Overview Of Banking Project Title: Comparative study of non interest income of the Indian Banking Sector Submitted by: Gaurav Sharma BBA(Finance, Gold Medal),MBA(Finance) [email protected]. com Electronic copy available at: http://ssrn. com/abstract=1431288 Index Introduction Methodology SBI& Associates Nationalized banks(Public sector banks) Private sector banks Foreign banks Findings Conclusion Literature review References 1 3 5 10 15 20 25 26 26 26

Electronic copy available at: http://ssrn. com/abstract=1431288 Introduction There are two broad sources of bank revenues: 1. Interest income 2. Non-interest income. Interest income is generated from what is known as “the spread. ” The spread is the difference between the interest a bank earns on loans extended to customers, corporate etc and the interest paid to depositors for the use of their money. It is also earned from any securities that the banks own, such as treasury bills or bonds.

Non-interest income is earned by providing a variety of services, such as trading of securities, assisting companies to issue new equity financing, securities commissions and wealth management, sale of land, building, profit and loss on revaluation of assets etc. As compared to the developed world, the Indian banking sector, apart from the relying on traditional sources of revenue like loan making are also focusing on the activities that generate fee income, service charges, trading revenue, and other types of noninterest income.

While noninterest income plays an important role in banking revenues in the developed world, its contribution to the total income of the Indian banking was 25% as on 31st March 2008. Components of non interest income The major components of non interest income in our banking sector are as follows: 1. 2. 3. 4. 5. 6. Commission/ exchange and brokerage Profit or loss on Sale of investments Profit or loss Sale of land& buildings Profit/loss on revaluation of investments Profit or loss on Exchange transaction etc. Miscellaneous income source which includes advisory, trading etc.

Share of various sources of non interest income The share of various sources of non interest income to the total income of banking sector as on 31st march 2008 is shown in the pie chart below: In the above figure we find that the highest contribution to the non interest income has been of the commission followed by sale of investments, miscellaneous income and exchange transactions. Movements of interest and non interest income of the Indian banking sector (1994-2004) Methodology Under this I have done a comparative study of non interest income of the Indian banking sector by classifying banks into four categories: 1.

SBI and associates which includes State bank of India, State bank of Bikaner and Jaipur, State bank of Hyderabad, State bank of Mysore, State bank of Patiala, State bank of Saurashtra and State bank of Travancore. 2. Nationalized banks: (Public sector banks) which includes Allahabad bank, Andhra bank, Bank of Baroda, Bank of India, Bank of Maharashtra, Canara bank, Central Bank of India, Corporation bank, Dena bank, Indian bank, Indian Overseas bank, New bank of India, Oriental bank of Commerce, Punjab &Sind bank, Punjab National Bank, Syndicate bank, UCO bank, Union bank of India, United bank of India, Vijaya bank. Total 19) 3. Other scheduled banks: (Private sector banks) which includes Development credit bank, Times bank, Axis bank, Indus land Bank, ICICI bank, Bank of Rajasthan, Catholic Syrian bank, Lakshmi Vilas bank, HDFC bank, Centurion bank, Bank of Punjab, Tamilnad Mercantile Bank, Federal bank, Punjab Cooperative bank, Lord Krishna bank, ING Vyasya bank, IDBI bank, Dhanlakshmi bank. (total 18 banks) 4. Foreign banks: which includes Barclays bank, ING bank, ABN Amro bank,

Bank of America, BNP Paribas, Standard Chartered bank, DBS bank ,Citibank, HSBC, Deutsche bank, Mashreq bank, Bank of Nova Scotia, Bank of Bahrain & Kuwait, American Express bank (total 14 banks) The banks used under private sector and foreign sector category are reflective of major portion of their respective market/category. Moreover data was not available for other banks within that category. The period of study taken was 11 years i. e. 994-2004. The period of study was taken as 11 years because, for the above mentioned period the data was available for all the bank and to ensure uniformity. Objectives of the study: 1. To analyze the growth of non interest income as a source of revenue for the Indian banking sector over a period of 11 years (1994-2004). 2. To analyze the contribution of major components of the non interest income over a period of 11 years (1994-2004). 3.

