Financial inclusion has emerged as the main determinants of inclusive economic development, social equality and wellbeing of entire population. It describes the accessibility, availability, and efficient use of formal financial services such credit facilities, savings accounts, digital payment methods, insurance, and investment opportunities. Financial inclusion is essential for lowering income inequality, improving household stability, and promoting sustainable livelihoods in developing economies. Disparities in financial access and usage between demographic groups persist despite notable advancements in digital finance and banking infrastructure expansion. A main component of enhancing financial inclusion is financial literacy. It gives people the capacity to comprehend financial goods, assess risks, control income and expenses, and make sound financial decisions. Access to financial services alone might not result in significant inclusion if one has sufficient financial literacy. Due to a lack of confidence or information, people may underuse the services that are provided, become caught in debt traps, or completely avoid official institutions.

Digital financial services like credit cards and UPI systems have revolutionized financial transactions in recent years, especially in rural and semi-urban areas. Although these services are quick, easy, and transparent, their efficient use is mostly dependent on behavioral, literacy, and trust characteristics. Financial behavior is greatly influenced by demographic factors like age, gender, income, education, and occupation. Differences in spending patterns, investment preferences, debt management, and saving habits frequently reveal underlying socioeconomic and demographic factors. The degree of financial inclusion is also influenced by investing and savings practices. Investment diversification is still lacking, particularly among lower and middle-class individuals, notwithstanding the continued dominance of traditional savings instruments. Long-term wealth building and retirement planning are frequently subordinated to short-term financial needs. Furthermore, financial decisions are heavily influenced by household duties and economic instability, underlining the necessity of focused financial education and governmental support. Designing successful treatments requires an understanding of how financial literacy, demographic characteristics, and financial inclusion interact. An empirical evaluation of these connections reveals gaps and areas for development. A special emphasis on demographics, financial literacy regarding credit cards and digital payments, investment and savings strategies, and their combined impact on financial inclusion, this study aims to investigate these variables holistically.

STATEMENT OF THE PROBLEM

Even while formal financial institutions and digital payment technologies have been more widely used, a sizable portion of the population is still not fully integrated into the financial system. Access to banking services alone does not guarantee efficient use or sound financial standing. Meaningful financial inclusion is nevertheless hampered by disparities in demographics, low financial literacy, bad credit management, and insufficient knowledge of savings and investments. Many people rely on unofficial sources of financial information, which can result in poor financial choices, excessive debt, or avoidance of official credit and investment opportunities. Furthermore, new issues with awareness, security, and responsible use have emerged as a result of the quick growth of digital finance. These problems highlight the necessity of investigating the combined effects of financial literacy and demographic determinants on financial inclusion. Addressing this problem is essential for ensuring that financial services contribute to economic security and long-term development.

NEED FOR THE STUDY

The necessity stems from the increasing significance of financial inclusion in attaining social development and economic stability. Even while financial services are now more widely available, their efficient usage is constrained by differences in financial literacy and demographics. Improving inclusion results requires an understanding of how people learn about money, handle credit, and make investments and savings. The study aids in identifying behavioral obstacles, demographic factors, and awareness gaps that impact financial involvement. The outcomes can help educators, financial institutions, and legislators create inclusive financial products and focused financial literacy initiatives. In order to encourage prudent financial conduct, the study also emphasizes the significance of organized financial education and demographic-sensitive tactics. These kinds of information are crucial for guaranteeing fair access to financial opportunities and bolstering household financial resilience.

REVIEW OF LITERATURE

Financial inclusion is a multifaceted notion that is impacted by behavioral variables, financial competence, and access to financial services (Jain et al., 2020). The ability of people to properly use banking services, digital payments, credit facilities, and investment opportunities is significantly influenced by their level of financial literacy (Garu and Dash, 2023). Greater engagement in formal financial systems, better credit management, and better saving habits are all linked to higher literacy levels (Long et al., 2023). Financial behavior is significantly impacted by demographic factors. Financial awareness and decision-making ability are significantly influenced by age and education (Akinyemi and Mushunje, 2020). While elderly populations frequently rely on traditional financial practices, younger and better educated people are more likely to accept digital financial services (Fanta and Mutsonziwa, 2021). There is ample evidence of gender-based disparities that impact inclusion outcomes through differences in risk tolerance, loan utilization, and income control (Reddy et al., 2025). Occupational status further determines income stability and access to formal financial products (Morgan and Long, 2020).

