144 American Journal of Economic and Management Business e-ISSN: 2835-5199 Vol. 2 No. 4 April 2023 FINANCIAL INCLUSION POLICY AND PLANNED TRIBES IN MAYURBHANJ DISTRICT, ODISHA Rupak kumar Tung The Maharaja Sriram Chandra Bhanja Deo University (MSCB), India Email: tungrupakkumar@gmail.com Abstract The government's policy of opening bank branches in tribal areas and funding priority areas is very welcome. Facilities offered in these tribal areas include basic savings bank deposit account (BSBDA) and no-frills deposit account opening, making it easy for customers to know their requirements. Self-help group bank liaison programs are another way to increase the income of poor households by providing financial services through public institutions. Macro-level data analysis showed high scores in Chhattisgarh, Jharkhand, Rajasthan, Madhya Pradesh, Andhra Pradesh, Maharashtra, Orissa, Gujarat, Tamil Nadu and Karnataka. rice field. Financial inclusion is considered achieved. At the same time, it was low in Bihar, Harayana, Assam, Kerala, Punjab, West Bengal and Uttar Pradesh. Government programs such as the MGNREG program, microcredit facility, PMJDY, old age pension, SHG bank account, and Kisan credit card have had a significant impact on the economic status of the tribesmen in some villages in Mayurbhanj district. The majority of selected Indigenous households have bank accounts, and program rewards are paid through each program beneficiary's individual bank account. The gradual introduction of government and banking programs contributes significantly to the success of indigenous integration Keywords: financial inclusion policy, PMJDY, financial services, Tribes, FII, FIP This article is licensed under a Creative Commons Attribution-ShareAlike 4.0 International INTRODUCTION According to economic literature, "inclusive growth" refers to the equitable distribution of resources that benefits every segment of society. The achievement of the equality goal in growth is made possible by the participation of all societal segments and geographical areas in economic progress and in reaping its advantages (Dixit & Ghosh, 2013). Economic growth with equal opportunity for all is referred to as the inclusive growth concept. It simply entails generating possibilities for progress and making them available to everyone, especially the underprivileged (Ali & Zhuang, 2007). Since the inception of national plans, India has stressed the role of finance in encouraging equitable progress. The creation of rural cooperatives, Regional Rural Banks https://creativecommons.org/licenses/by-sa/4.0/ https://creativecommons.org/licenses/by-sa/4.0/ https://creativecommons.org/licenses/by-sa/4.0/ Rupak kumar Tung 145 (RRB), National Bank for Agriculture and Rural Development (NABARD), nationalisation of commercial banks, emphasis on social banking, rural credit, priority sector lending, Lead Bank Schemes, interest rate ceilings, subsidies, etc., are a few significant steps taken in this direction. Even now, after all of India's policy efforts to promote financial inclusion, official banking services still haven't reached a significant portion of households, and the poor and outcasts of society are still unable to access any financial services. Review of Literature: 1. Onta-Bhatta, (2000) The homeless and underprivileged are given access to economical meal services by street vendors. The availability of regional and local delicacies at these kiosks is another factor. The mechanics of the city's daily betting and the poor's food vending machine supply. Because it contributes to the availability of affordable food for the urban populace, urban street food survives. 2. Singh et al., (2020) The project will take steps to support community organisations technically, create business plans for providers to enter the market, and collect and disseminate best practises from throughout the nation. It details what you require. 3. Bhoi et al., (2022), examines how street vendors perceive digital payments and how they affect the success of their businesses. Data will be gathered for this purpose from Cuttak, Kurda, and Berhanpur, three Tier 2 cities in Orissa, utilising both structured questionnaire and interview methodologies. To fully achieve the aforementioned goals, this empirical study also includes both primary and secondary data. 4. Tung, (2023) The report makes an effort to examine financial inclusion in all of Odisha's districts on a comprehensive basis. The current study examines the financial inclusion of Odisha at the district level for the years 2010 to 2020 using two variables: the number of branches and the number of bank accounts. The chosen variables represent, at least generally, how the banking business is distributed and, subsequently, how much it is present or absent. While a deposit account shows how to utilise and access banking, the distribution of branch locations shows how deeply people are incorporated into the financial system. Thereafter, individual indices are built for each component, resulting in the composite index known