To find out statistically that how much of the profits of the banking sector over a period of 11 years is determined by non interest income and interest income. 4. To find out statistically the contribution of various components of Non interest income towards the profits of the bank over a period of 11 years. 5. To find out the contribution of interest and non interest income towards the total income in each of the 11 years (1994-04). 6. To find out the correlation between the non interest income and the total income of the banking sector over a period of 11 years. . To find out the reasons for the increase in the non interest income and what are the challenges involved to generate non interest income. Tool used: Data regarding the interest income, non interest income, profits, various components of non interest income, total income of the banking sector has been collected from the RBI website. To find out the influence of interest and non interest income on the profits of the banking sector, I have made use of multiple regression tool in E-views software.

The interest and non interest income were independent variable and the profits of the bank was the dependent variable Two Multiple Regression equation was used for the study: Equation 1 Profits=a+b1*interest income+b2*noninterest income Where b1 and b2 were coefficient and a is the intercept term which shows the profits of the bank had been c if interest and non interest income had been 0 Equation 2 Profits: a+b1*commission+b2*profit/loss on sale of land+ profit/loss on sale of investment+ profit/loss on revaluation of investment profit/loss on exchange transactions+ Miscellaneous income Where profits was the dependent variable and various components of non interest income were independent variable and a is the constant term The equation 2 was used to find out the influence of various components of non interest income on the profits of the bank. SBI and Associates (Rs‘000)

In the above table we see the following: Column1: Average Column 2: Year Column 3: Other income or the non interest income of the bank Column 4: Commission, exchange and brokerage Column 5: Net profit/loss on sale of investment Column6: Net profit/loss on revaluation of investment Column7: Net profit/loss on sale of land, building and other assets Column 8: Net profit/ loss on exchange transactions Column 9: Miscellaneous income Column 10: Total income of the bank Column 11: Profit/loss of the bank Column 12: Interest income of the bank Column 13: Noninterest income as a percentage of total income Column 14: Interest income as a percentage of total income Influence of interest and non interest income on profits of SBI& Associates The above output is of the multiple regression equation where we have tried to find out that how much of the profits of the SBI and its associates are determined by interest and non interest income. 1. We find non -interest income to be a significant variable in explaining the profits of SBI as the prob value is less the . 05 (. 0095)and the value of t stat is more than 2(3. 386)[ Rule: an independent variable is said to be significant is its prob value is less than . 05 or the t-stat is more than 2). 2.

We find that in our regression model the percentage of variation in the profits of SBI and its associate that is explained by interest and non interest income is 92. 81% ( Rule: for a regression model to be efficient the r-square shall be at least . 6) 3. From the above output we find that Noninterest income had a significant influence on the profits of SBI and its associates over a period of 11 years. Influence of non interest components on profit of SBI& Associate Model Summary Std. Error of the Estimate 4040785. 5 . 981 . 943 5743 a Predictors: (Constant), misc, plland, plexchange, pllinvest, plreav, comm Mode l R 1 . 990(a) Adjusted R Square R Square Coefficients(a) Mode l Standardized Coefficients Unstandardized Coefficients t Sig. B Std.

Error Beta 1 (Constant) 20565743. 52 10099548. 868 -2. 036 . 135 6 comm 2. 109 . 603 1. 153 3. 495 . 040 pllinvest . 970 . 255 . 944 3. 805 . 032 plreav 27. 569 76. 257 . 100 . 362 . 742 plland 76. 158 97. 743 . 221 . 779 . 493 plexchang -1. 077 . 815 -. 135 -1. 322 . 278 e misc -4. 728 2. 151 -1. 042 -2. 198 . 115 a Dependent Variable: profit In the above regression output the independent variable used were various components of non interest income i. e. commission/exchange /brokerage, profit/loss on sale of investment, profit and loss on revaluation of investment, profit/loss on sale of land/building, profit/loss on exchange transaction and miscellaneous income.

