PRIORITY SECTOR LENDING BY FINANCIAL INSTITUTIONS

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1 PRIORITY SECTOR LENDING BY FINANCIAL INSTITUTIONS (WITH SPECIAL REFERENCE TO COIMBATORE DISTRICT) Dr.VENUGOPAL.G Assistant Professor of Commerce, Department of Commerce, Chikkanna Government Arts College, Tirupur ABSTRACT banks were advised to grant at least 40% of their total advances to borrowers in the priority sectors. This paper analyses and compares the performance of Financial Institutions in Priority Sector lending under Lead bank scheme with special reference to Coimbatore District. The analysis was made by the application of Kruskal-Wallis test to find out the significant among the financial institutions during the 11 years annual credit plan from 1 st April 2003 to 31 st March 2014 in relation to priority sector lending in Coimbatore District. The results of the study is that there was no significant difference among the performance of financial institutions in lending to the Agricultural Sector, Small Scale Industries Sector and total Priority Sector, but there was significant difference in lending to Services Sector. It is concluded that, Private Sector banks is good in lending to Agricultural and Services Sector. The banks are good in lending to Small Scale Industries and Total Priority Sector lending. Key words: Financial Institutions, Annual Credit Plans, Kruskal-Wallis test, Priority Sector, Null Hypothesis. 1. INTRODUCTION Banking sector plays an important and active role in the economic development of a country. The contribution of banks to Indian economic growth through Priority sector lending is remarkable. The priority sector lending was evolved and commercial banks were advised to grant at least 40% of their total advances to borrowers in the priority sectors. It covers sectors such as agriculture and allied activities (Agricultural sector), Small Scale Industries (SSI Sector), and small business, retail trade, small road transport, profession, self-employment, education, housing and consumption (Service Sector). The Lead Bank Scheme (LBS) 1 was introduced by Reserve Bank in 1969 when designated banks were made key instruments for local development and entrusted with the responsibility of identifying growth centres, assessing deposit potential and credit gaps and evolving a coordinated approach for credit deployment in each district in concert with other banks and other agencies. The 84

2 LBS underwent significant transformation in 1989 when the Service Area Approach was match into the scheme. District annual credit plan is an important part of the Lead Bank Scheme. The prime objective of district credit plan is to regulate the flow of priority sector credit in each district in accordance with the plan priorities. Canara Bank is the Lead bank of Coimbatore District. 2. REVIEW OF PREVIOUS STUDIES To study the priority sector lending of financial institutions in Coimbatore district, the researcher has referred to the important studies which have been already undertaken. Das 2 (2002) has studied the interrelationship among capital, non performing loans and productivity of public sector banks. Galagedera et al., 3 (2005) Performance of Indian ( ), this article investigates the efficiency and productivity in a sample of Indian commercial banks over the period The results reveal that there has been no significant growth in productivity during the sample period. Harsh Vineet Kaur 4 (2010) Analysis of in India A CAMEL Approach. In this article, an effort has been made to rank the various commercial banks operating in India. Malhotra 5 (1987) his research finds the correlation between agricultural credit and agricultural growth was found positive. A study on technical efficiency and benchmark performance of 68 commercial banks has been conducted by Mukherjee et al., 6 (2002), it is revealed that in India, public sector banks are more efficient than both private and foreign banks. Noulas and Ketkar 7 (1996) conducted a study to examine the technical and scale efficiency of banks. Patel 8 (1994) in his Doctoral dissertation entitled on Role of Lending to Priority Sector in Gujarat An Evaluation finds in his research are: The majority of the sample farm households were aware about the norms for determining the quantum of farm loan; the formal procedure to be observed in availing advance was found to be time consuming; Bank were lagging behind in achieving the set targets by providing advances to weaker section. Swamy 9 (2001) analyses the comparative performance of different banks groups. Qamar 10 (2003) has studied the profitability and efficiency in scheduled commercial banks in India. He concluded that the new private sector banks and foreign banks are marginally more efficient at the edge of the old private sector and public sector banks. 3. FINANCIAL INSTITUTIONS The financial institutions implementing the annual credit plan of Coimbatore District. It s divided into three categories, viz. branches of, Private Sector and of Agencies located in Coimbatore district. The other agencies are Pallavan Gramma Bank, Coimbatore Central Co-operative Bank Ltd., Tamilnadu Industrial Investment Corporation Ltd., and Small Industries Development Bank of India. 4. OBJECTIVE OF THE STUDY Analyses of priority sector lending by financial institutions in Coimbatore District. 5. HYPOTHESIS OF THE STUDY For the purpose of this study the following null hypothesis was framed: There is no significant difference among the performance of various financial institutions in lending to the Agricultural sector, Small Scale Industries sector, Services sector and total Priority sector. 6. METHODOLOGY The present research is an analytical study. 85

