An Analysis the Return and Efficiency Financial Analysis of Indian Banking Sector

One of the oldest financial organizations, banking has been around for as long as human civilization has existed. The roots go back to long ago. A country's banking system has a significant role in its economic development. These days, no modern society could function without banking institutions. It is crucial to a country's economic growth. Collecting deposits from customers & allocating them to the most profitable sector are the fundamental functions of a bank (Dufera, 2010). Any business that accepts deposits, processes them, transfers them, pays them, lends them out, invests in them, deals with them, exchanges them, and provides services related to banking (such as trusteeship, agency, custodianship, etc.).

Major changes to India's banking industry began over twenty years ago, but only now are its fruits bearing fruit. There were significant shifts in the Indian banking industry as a result of liberalization, privatization, & globalization policies. As the backbone of the economy, the banking sector is widely believed to be the most crucial when it comes to reforms in the financial sector. A more competitive, adaptable, efficient, & productive banking industry that follows international standards and is free from government direction and control was the goal of the reforms. Economic reforms in India have caused enormous change in the banking sector. Although it was a component of broader economic reforms, it fundamentally altered how banks in India operate. This reform has had a lasting impact on the functioning of India's banking system and has affected the efficiency of numerous Indian banks.

To evaluate the returns and efficiency of the Indian banks.

An approach to systematically gathering and analysing data in order to draw valid conclusions on significant and relevant topics. "Research" further means "the search for knowledge." Research, in fact, is the practice of scientific inquiry at its finest. The study's objective is to look at how various public and private banks are doing financially.

Sources of Data

The empirical nature of both micro and macro phenomena will be explored in this study. The majority of the information used in this study was culled from previously published works, such as scholarly publications and internet databases. The data utilized to create this report was sourced from the following places: RBI, BSE, NSE, SEBI, moneycontrol.com, and the websites of chosen financial companies. The banking industry's journals and publications will form the backbone of this study. Additional data that will be helpful to the study comes from a variety of websites that are relevant to the banking business. Articles from newspapers, journals, & publications were also utilised, in addition to survey data.

Period of the Study

This study covers a decade's worth of data, from 2010–2011 to 2019–2020, and it uses both descriptive and analytical methods. The data will be utilized to draw conclusions when a long period of time has passed.

Sample Design

The process of selecting a representative subset of a larger population is known as a sample design. Methodology describes the steps a researcher would take to choose things for a sample. Prior to data collection, the sample design is established. Stratified random sampling, a proportionate sampling method, will be used for this study.

Sampling

The term "sample size" describes the amount of data points taken from a larger population. Sixteen of the thirty-seven public and private banks that submitted applications will participate in our study. Banks were classified as large, medium, or small according to the amount of deposits and advances in the respective industry. Applying both criteria, 9 PSBs, 4 OPSBs, and 3 NPSBs will be chosen.

In the previous chapter on the bases of 15 composite ratios (which are useful for studying various aspects of performance the banking sector) the variance or disparity in various aspects of performance in the m companies over the entire period has been carried. In same maimer, is the 15 sections to follow, the ANOVA for the difference or variation in performance of banking sector of India in the 10 years (2010-11to 2019-20) have been carried.

Return Ratios: -

Sixteen of the thirty-seven public and private banks that submitted applications will participate in our study. Banks were classified as large, medium, or small according to the amount of deposits and advances in the respective industry.

Return on Net worth Ratio

ANOVA for composite return on net worth ratios of the Indian banking sector in the years of the decade.

Using the data on composite return on net worth ratios provided in the following table, an ANOVA was conducted for the sample banks of the Indian banking sector under consideration in this part.

Table 1: Composite Return on Net Worth

Table 2: (Composite Return on Net worth)

Table 3: (Composite Return on Net worth)

Table no: - 2 displays comprehensive statistics pertaining to the ANOVA. The sum of square, degree of freedom, and mean sum of square for both within & between years are provided in table no: - 3. Using the F-test, one can test the hypothesis using the ANOVA process. The F-test and its associated p-value are displayed in the ANOVA table. A p-value of 0.40 and an F-value of 1.06.

·        Return on Assets Ratio

Statistical analysis of variance for the composite return on assets ratio of the Indian banking sector across the decade.

In this part, we use the data on composite ROA ratio provided in the following table to conduct an ANOVA for the sample banks of the Indian banking sector that are under research.

Table 4: Composite Return on Assets

Table 5: Composite Return on Assets

Table 6: Composite Return on Assets

For further information on the ANOVA, see Table no: - 5. For both years within and between, the sum of square, degree of freedom, & mean sum of square are provided in table no. 6. Using the F-test, one can test the hypothesis using the ANOVA process. The ANOVA table displays the computed F-test value along with the matching p-value. The significance level was found to be 0.31 with an F-value of 1.19.