as the Index of Financial Inclusion (IFI). The socioeconomic profile (the main respondents of the survey) was widely discussed in his 29 terms in Baripada city, based on field data. According to a preliminary report from the 2011 Indian Census, Baripada has a population of 110,058, of which 57,008 are male and 53,050 are female. Baripada City has 110,058 inhabitants. The city/city has 116,874 inhabitants, of which 60,535 are male and 56,339 are female. Also, in the education sector, there are a total of 89,421 illiterate people in Baripada city, of which 48,388 are men and 41,033 are women. Baripada City has an average literacy rate of 89.31% with male and female literacy rates of 93.45 and 84.88 respectively. By investigating whether social work professions can contribute to financial literacy, Designated Tribes can develop an understanding and knowledge of financial literacy (Anderson et al., 2013). The contribution of social work to general financial education can be justified in terms of vocational theory. Social workers should promote financial education to alleviate poverty by connecting economically vulnerable people to key financial education providers. RESEARCH METHODS American Journal of Economic and Management Business Vol. 2 No. 4 April 2023 146 The information was gathered from both primary and secondary sources This study is descriptive and analytical in nature as it aims to describe the situation of tribes in terms of access to banking services in Baripada city, Mayurbanji district, Odisha. Field studies are conducted for research purposes. A sample size of 360 is obtained and responses are collected in a structured timeline questionnaire. Researchers determined the samples using practical sampling methods. The scheduled survey consists of 25 questions (A. S. Singh & Masuku, 2014). Quantitative methods are used to analyze the collected data. Secondary data were collected from secondary sources such as websites, news channels, newspapers and government, statistical reports. For categorical data, data were summarised and assessed using frequency and percentages. Mean, Standard Deviation, and Median were used to analyse interval data and rating scales. The economic and social impact of financial inclusion on rural and urban households has been assessed using multiple regression analysis. In the study, the total score of the individual sub-components of the constructs was obtained by adding up the scores of each question falling under those components, followed by standardisation and sorting out using the property of normal distribution, while measuring the components of financial inclusion and its impact on socioeconomic status. The component of financial inclusion and its impact was measured independently, while the final component of inclusive growth was considered dependent. They were evaluated and classified as average, below average, and above average using normal distribution and percentile values. The above mentioned objectives have been verified by the application of Chi- Square test (x^2) for observed results with expected results, T test for compare the means of two groups and Eigenvalues for reducing dimension space. The Logit model was used in this quantitative analysis because it captures the persistence of dependent variables with binary yes or no outcomes (Alemayehu, 2014). In this context, variables with binary outcomes are financial inclusion. Whether the respondent is financially involved. In this study, financial inclusion is measured by account availability and frequency of access to financial services RESULT AND DISCUSSION Observations on the Nature, Extent, and Impact of Financial Inclusion in Rural and Urban Populations. Table 1 :Distance as a Barrier to Banking Services Distance as barrier to banking services Rural Urban Total No 74.8 96.1 85.45 Yes 25.2 3.9 14.55 Total 100 100 100 Note: x2 =115.353, d=1, p =0.000<0.01, HS Source: Survey Data Rupak kumar Tung 147 In terms of distance to access banking services, nearly 78.6% of households If the distance from which basic banking facilities or other banking facilities can be accessed is less than 5 kilometers, About 20.6% of households were within 5-10 kilometers of a formal bank, and only 0.8% of households he had to travel more than 10 kilometers to get banking services. Rural BPL households had distance problems to access basic banking and other facilities compared to urban households, which was highly statistically significant and confirmed by the chi-square test. (z2 = 115.353, df = 1, p = 0.000 < 0.01 , HS ) Table 2: Distribution of Households based on the Nature of Financial Inclusion (Figures in percentage) Note: x2 =402.372, df=2, p=0.000<0.01, HS Source: Survey Data Among rural and urban households surveyed in the income sector of Orissa, CB emerged as the main channel of banking service delivery. The majority of households had access to two or more formal financial institutions for banking services and benefited from poverty eradication, risk reduction, productivity enhancement and government-sponsored