3 7. Data Sources 7.1 Secondary Data The study is mainly based on secondary data. The data required for study were collected from books, journals, Lead bank annual reports and web sites. 7.2 Period of Study The study covers the 11 annual credit plans starting from April 1, 2003 to 31 st March Analytical Tool The Kruskal-Wallis test used to analyse the data. It can be used with ordinal data as well as with interval or ratio data. The test does not require the assumptions of normality and equal variances. The Kruskal-Wallis Test statistic which is based on the sum of ranks of each of the samples can be computed as follows 11 : k W= 12 Ri 2-3 N(N+1) N(N+1) i= 1 N i Where, K= number of population groups (Number of financial institutions) = 3 N i = the number of items in sample i (11) N = total number of items in the samples (33) R i = total of the ranks for sample i The calculated value of W is compare with the table value of chi-square(x 2 ) at 5 per cent level of significance is X 2 = If the calculated value of W is less than or equal to the table value of chi-square (X 2 ), we conclude that, there was no significant difference among the performance of various financial institutions in lending to the priority sector. But, if the calculated value W exceeds the table value, the difference will be termed as significant. If it is found to be significant at 5 per cent level, it is further checked at 1 per cent level of significance value is X 2 = LIMITATIONS OF THE STUDY 1. The research is confined to the performance of various Financial Institutions in lending to the priority sector only. 2. The tool used (Kruskal-Wallis test) has it s? Own limitation, which in turn affects the result of the study. 8. ANALYSIS AND DISCUSSION To find the value of W, ranks are assigned to all 33 performance scores of 3 financial institutions (3 x 11=33 (Ref. Appendices II to V). The lowest value receives the rank of 1, whereas the highest value receives the rank of 33. Tied performance scores are assigned average rank values. The W values were calculated in sectors wise are given in Table 1 below. Table 1 Priority Sector lending of Financial Institutions Sectors W Result Agriculture Sector (8.77) Not Significant Small Scale Industries Sector (2.65) Not Significant Services Sector Significant Total Priority Sector (3.8559) Not Significant Source: Compiled from Appendices II V. It is evident from Table 1, the calculated value (W) is less than the table value of (X 2 ) at 5 per cent level of significance in respect of Agricultural Sector, Small Scale Industries Sector and 86

4 Total Priority sector. The null hypothesis framed for this study is accepted. Hence, we conclude that there was no significant difference among the performance of various financial institutions in lending to the Agricultural sector, Small Scale Industries Sector, and total priority sector. But, in Services sector the calculated value W = is more than the table value of 5 per cent and 1 per cent level of significance. Hence, we conclude that there was significance difference among the performance of commercial banks, Private Sector banks and other agencies in lending to the Services sector during the 11 years study period i.e from to CONCLUSION The performance of financial institutions is not significantly among in lending to the Agricultural Sector, Small Scale Industries Sector, and total Priority Sector. But there is a significant difference among Public sector banks, Private sector banks and other Agencies in lending to the Services Sector. The overall performance of Private sector banks is good followed by commercial banks and other Agencies in lending to the agricultural sector and services sector. (Appendix -II & IV). But, in Public sector commercial banks is good in lending to Industrial sector and total priority sector advances followed by Private sector commercial banks and other Agencies. The other agencies show poor performance during the period under study. (Appendix - III & V). APPENDIX -I ANNUAL CREDIT PLAN PERIOD (` in Lakhs) Financial Institutions (21 banks) Private Sector (16 banks) Agencies(4) Plan ` Agriculture Sector Small Scale Industries Sector Services Sector Perfor- P.Score Plan Perfor- P.Score Plan Performance mance (%) ` mance (%) ` ` ` ` P.Score (%) Total Source: Canara Bank, Coimbatore District Annual Credit Plan to , Lead Bank Section, Coimbatore.14 Notes: Performance Score (P.Score) of banks (PSCB) in lending to agricultural sector & Allied Sector during Annual Credit plan period Agri.Sector = Total performance of all public sector commercial bank branches x 100 Total plan amount for public sector commercial banks = x = (The same procedure is followed for calculating the performance scores of each group of Financial institutions for various sectors and total priority sector in all the Annual Credit Plan) 87