And the dependent variable used was the profits of the SBI& associates The objective is to find out that which one of the non interest component had a major influence on the profit of SBI & associates over a period of 11 years. We find the following: 1. The percentage of variation in the profits of the SBI& associates explained by the 6 independent variables is 98. 1% which is significant(as R square shall be more than . 6) 2. We find that commission/exchange/brokerage and profit/loss on sale of investment had a major influence on the profits of the SBI and its associates over a period of 11 years. As they are having a prob values less than . 05(level of significance) and is having a t-stat more than 2. This means that SBI and its associates shall focus more on commission exchange and brokerage for its non interest income.

Contribution of various components of non-interest income of SBI& Associate(94-04) The above pie graph has been prepared by taking into account the average values of non interest income components over a period of 11 years (94-04). From the above graph we find that commission/exchange and brokerage had around 59% (highest) contribution to the non interest income followed by sale of investment (20%). Exchange transaction was having a contribution of 12% and miscellaneous income was having an influence of 9%. The sale of land/buildings, revaluation of investment was having a very negligible influence on the non interest income. Movements of interest and non interest income of SBI & Associates(94-04)

If we look at the movement of interest and non interest income of SBI and associates over a period of 11 years we will find that the non interest income has grown at a CAGR of 18. 46% and the interest income has grown at a CAGR of 13. 15%. The noninterest income over a period of 11 years has grown by 444. 563% whereas interest income has increased by 244. 14% which shows how aggressively the bank is working on its non interest income. Contribution of interest and non interest income of SBI & Associate From the above table we find the contribution of interest and non interest income as a percentage of total income in each of the 11 years period.

We find the share of non interest income has increased over a period of time from 14% to 21% and share of interest income has decreased from 85% to 78%. On an average over a period of 11 years the contribution of non interest income as been 15% and interest income has been 85% to the total income of the SBI and its associates. Correlation between non interest income and total income 0. 935642 There is a very positive correlation between non interest income and the total income of SBI and its associates which shows that higher the non interest income higher the total income of the SBI& associate. Nationalized banks: Public sector banks (Rs‘000)

In the above table we see the following: Column1: Average Column 2: Year Column 3: Other income or the non interest income of the bank Column 4: Commission, exchange and brokerage Column 5: Net profit/loss on sale of investment Column6: Net profit/loss on revaluation of investment Column7: Net profit/loss on sale of land, building and other assets Column 8: Net profit/ loss on exchange transactions Column 9: Miscellaneous income Column 10: Total income of the bank Column 11: Profit/loss of the bank Column 12: Interest income of the bank Column 13: Noninterest income as a percentage of total income Column 14: Interest income as a percentage of total income Influence of interest and non interest income on profits of Public sector banks (94-04)

The above output is of the multiple regression equation where we have tried to find out that how much of the profits of the public sector banks are determined by interest and non interest income. Non interest and Interest income are independent variables and profit is the dependent variable From the above output we find: 1. We find non -interest income to be a significant variable in explaining the profits of public sector banks as the prob value is less the . 05 (. 0268) and the value of t stat is more than 2(2. 7056) [Rule: an independent variable is said to be significant if its prob value is less than . 05(level of significance) or the t-stat is more than 2]. 2.

We find that in our regression model the percentage of variation in the profits of public sector banks that is explained by interest and non interest income is 88. 86%( Rule for a regression model to be efficient the r-square shall be at least . 6) 3. From the above output we find that noninterest income had a significant influence on the profits of public sector banks over a period of 11 years. Influence of non interest components on profit of Public sector banks(94-04) Model Summary Std. Error Mode Adjusted of the l R R Square R Square Estimate 1 14640946. .974(a) . 948 . 870 95589 a Predictors: (Constant), misc, plland, plreav, pllinvest, plexchange, comm. Coefficients(a) Mode l Standardized Coefficients Beta . 024 . 014 -. 348 . 105 . 276 . 470 -1. 453 . 26 . 035 -1. 651 . 763 . 668 . 458 . 220 . 981 . 974 . 174 . 488 . 541 . 671 Unstandardized Coefficients Std. Error 58218744. 505 5. 866 . 478 8. 434 63. 394 8. 910 7. 536 t Sig. B 1 (Constant) -84595095. 339 comm . 151 pllinvest . 017 plreav -13. 928 plland 48. 353 plexchang 5. 954 e misc 3. 451 a Dependent Variable: profit In the above regression output the independent variable used were various components of non interest income i. e. commission/exchange /brokerage, profit/loss on sale of investment, profit and loss on revaluation of investment, profit/loss on sale of land/building, profit/loss on exchange transaction and miscellaneous income.