Digital payment channels render a vital role in promoting financial inclusion, especially in underprivileged areas. However, awareness, trust, and usability are necessary for successful adoption (Al-Smadi, 2023). The importance of informal learning channels is demonstrated by the fact that social networks are frequently the main providers of financial knowledge, particularly for women (Saputra et al., 2023). High interest rates and excessive spending have been recognized as the main issues with credit card usage, which has been studied as a possible risk factor as well as an indicator of financial sophistication (Alnemer, 2022). The majority of people still save and invest conservatively, favoring tangible, low-risk assets. Retirement planning and long-term wealth accumulation are given less consideration than short-term financial objectives (Mukhopadhyay, 2016). Savings capacity and investment decisions are often influenced by household responsibilities and the state of the economy (Singh, 2021). Training in financial literacy has a favorable effect that promotes financial inclusion among various demographic groups (Yangdol and Sarma, 2019). Structured training programs boost self-assurance, facilitate better financial decision-making, and promote interaction with official financial institutions (Nandru and Rentala, 2019). Attaining significant and long-lasting financial inclusion requires improving financial literacy while taking demographic diversity into consideration (Ho et al., 2020).

RESEARCH OBJECTIVES

The study is formulated with the following objectives.

1. To examine the demographic profile of respondents and its influence on financial behavior.
2. To assess the level of financial literacy related to digital payments and credit card usage.
3. To analyze savings and investment patterns as indicators of financial inclusion.
4. To evaluate the effect of financial literacy on financial inclusion.
5. To observe the role of financial literacy training in improving financial inclusion.
6. To determine the impact of demographic and financial factors on financial inclusion.

RESEARCH METHODOLOGY

The study implements descriptive and analytical research design to assess the effect of financial literacy on financial inclusion. Primary data are collected from respondents using a structured questionnaire covering demographic characteristics, income and expenditure patterns, savings and investment behavior, digital payment usage, and credit card practices. The sample includes 180 deprived persons engaged in agriculture, industry, and service sectors. The questionnaire is designed to capture multiple dimensions of financial literacy and inclusion, ensuring clarity and relevance to the study objectives. Secondary data are gathered from reports, journals, and policy documents to support conceptual understanding. Statistical techniques are employed for analysis. Percentage analysis is used to describe demographic and financial characteristics. One-Way ANOVA tested differences between financially literacy and non-literacy respondents. Pearson correlation examined the relationship between financial literacy training and financial inclusion. Regression and t-test analyses assessed the influence of demographic and financial variables on inclusion. These methods ensured reliable and valid interpretation of results.

RESULTS AND DISCUSSION

Demographic Characteristics of Respondents

The demography status of respondents is analyzed, and its results are depicted in Table 1.

Table 1: Analysis of Demographic Characteristics

Source: Field Survey                                                              Figures in Parentheses denote percentages

Table 1 presents that among 103 (57.2%) males and 77 (42.8%) females age distribution, the largest group falls within the 40-50 years, accounting for 31.1%. Males represent 35%, while females constitute 26%. The 30-40 age group follows closely with 28.9%; it consists of 36.4% of female 23.3% of male. Notably, individuals aged 60 and above make up 15%, with males at 17.5% and females at 11.7%. The educational qualification shows that among males, 38 are illiterate (36.9%), 32 have a primary education level (31.1%), 11 have a secondary education level (10.7%), and 22 have a higher secondary education level (21.4%). Among females, 19 are illiterate (24.7%), 28 have a primary education level (36.4%), 22 have a secondary education level (28.6%), and 8 have a higher secondary education level (10.4%).  The marital status distribution shows that among males, 79 are married (76.7%), 6 are unmarried (5.8%), and 18 are widowed (17.5%). Among females, 57 are married (74%), 2 are unmarried (2.6%), and 18 are widowed (23.4%). The main occupation reveals that among males, 25 work in the agricultural sector (24.3%), 72 in the industrial sector (69.9%), and 6 in the service sector (5.8%). Among females, 17 are in the agricultural sector (22.1%), 58 in the industrial sector (75.3%), and 2 in the service sector (2.6%).

