Challenges Confronted by Banks in Implementing Financial Inclusion Schemes in Himachal Pradesh

India has been acknowledged the social and economic obligations of financial inclusion since independence and has made immense contributions. The government of India and the Reserve Bank of India has been making combined efforts to foster financial inclusion as one of the primary national aims of the country. Since last decade hard efforts have been made by the government to cover the unbanked population under the formal financial sector. A lot of important schemes have been introduced by the government from time to time for the benefit of the people on one hand and to strengthen the economy on the other but the load of execution of the schemes on the ground level was on the shoulders of banks. As far as the economic upswing of the nation is concerned, the most relevant thing is the financial inclusiveness, for which the paramount role players are banks. It will be impossible to think about financial inclusive economy if banks do not link the governmental schemes with the end users. Concerning the significance of banks study has been undertaken to study the challenges confronted by banks while implementing financial inclusion schemes in Himachal Pradesh. The study is based on the primary data collected with the help of questionnaires to be filled by branch’s manager or assistant manager by 64 selected banks of the state. To achieve the objective of the study analysis has been done with the help of various statistical techniques like mean, standard deviation and exploratory factor analysis.


Introduction
Concerning the economic upswing of the nation, the most relevant thing is the financial inclusiveness, for which the paramount role players are banks. In simple terms, financial inclusion refers to the process that ensures accessibility, availability and usage of formal banking products and services to all the members of an economy without discrimination 1 . It will be impossible to think about financial inclusive economy if banks do not link the governmental schemes with the end users. No doubt banks are the nervous system of every financial system that covers the gap between banks and unbanked population by extending suitable financial products and services to the people when expected to pursue the vision of financial inclusion. India has been acknowledged the social and economic obligations of financial inclusion since independence and has made immense contributions. The government of India and the Reserve Bank of India has been making combined efforts to foster financial inclusion as one of the primary national aims of the country. Since last decade hard efforts have been made by the government to cover the unbanked population under the formal financial sector. A lot of important schemes have been introduced by the government from time to time for the benefit of the people on one hand and to strengthen the economy on the other but the load of execution of the schemes on the ground level was on the shoulders of banks 2 . Hence it is mandatory that bank should not confront any obstacle while executing these schemes, as if they face any hurdle, it may reduce the productiveness of the scheme. Therefore, the study has been undertaken to explore the major factors that bank employee's face in Himachal Pradesh while implementing

Research methodology
The present study covers the challenges faced by the banks in implementing financial inclusion schemes based on the primary data collected with the help of questionnaires to be filled by branch's manager or assistant manager by 64 selected banks of the state. With respect to data collection from banks three banks have been purposively selected namely PNB, SBI and UCO banks as these three banks are having maximum number of branches and these three also act as lead banks in our state. An effort has been made to study the financial inclusion schemes offered by a selected bank, method opted by the banks to provide information to public about newly introduced schemes, main hurdles confronted by banks while executing schemes. The 64 respondents from 64 selected banks from two districts of the state identified through proportionate sampling method. In order to assess the challenges, the data has been collected from the bankers on 5-point Likert scale ranging from 5 points for to great extent to 1 point for not at all. To test the reliability and internal consistency of questionnaire cronbach's alpha technique was applied. An effort has been made to extract the factors which put maximum hurdles in the financial inclusion efforts of banks in the state. The data archived has been appropriately classified and analyzed with the help of exploratory factor analysis. The appropriateness of analysis was determined by the Kaiser-Meyer-Olkin measure of sampling adequacy and Bartlett's test of sphercity. The extraction of factors was done using varimax rotation method of data normalization.
Analysis and findings Table 1 is presenting the classification of banks on the basis of district and reveals that major bank operating in the state is Punjab National bank followed by State Bank of India and United Commercial Bank. The above table is highlighting that 42 banks covered under the study has been selected from district Kangra and rest 22 banks has been taken up from district Mandi.

Classification of bank officials on the basis of demographic features
The demographic features of bank officials have been depicted through table 2  Table 2 is presenting the distribution of respondents on the basis of their gender and reveals that a large segment of respondents is male i.e. 90% and only 10% females are working as managers in the banks. Further majority of respondents fall in the age group of below 35 years i.e. 55%. About 30% respondents belong to the age group of 36 to 50 years and remaining 15% respondents are of 51 years and above. Educational qualification of respondents has been also analyzed which shows that majority of respondents are post graduate followed by 33.3% respondents are graduate and 15% respondents are having professional degree. On the basis of their experience most of the bank managers 58.3% are having experience of 11 to 20 years followed 30% are having less than 10 years of experience and few of them only 11.7% are having work experience of more than 20 years in banking line.