5 APPENDIX -II PERFORMANCE SCORES OF FINANCIAL INSTITUTIONS IN LENDING TO THE AGRICULTURAL SECTOR Year of Annual Credit Plan banks Performance Scores Private Sector Agencies Sum of ranks n 1 = 11 n 2 = 11 n 3 = 11 The W value is calculated as follows: W = 12 { (217) 2 + (225) 2 + (119) 2 } - 3 (33+1) 33(34) W = (8.77) 88

6 APPENDIX -III PERFORMANCE SCORES OF FINANCIAL INSTITUTIONS IN LENDING TO THE SMALL SCALE INDUSTRIES SECTOR Year of Annual Credit Plan banks Performance Scores Private Sector Agencies Sum of ranks n 1 = 11 n 2 = 11 n 3 = 11 W = 12 { (281) 2 + (163) 2 + (117) 2 } - 3 (33+1) 33(34) W= (2.65) 89

7 APPENDIX IV PERFORMANCE SCORES OF FINANCIAL INSTITUTIONS IN LENDING TO THE SERVICES SECTOR Year of Annual Credit Plan banks Performance Scores Private Sector Agencies Sum of ranks n 1 = 11 n 2 = 11 n 3 = 11 W = 12 { (204) 2 + (254) 2 + (103) 2 } - 3 (33+1) 33(34) W =

8 APPENDIX -V PERFORMANCE SCORES OF FINANCIAL INSTITUTIONS IN LENDING TO THE TOTAL PRIORITY SECTOR Year of Annual Credit Plan banks Performance Scores Private Sector Agencies Sum of ranks n 1 = 11 n 2 = 11 n 3 = 11 W = 12 { (274)2 + (171)2 + (116)2 } 3 (24+1) 33(34) W = (3.8559) 91

9 REFERENCES: 1. Report of the High Level Committee (2009) to Review Lead Bank Scheme, RBI, Aug.,p Das Abhiman(2002), Risk and Productivity change of public sector banks, EPW, Vol.37, No. 5, pp Galagedera, Don UA, Edirisuriya, Piyadasa(2005), Performance of Indian Commerical ( ), South Asian Journal of Management, Association of Management Development Institutions in South Asia(AMDISA), Hyderabad. Oct.-Dec. 4.Harsh vineet Kaur (2010), Analysis of in India A CAMEL Approach, Global Business Review, June, Vol.11, PP Malhotra S.R(1987), Institutional Credit to the Needs of Small Farmers", Indian Dissertation Abstrat, ICSSR; New Delhi. 6.Mukharjee A, Nath P and Pal M N(2002), Performance Benchmarking and Strategic Homogeneity of Indian, International Journal of Bank Marketing, Vol. 20, No. 3,pp Noulas A G and Ketkar K.W.(1996), Technical and Scale Efficiency in the Indian Banking Sector, International Journal of Development Banking, Vol. 14, No. 2,pp Patel.S.G. (1994) Role of Lending to Priority Sector in Gujarat An Evaluation, Finance India, Vol.X, No.2, June 1996, pp Swamy B N A(2001), New Competition, Deregulation and Emerging changes in Indian Bankings: An Analysis of Different banks Groups, The Journal of the Indian Institute of Bankers, Vol.72, No.3 July Sept., pp Qamar F(2003), Profitability and Resource Use Efficiency in Scheduled in India: A Comparative Analysis of foreign, New Private Sector, Old Private Sector and Public Sector banks, Synthesis, Vol. 1, No. 1, pp C.R.Kothari(2004), Research Methodology, New age International (P) Ltd, New York.2 nd Edition, PP Coimbatore District Annual Credit Plan Report ( to ), Canara Bank, Lead bank, Coimbatore District. 92