The household monthly income reveals that notable 39.8% of males and 19.5% of females report monthly incomes between Rs.10,000 and Rs.15,000, while the Rs.15,000 to Rs.20,000 bracket sees 40.8% of males and 31.2% of females. The monthly income category of less than Rs.10,000 comprises 15.5% of males and 23.4% of females. Equally, a substantial 26% of females earn more than Rs.20,000, compared to only 3.9% of males. The monthly expenditure shows that 70.9% of males and 66.2% of females spend between Rs.10,000 and Rs.15,000. Additionally, 27.2% of males and 33.8% of female report expenditures exceeding Rs.15,000. Only a minimal 1.9% of males and none of the females spend less than Rs.10,000. Savings amounts according to month wise calculations in the study regions. A significant portion, 35% of males and 31.2% of females, save less than Rs.750. On the other hand, 28.2% of males and 54.5% of females save between Rs.750 and Rs.1,500, Notably, 36.9% of males have savings exceeding Rs.1,500, while only 14.3% of females. The loan amount shows that 53.4% of males and 40.3% of females, have loans amounting to less than Rs.100,000. Conversely, only 4.9% of males and 7.8% of females have loans in the range of Rs.100,000 to Rs.200,000. Notably, a substantial portion, 41.7% of males and 51.9% of females, report loans exceeding Rs.200,000.

FINANCIAL LITERACY ON CREDIT CARD

The financial literacy of respondents is analysed in different dimensions as per gender, it is furnished in Table 2.

Table 2: Financial Literacy on Credit Card

Source: Field Survey                                                             

FIGURES IN PARENTHESES DENOTE PERCENTAGES

Table 2 shows that the source of information to use UPI platforms, shows that among males, 51 learned about UPI through online platforms (49.5 percent), while 17 were influenced by media and newspapers (16.5 percent), and 35 learned from friends and relatives (34 percent). For females, 26 learned via online platforms (33.8 percent), 2 from media sources (2.6 percent), and a significant 49 learned from friends and relatives (63.6 percent). A substantial proportion of respondents (42.8 percent) acquired UPI skills through online resources, while a notable 46.7 percent learned from their social networks, particularly among females. Use of smart phones shows that 103 males (100 percent) and 77 females (100 percent) confirms its usage. The average transaction amounts through the UPI platform shows that 65 percent of males and 92.2 percent of females, conduct transactions of less than Rs.10,000. Then 35 percent of males and 7.8 percent of females’ report transactions exceeding Rs.10,000. Credit usage shows that among males, 65 individuals (63.1 percent) possess and use credit cards, whereas 38 males (36.9 percent) do not. In contrast, a significantly higher proportion of females utilize credit cards, with 70 women (90.9 percent) indicating active use, while only 7 females (9.1 percent) do not own one.

The credit card limit discloses that total of 38 males (36.9 percent) and 7 females (9.1 percent) do not hold credit cards, accounting for 25 percent. Among credit card holders, 14 males (13.6 percent) have limits up to Rs.50,000, while 19 females (24.7 percent) fall into the same category. For limits ranging from Rs.50,000 to Rs.60,000, 30 males (29.1 percent) and 13 females (16.9 percent) report this amount. Interestingly, 18 males (17.5 percent) and 18 females (23.4 percent) have limits between Rs.60,000 and Rs.70,000. Notably, 3 males (2.9 percent) and 20 females (26 percent) possess credit cards with limits exceeding Rs.70,000. The amount utilized on credit cards shows that 38 males (36.9 percent) and 7 females (9.1 percent), do not use credit cards, representing 25 percent of the total sample. 14 males (13.6 percent) and 19 females (24.7 percent) spend up to Rs.45,000. 33 males (32 percent) and 33 females (42.9 percent) utilize amounts between Rs.45,000 and Rs.60,000. Additionally, 18 males (17.5 percent) and 18 females (23.4 percent) report expenditures exceeding Rs.60,000. The perceived drawbacks of credit card usage reveal that 39 males (37.9 percent) and 2 females (2.6 percent) indicate that they perceive no drawbacks. The high rate of interest, noted by 27 males (26.2 percent) and 40 females (51.9 percent), amounting to 67 respondents (37.2 percent). Overspending (32 respondents or 17.8 percent), fraudulence (11 respondents or 6.1 percent), and high penalties, late fees, and surcharges (29 respondents or 16.1 percent).

Financial Inclusion through Savings and Investment

The financial inclusion of respondents through savings and investment is analyzed as per gender, it is furnished in Table 3.