Respondent's opinion about financial inclusion schemes offered by banks
Major eight national level financial inclusion schemes were selected and banks were asked to provide information about which of the selected schemes have been offered by them. The data collected shows that maximum schemes have been offered by all the selected bank branches of the state fully except Pradhan Mantri Vaya Vandana Yojna which is not operative in 60% banks of our state.   Table 4 furnishes the information regarding how banks manage to spread information to the public about newly introduced financial inclusion schemes and found that majority 95% of the banks organize financial inclusion programs then 90% also uses pamphlets and brouchers followed by 76.7% use services of business correspondents to aware people about the schemes at their door steps. 73.3% responded that they also directly approach customer when they visit bank branch. The least used method from the list is mass media as only 35% banks responded yes for mass media as a source of spreading information to the public.

Analysis based on factors that act as main hurdles of financial inclusion efforts of banks
The current analysis has been planned to scrutinize the problems that come across banks while implementing financial inclusion schemes. The descriptive analysis of problems confronted by banks while implementing financial inclusion schemes has been exhibited in table 5. It reveals from the table that illiteracy of people, indifferent attitude of people, lending money to poor people is attracting NPA, influence of informal sector, account dormancy and lack of staff are the most important factors which negatively effects the bank officials as these variables has the highest mean score 3.5932, 3.4237, 3.4068, 3.3390, 3.2881 and 3.2881 respectively. However, lack of faith of people in banks has the lowest mean 1.3559 with standard deviation 0.94253.

Factor analysis: Data suitability test
Factor analysis is a procedure used to lessen the multivariate data into fewer interpretable components. This is an efficient way to extract most common variances from all the variables and place them in a common carton. This technique is considered because it does not need any prior operational relationships and is a commonly applied technique of data reduction.

(a) Reliability test:
First of all, the reliability of scale is determined by computing the coefficient of cronbach, alpha which confirms the intrinsic consistency of the scale. The value of coefficient alpha 0.7 or higher is acceptable. 9  Table 5.1(a) summed up the cronbach's alpha for given items in the scale. The outcome specifies that scale is having good reliability with alpha value 0.919 for 13 statements in the scale.

(b) KMO and Bartlett's test of sphericity
The subsequent  .000 Here, value of KMO = .683 which indicates that the sample is adequate and we can proceed with factor analysis.
With regard to Bartlett's test, the approximate of chi square is 728.386 with 78 degree of freedom which is significant at 0.05 level of significance i.e. sig = .000, consequently there is considerable correlation in the data. Therefore, factor analysis is observed as a relevant technique of further analysis of data.

Factor analysis; Total variance explained
The Eigen values, variance percent and cumulative variance description for our factor solution has been illustrated in table 5.3 The first panel depicts the initial eigen values, the second panel depicts the extraction sums of squared loadings and the third panel presents the rotation sum of squared loadings. Eigen value constitutes the total variance defined by each variable. Eigen value more than 1 will be chosen as components. In the present study only 4 components are extracted by collaborating the material variables. The total column furnishes the quantity of variance of each variable. In a good factor analysis, there are few components that explain a lot of variances and few explain small amount of variance. Only those variables are considered whose eigen value is more than 1 and the remaining variables whose amount of variance is very small are not considered by the analysis. In the present study 4 factors have been obtained from 13 variables, representing major problems faced by banks while implementing financial inclusion schemes in the state. The first component explains 53.714 percent of variance, second factor 10.393 percent and third factor 9.377 percent of variance and the fourth factor explain 8.293 percent of variance. All the remaining variables are not remarkable.

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The extraction sum of squared loading provides details about extracted factors. These values are always same as displayed under initial eigen values. Further rotation sum of square loadings is also displayed. This column emerged when we choose the rotation of factors. In the current study varimax rotation solution has been used. The percentage of variance displayed by the rotated sum of square loadings are different for the selected components but the cumulative percentage for the group of three factors are always same i.e. 81.777.

Scree plot
The graphical representation of factor analysis is known as scree plot. The scree plot exhibits the association between number of variables and their respective eigen value as is portrayed in figure 1 The scree plot portrays the eigen value against each variable. This graph is helpful to determine number of variables to be retained. The point of concern is where the curve starts to flatten. We can see in the graph that after 4 components, there is change in the arch of the scree plot and it is going downward. This shows that after fourth component the variance accounts for smaller and smaller.