And the dependent variable used was the profits of the public sector banks The objective is to find out which one of the non interest component had a major influence on the profit of public sector banks over a period of 11 years. We find the following: 1. The percentage of variation in the profits of the public sector banks explained by the 6 independent variables is 94. 8% which is significant(as r square shall be more than . 6) 2. We find that none of the non interest component was individually sufficient in explaining the profits of the public sector banks as we find that none of the non interest component is having a significance value of less than . 5 or having a t-stat of more than 2.

Contribution of various components of non interest income of Public Sector banks (94-04) The above pie graph has been prepared by taking into account the average values of non interest income components over a period of 11 years (94-04). From the above graph we find that commission/exchange and brokerage had around 36% (highest) contribution to the non interest income followed by sale of investment (35%). Miscellaneous income was having a contribution of 16% followed by exchange transaction i. e. 12%. The sale of land/buildings, revaluation of investment was having a very negligible influence on the non interest income. Movements of interest and non interest income of Public sector banks(94-04)

If we look at the movement of interest and non interest income of public sector banks over a period of 11 years we will find that the non interest income has grown at a CAGR of 19. 85% and the interest income has grown at a CAGR of 12. 68%. The noninterest income over a period of 11 years has grown by 511. 87% whereas interest income has increased by 230. 03% which shows how aggressively the bank is working on its non interest income. Contribution of interest and non interest income of the Public Sector banks(94-04) From the above table we find the contribution of interest and non interest income as a percentage of total income in each of the 11 years period. We find the share of non interest income has increased over a period of time from 11% to 20% and share of interest income has decreased from 88% to 79%.

On an average over a period of 11 years the contribution of non interest income as been 13% and interest income has been 87% to the total income of the public sector banks. Correlation between non interest income and total income of Public sector banks 0. 940162 There is a very positive correlation between non interest income and the total income of public sector banks which shows that higher the non interest income higher the total income of the public sector banks. Private sector banks (Rs ‘000) In the above table we see the following: Column1: Average Column 2: Year Column 3: Other income or the non interest income of the bank Column 4: Commission, exchange and brokerage Column 5: Net profit/loss on sale of investment Column6: Net profit/loss on revaluation of investment Column7:

Net profit/loss on sale of land, building and other assets Column 8: Net profit/ loss on exchange transactions Column 9: Miscellaneous income Column 10: Total income of the bank Column 11: Profit/loss of the bank Column 12: Interest income of the bank Column 13: Noninterest income as a percentage of total income Column 14: Interest income as a percentage of total income Influence of interest and non interest income on profits of Private sector banks(94-04) The above output is of the multiple regression equation where we have tried to find out that how much of the profits of the private sector banks are determined by interest and non interest income. Non interest and Interest income are independent variables and profit is the dependent variable From the above output we find: 1. We find non -interest income to be a significant variable in explaining the profits of private sector banks as the prob value is less the . 05 (. 0128) and the value of t stat is more than 2(3. 88) [Rule: an independent variable is said to be significant if its prob value is less than . 05(level of significance) or the t-stat is more than 2]. 2. We find that in our regression model the percentage of variation in the profits of private sector banks that is explained by interest and non interest income is 95. 95 %( Rule for a regression model to be efficient the R-square shall be at least . 6) 3. From the above output we find that noninterest income had a significant influence on the profits of private sector banks over a period of 11 years. Influence of non interest components on profit of Private sector banks (94-04) Model Summary Std.