Table 3: Financial Inclusion through Savings and Investment

Source: Field Survey                                                             

Figures in Parentheses denote percentages

Table 3 reveals that the types of savings accounts show that a significant majority, 115 respondents (63.9 percent), utilize regular savings accounts, with 67 males (65 percent) and 48 females (62.3 percent) opting for this traditional option. In contrast, 65 respondents (36.1 percent) have high interest savings accounts, consisting of 36 males (35 percent) and 29 females (37.7 percent). The various investment vehicles show that, 180 respondents participated, with 60 (33.3 percent) investing in real estate, marking it as the most favored option. The preference may stem from real estate’s perceived stability and potential for long-term appreciation. Precious metals follow closely, with 72 respondents (40 percent) opting for this investment, particularly among females, who constitute 49.4 percent of that group. Mutual funds attract 29 investors (16.1 percent), indicating moderate interest, while stocks account for 19 participants (10.6 percent), suggesting a more cautious approach to equity investments. The purposes of savings and investment shows that the most prevalent goal is short-term objectives, such as travel and other purchases, with 69 participants (38.3 percent) prioritizing this activity. Education funds are also significant, attracting 47 respondents (26.1 percent). Retirement planning and emergency funds follow, garnering 43 (23.9 percent) and 19 (10.6 percent) responses, respectively. Wealth accumulation is the least emphasized purpose, with only 2 respondents (1.1 percent) citing it, emphasizing a potential gap in understanding the importance of building wealth over time.

The periodical contributions to savings and investments shows that 107 participants (59.4 percent), contribute monthly. Quarterly contributions are noted by 42 respondents (23.3 percent), with a higher representation of females (36.4 percent) compared to males (13.6 percent). This pattern may reflect varying financial strategies or income patterns between genders. Annual contributions account for 29 respondents (16.1 percent), while only 2 respondents (1.1 percent) report irregular contributions. The factors influencing savings and investment contributions reveals that economic conditions emerged as the most significant factor, with 43.9 percent, slightly more prominent among females (46.8%) compared to males (41.7%). Family goals and obligations also played a notable role, particularly for males (36.9%) versus females (14.3%), indicating differing priorities. Education about investment opportunities was notably more important for females (26%) than for males (4.9%). The investment horizon preferences show that a significant 70 percent of participants, with a marked preference among males (77.7 percent) compared to females (59.7 percent). In contrast, only 17.2 percent opted for short-term investments, reflects a more cautious approach to immediate gains. Interestingly, long-term investments attracted only 12.8 percent of respondents, with a notable gender disparity: just 2.9 percent of males preferred this option versus 26 percent of females.

Effect of Financial Literacy on Financial Inclusion

The effect of financial literacy on financial inclusion is analyzed using One-Way ANOVA with (H₀) there is no significant difference exist between financial literacy and financial non-literacy respondents for financial inclusion. The results are portrayed in Table 4.

Table 4:  One-Way ANOVA

Source: Computed                                                                                                                    

Table 4 shows that sum of squares between groups (7.626) and the sum of squares within groups (532.796) indicate variations in financial literacy levels across the selected district. The F-value of 2.548 and the significant p-value of 0.000 demonstrate that the difference between groups is statistically significant. Therefore, there is significant difference exist between financial literacy and financial non-literacy respondents for financial inclusion. It shows that financial literacy indeed influences financial inclusion outcomes, as individuals with higher financial literacy are more likely to access and use financial services effectively.

7.5. Effect of Financial Literacy Training on Financial Inclusion

The effect of financial literacy on financial inclusion is analyzed using Pearson correlation with (H₀) there is no significant difference in financial literacy training attended and not attended respondents for financial inclusion. The results are portrayed in Table 5.

Table 5:  Pearson Correlation

Source: Computed                                                        ** Significant at 1%

Table 5 portraits the Pearson correlation coefficient of 0.921^** demonstrates a strong, statistically significant positive relationship between the two variables (p-value = 0.000). Therefore, there is significant difference in financial literacy training attended and not attended respondents for financial inclusion. It shows that individuals who undergo financial literacy training are significantly more likely to engage in formal financial activities, such as accessing banking services, saving in institutional channels, or utilizing credit and insurance products.

Effect of Demography on Financial Inclusion

The effect of financial literacy on financial inclusion is analyzed using t-test with (H₀) there is no significant difference in demography of respondents for financial inclusion. The results are portrayed in Table 6.