Rotated component matrix
The rotated component matrix usually referred to as the loadings, is the crucial findings of principal component analysis. It covers the extent of the correlation between individual variable and the extracted components. The objective of rotation is to reduce the number of variables on which the statement under investigation has high loadings. Actually, rotation does not make any difference but facilitates the interpretation. The above table presents rotated component matrix and intimates the factor loading for each variable after rotation. The correlation between the items and the rotated factors is represented by each number. This correlation assists us to simplify the association between variables and factor. With the help of above rotated component matrix various variables have been clubbed in four factors.
Factor 1: Infrastructure inadequacy: This factor measures the bankers' opinion about problems associated with implementation of financial inclusion schemes in rural areas with respect to infrastructure. Infrastructure is the basic structure, facilities and systems that ensures the smooth functioning of any department. It is directly associated with the productivity and quality of work. With respect to banking sector, if there will be inadequate infrastructure it will significantly hamper the efficiency and outcomes of a particular branch. The key variables extracted under this factor are "lack of staff" (.840 factor loading), "lack of infrastructure" (.826 factor loading), "lack of proper network facilities" (.786 factor loading), "lack of upgraded technology" (.697 factor loading), and "lack of branch approachability" (.644 factor loading). Hence the highest rating has been given to the variable lack of staff. In order to achieve complete financial inclusion as one of the commanding agenda of Indian government, branches are opening in each and every corner of the country; there is growing need of business correspondents, sale executives and other bank professionals to reach out the rural people; banks have become target oriented nowadays. Thus, there is abundance of growth opportunities in the banking sector, but the staff shortage is one of the major issues confronting by banks to achieve their targets and expectation of Government with respect to the implementation of financial inclusion schemes. Further proper network coverage is another major issue in the hill states due to its geographical and climatical conditions. More over lack of upgraded technology and approachability of branch by the rural women are the significant concern in front of bankers to achieve their targets smoothly.
Factor 2: Illiteracy: This factor is the sum of those variables which are indicating that lack of literacy and economic backwardness are the supreme issues that become hindrance in the way of banks to implement financial inclusion schemes completely and efficiently. The key variables extracted under this factor are "long processing time (.882 factor loading), "illiteracy of people" (.835 factor loading), "influence of informal sector" (.725 factor loading), "economic backwardness of people" (.703 factor loading) and "indifferent attitude of people" (.697 factor loading). Rural women have been usually considered as deprived segment of society since life because they are less educated and less aware that is why they do not understand what change formal financial services especially loan services can bring to their life. Moreover, life spent by them on doing domestic work is unrecognized as well as unpaid because of which they are economically backward. This backwardness and unawareness are the main cause of their indifferent attitude towards banks and still made them to choose informal sources of finance to fulfill their credit needs. Thus, due to ignorance and poverty choosing to informal sources over formal sources don't let banks to achieve the target of complete financial inclusion till date.
Factor 3: Increasing unproductivity: Banker's perception is that somehow due to the influence of financial inclusion scheme, account opening has been enormously increased but the major concern for banks officials is that account of rural women remained unused for long time and become dormant. More over under lending schemes, when loans are given to poor people, NPA is increasing due to poor recovery hereby enhancing unproductivity in terms of achievement of targets and profit in the bank branch. This is why factor has been named as unproductive. The key variables extracted under this factor is "account dormancy" (.953 factor loading) and "lending money to the poor is attracting NPA" (.753 factor loading). According to Reserve Bank of India a saving account will be treated as dormant if there is no transaction over a period of two years. The account dormancy is actually contradicting and paralyzing the essence of financial inclusion schemes. Government is claiming complete financial inclusion on the ground of account opening by the people but what if those accounts remained unused. People are not saving anything in their accounts, they are not lending money from banks and not using basic financial services then the essence of financial inclusion becomes worthless. Moreover, people who are taking financial help from bank are not repaying and this causes banking NPA which is harmful for bank's financial position.
Factor 4: Lack of trust: The fourth factor is named as 'Trust' containing the variable 'Lack of faith of people in banks' (.942 factor loading). If rural women are not having faith in banks, then the major reason behind this is again lack of literacy and awareness.

Conclusion
From the above analysis we come to the conclusion that goal of financial inclusion cannot be realized without the active participations of banks as well as the participation of the people for which the schemes are designed and efforts are made. Despite of the hard efforts made by banks to implement the financial inclusion schemes there is still gap between the banking services and unbanked populations especially rural women. From the above analysis it is clear that major challenges which banks are still confronting includes four major factors namely infrastructure inadequacy, illiteracy of rural people, increased unproductivity due to NPA and moreover lack of faith of rural people in banks. The study has recorded four factors explaining the problems faced by rural banks to implement financial inclusion schemes effectively namely inadequate infrastructure especially lack of staff, network connectivity. Thus, government need to ensure the recruitment of staff in the rural banks and high-speed broad band should be made available. Second is the illiteracy of people, thus stress should be given on strengthening the educational base of rural women. Third factor is increasing unproductivity in the form of account dormancy and NPA is enhancing somehow because of lack of income, if rural women will be provided with income opportunities the issue of account dormancy and increasing NPA will be resolved. The study also advocated that the policymaker should study the psychology of rural women and their specific needs so that need based financial products and policies can be introduced. More holistic approach is needed to motivate the rural people to understand the worth of various financial inclusion schemes so that they prefer to subscribe the schemes, can cooperate banks in effective implementation and can get superlative benefits out of it.