Error of the Estimate 309483. 83 . 912 . 881 835 a Predictors: (Constant), misc, plreav, plexchange, pllinvest, plland, comm Mode l R 1 . 964 Adjusted R Square R Square Coefficients(a) Mode l Unstandardized Coefficients Std. B Error (Constant) 177724. 775200. 9 748 43 comm . 493 . 252 pllinvest . 623 . 147 plreav 4. 129 2. 209 plland 108. 894 14. 560 plexchang -2. 522 . 513 e misc 3. 314 . 310 Standardized Coefficients Beta -4. 362 . 311 . 672 . 062 . 923 -. 268 1. 114 1. 955 4. 240 1. 869 7. 479 -4. 915 10. 680 . 012 . 122 . 013 . 135 . 002 . 008 . 000 t Sig. 1 In the above regression output the independent variable used were various components of non interest income i. . commission/exchange /brokerage, profit/loss on sale of investment, profit and loss on revaluation of investment, profit/loss on sale of land/building, profit/loss on exchange transaction and miscellaneous income. And the dependent variable used was the profits of the private sector banks The objective to find out which one of the non interest component had a major influence on the profit of private sector banks over a period of 11 years. We find the following: 1. The percentage of variation in the profits of the private sector banks explained by the 6 independent variables is 91. 2% which is significant(as r square shall be more than . 6) 2.

We find that sale of investment , land & building and miscellaneous income and exchange transactions have a major influence on the profits of private sector banks over a period of 11 years as these variable are having a significance level of less than . 05 and a t-stat of more than 2. 3. According to the above output miscellaneous income had a major influence o the profits of the as it’s is having the maximum t-stat i. e. 10. 680 so bank shall focus on it for its non interest income. Contribution of various components of non interest income of Private Sector banks (94-04) The above pie graph has been prepared by taking into account the average values of non interest income components over a period of 11 years (94-04).