human resource development programs (Hussain et al., 2014). Across income sectors, there were disparities in access and use of formal banking services, but those with lower incomes who had recently started using banking services were unaffected. In this regard, inter alia: 66.5% of rural households had below average financial inclusion flat. Only 7% of rural households were in the above average category and almost 46.8% of urban households had above average levels of financial inclusion, while 9.1% were in the below average category. rice field. Overall, approximately 37.85% of households had a below- average type of financial inclusion, and 26.9% of households were in the above-average category. Across income bands, the difference between rural and urban households was statistically significant and confirmed by the chi-square test (x2=402.372, df=2, p=0.000<0.01 HS). Nature of Financial Inclusion Rural Region Urban Total Below Average 66.5 9.2 37.85 Average 26.5 44.0 35.25 Above Average 7.0 46.8 26.9 Total 100.0 100.0 100.0 American Journal of Economic and Management Business Vol. 2 No. 4 April 2023 148 Table 3: Distribution of Households based on the Extent of Financial Inclusion Note x2: =246.720, df=2, p=0.000<0.01, HS Source: Survey Data On average, 79.3% of rural households had below average levels of financial inclusion. Overall, about 8.1% of households had an above-average level of financial inclusion. Among urban households, about 31.3% had below average levels of financial inclusion and were below average. 55.3% of households had above average levels. The difference between rural and urban households across income strata was highly statistically significant, as indicated by the chi-square test (x2=246.720, df=2, p=0.000<0.01HS). Table 4: Inter-Tribal Financial Inclusion Index (IFI) variables Sl. No. Variables in IFI Mean Scores among Tribes in ‘t’ Statistics Urban Rural 1. Loan from financial institution 3.4812 3.8895 -2.2273* 2. Loan under schemes 3.4981 3.9189 -2.5503* 3. Loan under microfinance 3.5046 3.5599 -2.3286* 4. Loan through SHG 4.4542 3.8676 -2.5314* 5. Savings in saving account 3.4218 3.1887 2.8942* 6. Savings in recurring deposits 3.8114 3.2583 2.5647* 7. Savings in fixed deposits 3.9027 3.2528 2.7119* 8. Daily savings in banks 3.9194 3.4187 2.6914* 9. Payment of health and life insurance 3.8123 3.0985 2.8194* 10. Payment of family insurance 3.7558 3.2122 2.7243* 11. Usage of cheques and drafts 3.8999 3.1142 2.9988* 12. Usage of mobile banking 3.8213 3.0341 3.0986* 13. Usage of net banking 3.7199 2.9783 2.8571* 14. Usage of money transfer 3.5693 2.8434 2.9294* 15. Usage of other banking instruments 3.7550 3.1756 2.6576* Significant at 5% level. The table shows that IFI bank term deposits and daily savings are variables highly valued by urban tribes. The average values are 3.9027 and 3.9194 respectively. Among rural tribes, there are SHG loans and microfinance loans, with average values of 3.8676 The extent of Financial Inclusion Rural Region Urban Total Below Average 79.3 31.3 55.3 Average 4.1 12.1 8.1 Above Average 16.6 56.6 36.6 Total 100.0 100.0 100.0 Rupak kumar Tung 149 and 3.5599 respectively (Hoffmann et al., 2021). Regarding the IFI variables, significant differences between urban and rural tribes were found at the levels of all 15 IFI variables. This is because the corresponding 't' statistic is significant at the 5% level. Table 5 : Important Banking Activities in Financial Inclusion (IBAFI) Sl. No. IBAFI No. of Variables in Eigenvalue Percent of Variation Explained Cumulative Percent of Variation Explained 1. Loans 4 4.0867 28.27 27.29 2. Savings 4 3.7096 24.85 51.99 3. Value-added Services 4 3.1918 20.73 72.69 4. E-banking services 4 2.3985 14.94 88.61 KMO measure of sampling adequacy: 0.8116 Bartletts test of Sphericity: Chi-square value: 111.99* Significant at 1% level The table above shows that the first two IBAFIs recognized by EFA for the intrinsic value of loans and savings are 4.0867 and 3.7096 respectively. 28.27% and 24.85% are the percentages of variability explained by these two activities. The cumulative percentage of variation interpreted by these two activities is 27.29% and 51.99% respectively. The two main activities identified by the factor analysis are value-added services and e-banking services. Their eigenvalues are 3.1918 and 2.3985 respectively. The percentage of variation explained by these two significant activities is 20.73% and 14.94% respectively. The four IBAFIs described show 16 variables at 88.61%. All four of these IBAFIs are considered for further analysis. Correlation analysis: Correlations between study components were assessed by the Karl Pearson correlation coefficient and grouped into three categories. For 'r' values greater than 0.8, the first category is 'strong correlation'; for 'r' values between 0.5 and 0.8, the second category is 'good correlation' and the third category is 'moderate It was correlation. The 'r' value is between 0.3 and 0.5 between study components. Overall, the correlations between the components of