Efficiency ratios:-

·     Income on Assets Ratio

An analysis of variance for the banking sector's composite income-on-assets ratios across the decade in India.

The following table contains the data on income on assets ratio that was used to conduct the ANOVA for the composite ratios of the sample banks in the Indian banking sector that were under research during the last ten years.

Table 7: Composite Income on Assets Ratios

Table 8: Composite Income on Assets

Table 9: Composite Income on Assets

The ANOVA-related statistics are displayed in Table no: - 8. The degree of freedom, mean sum of square, and sum of square for both within and between years are provided in Table no. 9. Using the F-test, one can test the hypothesis using the ANOVA process. The ANOVA table displays the computed F-test value along with the matching p-value. A p-value of 0.10 and an F-value of 1.69.

·          Wage Bills Ratio

ANOVA for composite wage bills ratio of the Indian banking sector in the years of the decade.

This section presents the results of an ANOVA for the composite wage bills ratio using the data from the following table. The sample banks in the Indian banking sector were used for the analysis.

Table 10: Composite Wage Bills Ratios

Table 11: Wage Ratios

Table 12: Wage Ratios

The results of the ANOVA & trend analysis are congruent in this instance. The composite salary bills ratio of the Indian banking sector did not change significantly over the research period. The trend study states that there are three types of banks: public, old private, & new private sector.

TREND ANALYSIS OF VARIOUS RATIOS OF PUBLIC SECTOR BANKS

Composite Return on Net worth Ratio (Public Sector Banks)

The following section calculates the banking sector's composite return on net worth ratio for the 10 year study period using the return on net worth ratio of the individual institutions. This ratio is shown in the table that follows.

Table 13: Actual Composite Return on Net Worth Ratios

The results of the trend detection test shown above indicate the absence of a trend. Based on the results of the linear regression line fitting, we can conclude that the model does not provide a satisfactory fit (Mann-Kendall Statistic = -17, p-value = 0.071). This leads us to believe that the 2nd degree polynomial equation is statistically significant, since we obtain an R2 value of 0.92 and a p-value of 0.0001 when we attempt to fit it to the series. In this case, the return on net worth can be described by a quadratic equation.

Composite Return on Assets Ratio (Public Sector Banks)

In the present section, we calculate the banking sector's composite return on assets ratio during the study period of 10 years using the individual banks' return on assets ratios. This ratio is shown in the table that follows.

Table 14: Actual and Estimated Composite Return on Assets Ratios

Efficiency Ratios

Two efficiency-related ratio trends are presented in this section:

Income on Assets Ratio (Public Sector Banks)

For the period of 10 years covered by this section, we may calculate the banking sector's composite income on assets ratio by adding together the individual banks' income on assets ratios. This ratio is shown in the table that follows.

Table 15: Actual Composite Income on Assets Ratios

We checked significance of income on assets ratio using Mann-Kendall test and found that Mann Kendall Statistic is 13 with p-value 0.13, which is greater than pre-defined significant level α=0.05. So we not reject Ho and conclude that there is no significant trend in composite income on assets ratio and we cannot fit linear model on it.

Composite Wage Bills Ratio (Public Sector Banks)

Here we derive the banking sector's composite wage bills ratio for the ten-year study period from the individual banks' wage bills ratios. This ratio is shown in the table that follows.

Table 16: Actual and Estimated Composite Wage Bills Ratios

TREND ANALYSIS OF VARIOUS RATIOS OF OLD PRIVATE SECTOR BANKS

Return Ratios

Here we see the development of two ratios pertaining to returns,

Composite Return on Net worth Ratio (Old Private Sector Banks)

This part calculates the banking sector's composite return on net worth ratio for the 10 year study period using the return on net worth ratio of the individual institutions. This ratio is shown in the table that follows.

Table 17: Actual and Estimated Composite Return on Net worth

Applying the Mann-Kendall test, we determined that the return on net worth ratio is statistically significant (with a Mann Kendall statistic of -21 & a p-value of 0.033), which is less than the pre-defined criterion of significance (α=0.05).

Composite Returns on Assets Ratio (Old Private Sector Banks)

In this part, we calculate the banking sector's composite return on assets ratio during the study period of 10 years using the individual banks' return on assets ratios. This ratio is shown in the table that follows.

Table 18: Actual Composite Return on Assets

Efficiency Ratios

Two efficiency-related ratio trends are presented in this section: 

Income on Assets Ratio (Old Private Sector Banks)

For the period of 10 years covered by this section, we may calculate the banking sector's composite income on assets ratio by adding together the individual banks' income on assets ratios. This ratio is shown in the table that follows.