From the above graph we find that sale of investment has around 41%(highest) contribution to the non interest income followed by commission/exchange /brokerage 34% followed by miscellaneous income(17%) and exchange transactions 8%. The sale of land/buildings, revaluation of investment was having a very negligible influence on the non interest income. Movements of interest and non interest income of Private Sector banks(94-04) If we look at the movement of interest and non interest income of private sector banks over a period of 11 years we will find that the non interest income has grown at a CAGR of 43. 50% and the interest income has grown at a CAGR of 33. 95%. The non interest income over a period of 11 years has grown by 3604. 74%% whereas interest income has increased by 1760. 4% which shows how aggressively the private sector banks are working on its non interest income. Contribution of interest and non interest income of Private sector banks (94-04) From the above table we find the contribution of interest and non interest income as a percentage of total income in each of the 11 years period. We find the share of non interest income has increased over a period of time from 13% to 23% and share of interest income has decreased from 86% to 76%. On an average over a period of 11 years the contribution of non interest income as been 17% and interest income has been 83% to the total income of the private sector banks. Correlation between non interest income and total income of Private sector banks 0. 87067 There is a very positive correlation between non interest income and the total income of private sector banks which shows that higher the non interest income higher the total income of the private sector banks. Foreign banks (Rs ‘000) In the above table we see the following: Column1: Average Column 2: Year Column 3: Other income or the non interest income of the bank Column 4: Commission, exchange and brokerage Column 5: Net profit/loss on sale of investment Column6: Net profit/loss on revaluation of investment Column7: Net profit/loss on sale of land, building and other assets Column 8: Net profit/ loss on exchange transactions Column 9: Miscellaneous income Column 10: Total income of the bank Column 11: Profit/loss of the bank Column 12: Interest income of the bank Column 13: Noninterest income as a percentage of otal income Column 14: Interest income as a percentage of total income Influence of interest and non interest income on profits of Foreign banks (94-04) The above output is of the multiple regression equation where we have tried to find out that how much of the profits of the foreign banks are determined by interest and non interest income. Non interest and Interest income are independent variables and profit is the dependent variable From the above output we find: 1. We find non -interest income to be a significant variable in explaining the profits of foreign banks as the prob value is less the . 05 (. 0006) and the value of t stat is more than 2(5. 59) [Rule: an independent variable is said to be significant if its prob value is less than . 05(level of significance) or the t-stat is more than 2]. 2. We find that in our regression model the percentage of variation in the profits of foreign banks that is explained by interest and non interest income is 94. 64%( Rule for a regression model to be efficient the r-square shall be at least . 6) From the above output we find that noninterest income had a major and significant influence on the profits of foreign banks over a period of 11 years Influence of non interest components on profit of Foreign banks (94-04) Model Summary Std. Error of the Estimate 891916. 79 . 990 . 75 648 a Predictors: (Constant), misc, plland, plreav, pllinvest, comm, plexchange Mode l R 1 . 995(a) Adjusted R Square R Square Coefficients(a) Standardize d Coefficient Unstandardized Coefficients s B 1 (Constant) 2987693. 345 Std. Error 1103189. 29 7 . 245 . 298 9. 845 5. 393 . 384 . 952 Beta t 2. 708 -. 131 . 158 -. 094 -. 123 . 485 . 580 -. 744 1. 248 -1. 534 -1. 776 2. 101 2. 790 Sig. .054 . 498 . 280 . 200 . 150 . 103 . 049 Mode l comm -. 182 pllinvest . 371 plreav -15. 101 plland -9. 579 plexchang . 808 e misc 2. 657 a Dependent Variable: profit In the above regression output the independent variable used were various components of non interest income i. e. ommission/exchange /brokerage, profit/loss on sale of investment, profit and loss on revaluation of investment, profit/loss on sale of land/building, profit/loss on exchange transaction and miscellaneous income. And the dependent variable used as the profits of the foreign banks The objective is to find out which one of the non interest component had a major influence on the profit of foreign banks over a period of 11 years. We find the following: 1. The percentage of variation in the profits of the foreign banks explained by the 6 independent variables is 99. 0% which is significant(as r square shall be more than . 6) 2. We find that only miscellaneous income have a major influence on the profits of foreign banks over a period of 11 years as it is having a significance level of less than . 05(. 049) and a t-stat of more than 2(2. 790).

Contribution of various components of non interest income of Foreign banks (94-04) The above pie graph has been prepared by taking into account the average values of non interest income components over a period of 11 years (94-04). From the above graph we find that commission/exchange /brokerage was having around 48% (highest) contribution to the non interest income followed by exchange transactions 29%. The contribution of sale of investment was 17% followed by miscellaneous income 6% . The sale of land/buildings, revaluation of investment was having a very negligible influence on the non interest income Movements of interest and non interest income of foreign banks (94-04)

If we look at the movement of interest and non interest income of foreign banks over a period of 11 years we will find that the non interest income has grown at a CAGR of 19. 57% and the interest income has grown at a CAGR of 13. 49%. The non interest income over a period of 11 years has grown by 497. 394%% whereas interest income has increased by 254. 54% which shows how aggressively the bank is working on its non interest income Contribution of interest and non interest income of foreign banks (94-04) From the above table we find the contribution of interest and non interest income as a percentage of total income in each of the 11 years period. We find the share of non interest income has increased over a period of time from 21% to 31% and share of interest income has decreased from 78% to 68%.

On an average over a period of 11 years the contribution of non interest income as been 23% and interest income has been 77% to the total income of the foreign banks. Correlation between non interest income and total income of foreign banks 0. 972437 There is a very positive correlation between non interest income and the total income of private sector banks which shows that higher the non interest income higher the total income of the private sector banks. Findings We have seen that the contribution of non interest income of our banking sector has increased significantly over a period of 11 years. We have also seen that in each type of banks i. e.