financial inclusion and inclusive growth and the socioeconomic impact components of formal financial service use and inclusive growth are measured as 'good' and 'strong' correlations. was done (0.801 and '0.660' p < 0.01), statistically significant. Regression analysis: American Journal of Economic and Management Business Vol. 2 No. 4 April 2023 150 To assess the impact of formal financial service use on inclusive growth outcomes, a multiple regression analysis was performed using inclusive growth as a baseline and the impact of financial inclusion and financial service use as predictors. . The analysis was statistically significant (t=30.044 & 26.257, p<0.01) and at the aggregate level, the components of “financial inclusion” (type of financial inclusion + degree of financial inclusion) and “impact of financial services consumption” was suggested. ' (material change + cognitive change + perceptual change + relationship change after consumption of financial services) had a significant impact on the 'inclusive growth' component, confirmed by the standard beta values (each §= 0.572 and 0.500). This accounts for 0.622 of the variability indicated by the R° statistic. The regression equation that predicts the impact of financial inclusion on inclusive growth and access to finance is Y = 13.335 + 0.774 X1 + 0.848^X2. Domínguez-Almendros et al., (2011) The Logit model was used in this quantitative analysis because it captures the persistence of dependent variables with binary yes or no outcomes (Gujarati 2003). In this context, variables with binary outcomes are financial inclusion. Whether the respondent is financially involved. In this study, financial inclusion is measured by account availability and frequency of access to financial services. A; The estimated equation; Y= β0+β1x1+β2x2+β3x3……+μ In this study, financial inclusion is measured by account ownership and frequency of access to financial services. We used five explanatory variables, Gender, education, marital status, and financial institution defining the dependent variables. (1) . Frequency of assessing = c+β1male+β2educ+β3amount+β4single+β5financial institution. The above formula estimates financial inclusion potential based on various characteristics. In this study, too, financial inclusion is measured by the frequency with which financial services are rated. The variables gender (= 1 if male), education, employment level, marital status (= 1 if single), having an account with a financial institution. Table 6: Definition of variables; Variable name Definition of variables Sex =1 if male Marital Status =1 if single Level of education Level of education of tribes No of education =0 if no education Primary =1 Secondary =2 Higher Secondary =3 Graduation =4 Higher Studies =5 Daily Amount Amount of money in Baripada town that the individual earns per day Availability of financial institution In any bank, micro-finance or other financial institutions Rupak kumar Tung 151 Type of financial institution Type of bank, micro-finance and other financial institution of Baripada town Frequency How many times do you access , use, afford your bank account or other financial institution Source: Interview data from field work (Dec 2022) The choice is between logit model and Probit model and I did both but am going to report the logit model. Table 7: Logit/ Frequency of assessing financial services Dependent variable: Frequency of assessing Method: ML- Binary Logit ( Newton-Raphson / Marquardt step) Variable Coefficient Std. Error Z- Statistics Prob. Male 0.839387 0.652732 1.165321 0.2104 Education 0.333887 0.348108 1.087714 0.2897 Amount 0.000110 6.38E-05 1.642977 0.0984 Single 0.217349 0.687126 0.382152 0.7256 Institution 1.346988 0.596285 2.560042 0.0116 C -5.219927 1.172432 -4.581918 0 McFadden R-squared 0.275675 Mean dependent var 0.24 S.D dependent var 0.441953 S.E of regression 0.36738 Akaike info criterion 0.989812 Sum squared resid 13.0732 Schwarz criterion 1.046222 Log likelihood -38.981 Hannan-Quinn criterion 0.964074 deviance 76.9813 Restr. Deviance 105.8653 restr. Log likelihood -54.918 LR statistic 33.78553 Avg. Log likelihood -0.3898 Prob (LR statistic ) 0.000007 Obs with Dep=0 269 total Obs 357 Obs With Dep=1 88 . Standard errors *** P<0.01, ** p<0.05, * p<0.1 In my sample of 357 observations. The results show that 88 tribes accessed or used his account at least once a month in the last six months, while 269 tribes had not accessed their accounts in the last six months.McFadden's r-squared of 0.275675 indicates that some variables (gender, education, marital status) have the expected signs, but are not American Journal of Economic and Management Business Vol. 2 No. 4 April 2023 152 statistically significant, so the model works logically well indicates that Furthermore, the likelihood ratio test statistic of 33.78553 and the associated p-value of 0.000007 indicate that the model fits significantly better when he uses all five of his explanatory variables than when he uses fewer explanatory variables. I'm here. A coefficient of 0.00 associated