Table 19: Actual and Estimated Composite Income on Assets Ratios

Our analysis of the income-to-assets ratio was conducted using the Mann-Kendall test. The results showed that the Mann Kendall Statistic was 25, and the p-value was 0.013, which is lower than the pre-defined criterion of significance, α=0.05. The results of the trend detection test shown above indicate an increasing trend. The R2 value is 0.61 & p-value is 0.008, both of which are below the pre-defined significant level α=0.05, as we obtained by fitting a linear regression line. The conclusion that the line fits well follows.

Composite Wage Bills Ratio (Old Private Sector Banks)

For the 10 years that followed covered by this section, we can calculate the composite wage bills ratio of the bailing industry by slicing the wage bills ratio of the banks. This ratio is shown in the table that follows.

Table 20: Actual and Estimated Composite Wage Bills Ratios

Applying the Mann-Kendall test, we determined that the wage bills ratio is statistically significant with a Mann Kendall statistic of 3, p-value of 0.41, that is higher than the pre-defined level of significance α=0.05. 

TREND ANALYSIS OF VARIOUS RATIOS OF NEW PRIVATE SECTOR BANKS

Composite Return on Net worth Ratio (New Private Sector Banks)

This section calculates the banking sector's composite return on net worth ratio for the 10-year study period using the return on net worth ratio of the individual institutions. This ratio is shown in the table that follows.

Table 21: Actual and Estimated Composite Return on Net worth

Our analysis of the return on net worth ratio's significance was conducted using the Mann-Kendall test. The results showed that the Mann Kendall Statistic was 25, and the p-value was 0.013, which is lower than the pre-defined level of significance, Έ=0.05. The results of the trend detection test shown above indicate an increasing trend. The R2 value of 0.59 & p-value of 0.009, which are smaller than the pre-defined significant level α=0.05, are obtained from the fitted linear regression line. The conclusion that the line fits well follows.

Composite Returns on Assets Ratio (New Private Sector Banks)

In this section. we calculate the banking sector's composite ROA ratio during the study period of 10 years using the individual banks' ROA ratios. This ratio is shown in the table that follows.

Table 22: Actual and Estimated Composite Return on Assets Ratios

We used the Mann-Kendall test to determine if the ROA ratio was statistically significant & discovered that the Mann Kendall statistic was 33 with a p-value of 0.001, which is lower than the pre-established significance criterion of α-0.05. The results of the trend detection test shown above indicate an increasing trend. R=0.86, with a p-value of 0.001, is less than the pre-defined significant level α=0.05, as obtained from the fitted linear regression line.

Income on Assets Ratio (New Private Sector Banks)

For the 10 years covered by this section, we may calculate the banking sector's composite income on assets ratio by adding together the individual banks' income on assets ratios. This ratio is shown in the table that follows.

Table 23: Actual Income on Assets Ratios

Applying the Mann-Kendall test, we determined that the income-to-assets ratio is statistically significant, & Mann Kendall Statistic is 9, with a p-value of 0.226, which is higher than the pre-defined criterion of significance, α=0.05.

Composite Wage Bills Ratio (New Private Sector Banks)

In this part, we derive the banking sector's composite wage bills ratio for the 10-year period under consideration from the banks' wage bills ratios. This ratio is shown in the table that follows.

Table 24: Actual and Estimated Composite Wage Bills Ratios

The results of the trend detection test shown above indicate the absence of a trend. We can conclude that the model does not provide a good fit because the Mann-Kendall Statistic is -15 and the p-value is 0.099, as seen by the fitted linear regression line. As a result, we attempt to fit a 2nd degree polynomial equation to the series; the results show that the fit is significant, with an R2 value of 0.89 & p-value of 0.0004. In this case, the wage bills ratio can be fit using a quadratic equation.

This study examines the financial statements of 16 representative banks that operate within India's banking sector from 2010–2011 through 2019–2020. Of these, 9 are public sector banks, 4 are former private sector banks, and 3 are new private sector banks. Data from the Reserve Bank of India's websites and the annual reports of the participating banks were used to calculate fifteen key ratios pertaining to efficiency & return. Composite return on net worth ratios in the sample banks varied significantly over the study period, but these ratios did not vary significantly across the Indian banking sector's annual composite returns on net worth. Public sector banks are seeing a combined decline in both return on net worth and ROA ratios, whilst older private sector banks are seeing a negative trend in RONR but no trend in ROAR. New private sector banks are showing a good trend in both ratios. In terms of resource utilisation, both PSBs & OPSBs were inefficient. Therefore, these areas should prioritise making the most efficient use of available resources.