SBI, public sector banks, private sector banks and foreign banks the contribution of non interest income towards the total income has increased over a period of time and that of the interest income has decreased over a period of time. If we look at the total banking sector we will find that in our banking system the non interest income is having a significant influence on the profits of the banks. On an average the share of the non interest income towards the total income of the banking sector has increased from 12% in 1994 to 20% in 2004. If we look at the components of non interest income of our banking sector we will find that commission/exchange and brokerage earned by the banks had a major contribution i. e. 4% to the total noninterest income of the bank , after the commission the next big contribution to the non interest income had been of the sale of investments which was 28%, followed by exchange transactions having a share of 15%. Miscellaneous income was having the 13% contribution to the total noninterest income of the banking sector. The contribution of sale of land, revaluation of investments was having a negative or even a negligible influence on the noninterest income of the banking sector. On an average the non interest income of the banking sector has grown at a CAGR of 25% as compared to interest income which has grown at a CAGR of 18%. The percentage increase in the non interest income of the banking sector has increased by 1264. 64% and interest income has increased by 622%.

The private sector banks had seen a significant contribution in the increase of its non interest income over a period of 11 years as compared to other types of banks. Among the various non interest components that had an influence on the profits of the banking sector we find that commission, sale of investment, miscellaneous income had a significant influence on it. We also find that there was a positive correlation between the non interest income and the total income of the banking sector. We also find that in case of public sector banks none of the non interest component was found to be statistically significant enough to influence the profits over a period of 11 years.

Reasons for increase in the non interest income Now if we look at the reason for the increase in the non interest income of the banking sector we will find that it has majorly increased due to following reasons: 1. Increased pressure on net interest margins of the banking sector. 2. With economy growing at an unprecedented rate of 9. 4 per cent during 2006-07 and acceleration in the growth rate being attributable to the buoyancy in the industrial and service sector, the demand for fee-based services of banks has gone up and as a result of which the non interest income has also risen up. 3. Noninterest income is an effective way used by banks to respond to its squeezing margins 4.

At the bank level, greater reliance on noninterest income, particularly trading revenue, is associated with lower risk-adjusted pro? ts attached to it. Challenges involved 1. Not aggressive direct customer interaction of public sector banks. 2. High cost and less expertise involved in launching of innovative products/services as per the customers’ expectations. 3. Technology requirements. Conclusion After studying the non interest growth pattern of the Indian banking sector over a period of 11 years we can say that it is slowly and gradually becoming one of the important avenues for our Indian banks to generate revenue from. In this respect we see that not only private banks and foreign banks are ahead but also our public sector banks are gradually catching it.

We can say that it to be an important source available with our banking sector to respond to the squeezing margins and meeting the shareholders expectations. Literature review 1. Business Efficiency of Public Sector Commercial Banks: A Data Envelopment Approach : Ram Pratap Sinha (2008) The article says that following the nationalization of 20 major commercial banks in 1969 and 1980, the government followed policies of financial repression up to the 1980s. During this period the public sector commercial banks had rapid expansion of branches, especially in the rural and semi urban areas and had reasonable success in the matter of deposit mobilization and disbursement of loans. However, the operating efficiency of public sector commercial banks, declined during the period due to various reasons.

In the 1990s, the banking environment was radically transformed by certain bold initiatives taken by RBI including the dismantling of entry barriers, rate deregulation, introduction of prudential accounting norm and the implementation of Basel I capital adequacy norms. The changed competition and accounting environment compelled the commercial banks to provide unprecedented attention to cost cutting and supplementing fund-based income by fee-based income. 2. Product mix and earnings volatility at commercial bank: evidence from a degree of leverage model: Robert De young & Karin P Roland(1999) The article says that the commercial banks lending and deposit taking business has declined in recent years.

Deregulation and new technology have eroded bank’s comparative advantages and made it easier for non bank competitors to enter these markets. In response, banks have shifted their sales mix towards noninterest income-by selling non bank fee based financial services such as mutual funds, by charging fees for services that used to be bundled together with deposit or loan products . It says that the conventional wisdom in the banking industry is that earnings from fee based products are more stable than loan based earnings and that fee based activities reduce bank risk via diversification. References 1. RBI website 2. Icfai Journal of Banking studies Sept 2008 issue pg 22-26 3. Ideas. repec. org