with the variable amount is statistically significant at the 10% significance level. This suggests that higher income tribe are more likely than lower income tribe to access or use their accounts at least once a month in the past six months. Furthermore, the coefficient of 1.3 associated with the availability of financial institutions within the city is statistically significant at the 5% significance level (Kostovetsky, 2015). Also, schooled and single tribe access and use their accounts more than once a month in the past 6 months than out-of-school and married single tribe. more likely but this is not statistically significant. In summary, as noted above, financial inclusion in this study is measured by the presence of accounts and the frequency of access or use of financial services (Demirgüç-Kunt & Singer, 2017). As shown in Table 7, all five explanatory variables are positive: gender, education, marital status, amount of money, and financial institution. However, the amount is statistically significant at the 10% significance level, as shown in Table 7. Additionally, they are more likely to be financially involved, as shown in the table above. Thus, having an account and frequency of accessing or using financial services were the two dependent variables that defined financial inclusion in the study, with the availability of financial institutions in the city increasing the financial inclusion of tribe . more likely. CONCLUSION Based on observations, analyses, and insights, this paper draws the following conclusions.There is a mismatch between macro-level financial inclusion in the Indian economy and revenue sources in Odisha. At the macro level, even after financial inclusion initiatives have been implemented, there are large inequalities in the economy, with most farmers, the poor and marginalized segments of society lacking access to financial services. The study identifies differences in income distribution within states and among households belonging to socially disadvantaged sections of the population. There is a positive association between the use of banking services and socioeconomic status of households belonging to vulnerable groups. Therefore, financial inclusion of households belonging to vulnerable groups .It can be seen as an important factor in improving the socioeconomic status of households. The positive correlation between financial inclusion and inclusive growth can be seen as a factor underscoring the role of innovative, low-cost formal banking products in the process of inclusive growth. In addition to basic banking products, households belonging to vulnerable groups have access to Human Development Packages, Risk Reduction Packages and Productivity Enhancement Packages. This phenomenon demonstrates the role of welfare packages in improving the absorptive capacity of vulnerable people, lifting them from cycles of economic exclusion and making them more bankable. One key segment, households, would benefit from increased financial inclusion if promoted in the broader context of economic inclusion alongside social packages. Rupak kumar Tung 153 Formal financial networks have the potential to unlock the creative power of disadvantaged households, driven by increased incomes and consumption of a large proportion of the population belonging to disadvantaged groups. A formal banking system can improve the financial condition and living standards of households belonging to vulnerable groups and generate wealth, income and emergency funds to deal with unforeseen circumstances and economic crises; increase. It also benefits from the non-leak transfer of social benefits to disadvantaged segments of the population. Financial inclusion expands banking networks with more transactions, brings new ways of earning a living in society, and leads to inclusive growth of the economy. Given the existence of financial exclusion associated with the Indian economy, the study rationalizes public policies focused on financial inclusion. By confirming the link between financial inclusion and its impact on positive changes in the socioeconomic status of households in the sample area, the study supports financial sector reforms to promote financial inclusion. emphasizes the need to centre development agenda.. . REFERENCES Alemayehu, T. (2014). Smallholder farmer’s willingness to pay for improved irrigation water: a contingent valuation study in Koga Irrigation Project, Ethiopia. Journal of Economics and Sustainable Development, 5(19), 5–15. Ali, I., & Zhuang, J. (2007). Inclusive growth toward a prosperous Asia: Policy implications. ERD working paper series. Anderson, L., Ostrom, A. L., Corus, C., Fisk, R. P., Gallan, A. S., Giraldo, M., Mende, M., Mulder, M., Rayburn, S. W., & Rosenbaum, M. S. (2013). Transformative service research: An agenda for the future. 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Challenges For Financial Inclusion In Rural Areas Of Odisha. Copyright holders: Rupak kumar Tung (2023) First publication right: AJEMB – American Journal of Economic and Management Business