeil, U., Arjan, R.,Zaphiris,P.,(2009).Age differences in online social networking – A study of user profiles and the social capital divide among teenagers and older users in MySpace, Elsevier,25(3),643-654. [12] Rammaiya, V. and Prakash, G.(2019). Kap study of e-banking in indore, Amity Journal of Management Amity Business School, 7(1), 13-21. [13] Raza, S. A., Jawaid, S. T., & Hassan, A. (2015). Internet banking and customer satisfaction in Pakistan. Qualitative Research in Financial Markets, 7(1), 24–36. [14] Tasmin. R, Aliyu, A. A. and Takala, J. (2012) A Review of the Influence of Electronic Banking Services on Customer Service Delivery: Successes and Challenges, Australian Journal of Basic and Applied Sciences 6(13): 80-85. [15] Suh ,B. and Han, I., (2002).Effect Of Trust On Customer Acceptance Of Internet Banking ,Electronic Commerce Research And Application,1(3),247-263. https://www.researchgate.net/profile/Eun-Ju-Lee-4?_tp=eyJjb250ZXh0Ijp7ImZpcnN0UGFnZSI6InB1YmxpY2F0aW9uIiwicGFnZSI6InB1YmxpY2F0aW9uIn19 https://www.researchgate.net/scientific-contributions/Kyoung-Nan-Kwon-2196461451 https://www.researchgate.net/profile/David-Schumann-2 https://www.researchgate.net/journal/International-Journal-of-Bank-Marketing-0265-2323