Table 6: Regression Analysis

Source: Computed                                                                                                                    ** Significant at 1%

Table 6 shows that results of the regression analysis provide strong evidence that many of these factors form both financial literacy and financial inclusion. The constant (-2.183, p = 0.002) suggests a baseline negative influence, implying that without the influence of other factors, financial inclusion may face challenges. However, various demographic factors strongly influence financial literacy and inclusion. For instance, age (-1.989, p = 0.005), education (-2.097, p = 0.011), and occupation (-0.928, p = 0.016) are statistically significant, reveals that as people grow older, attain higher education, and engage in formal occupations, their financial literacy and inclusion improve. Conversely, gender (-0.046, p = 0.000) shows that women or men may face distinct challenges or advantages in accessing financial knowledge and resources. Certain financial behaviors, such as the use of credit cards (-4.853, p = 0.000), rate of interest (-2.845, p = 0.000), and managing debt (-1.855, p = 0.001), significantly affect financial inclusion. The negative t-values for these variables indicate that individuals struggling with debt or high-interest rates are less likely to be financially included, while the use of credit cards may be a marker of financial sophistication, thus positively influencing inclusion.

The types of savings (0.388, p = 0.000) and investment (1.056, p = 0.000) are significant, which highlight the importance of savings and investments as tools for promoting financial inclusion. The positive t-values indicate that individuals with diversified savings and investment strategies are more likely to be financially included. Household development (2.667, p = 0.000) and household budgeting (1.056, p = 0.000) are also significant contributors. Interestingly, religion (-1.579, p = 0.172) did not show a significant impact. The overall model fit is very strong, as indicated by an R² value of 86.255% and an adjusted R² value of 85.893%, meaning that these factors explain a large proportion of the variance in financial literacy and inclusion. The F-ratio (167.241, p = 0.000) further demonstrates that the model is statistically significant, rejecting the null hypothesis and accepting the alternative hypothesis that there is significant difference in demography of respondents for financial inclusion. This is a clear indication that policy interventions aimed at improving financial inclusion must consider these specific factors particularly education, occupation, gender, debt management, and household financial behavior. Therefore, improving financial literacy remains essential for ensuring that individuals across all socio-economic backgrounds can access, understand, and use financial services to improve their economic wellbeing.

CONCLUSION

The study scrutinized the relationship between financial inclusion and financial literacy, emphasizing the crucial impact that financial behavior and demographic traits play. According to the demographic analysis, the majority of respondents are middle-aged, with somewhat more men than women. Gender variations in educational attainment are a direct reflection of disparities in credit utilization, savings practices, and financial understanding. Long-term financial planning is hampered by the majority of respondents’ modest income levels, as evidenced by their spending and income trends. Extensive smartphone uses and increasing familiarity with UPI platforms are evident in the financial literacy studies pertaining to digital payments and credit cards. Gender differences exist in the sources of knowledge, nevertheless, with women primarily relying on social networks and men more on online platforms. Females are far more likely to hold and use credit cards, which is indicative of their increased involvement with formal credit systems. However, high interest rates, excessive spending, and fines are seen as significant disadvantages, highlighting the need for increased awareness of credit management. Regular savings accounts and conventional investment outlets like real estate and precious metals are preferred in saves and investment behavior. Long-term wealth accumulation receives little attention while short-term financial objectives predominate, indicating a gap in strategic financial planning. Although family responsibilities and the state of the economy have a big impact on saving decisions, respondents’ monthly contribution patterns show financial discipline.

Financial inclusion is significantly impacted by financial literacy, according to inferential study. Higher literacy levels are associated with improved access to and use of financial services. The significance of organized educational programs is further supported by the substantial positive link between financial literacy instruction and financial inclusion. The results of the regression show that while religion has no discernible effect on inclusion, age, education, occupation, credit behavior, savings, investing strategies, and household financial management organize. The study comes to the conclusion that financial inclusion is strongly influenced by financial literacy, demographic traits, and responsible financial conduct rather than being exclusively driven by access to financial services. Enhancing inclusive growth requires boosting financial literacy, encouraging responsible credit use, and supporting a variety of investment and savings strategies. Targeted financial literacy programs that address demographic gaps and promote sustainable economic wellness across all societal segments must be the main focus of policy actions.

RESEARCH IMPLICATIONS

The research has important implications for schools, financial institutions, and legislators. Financial literacy has a major impact on financial inclusion, which emphasizes the necessity for ongoing, systematic financial education programs that are adapted to specific demographics. Strategies tailored to a person’s gender and career can enhance investment participation, savings discipline, and appropriate credit use. Concerns about interest rates, fines, and debt management can be addressed by financial institutions through the creation of straightforward and transparent products. Incorporation practical financial education into workplace and community activities can improve inclusion, as demonstrated by the significant impact of financial literacy training. In general, the research backs evidence-based strategies that increase financial capacity and encourage equitable economic engagement.

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