P: ISSN No. 2231-0045 RNI No.  UPBIL/2012/55438 VOL.- XI , ISSUE- III February  - 2023
E: ISSN No. 2349-9435 Periodic Research
A Comparative Study of the Credit-Deposit Ratio among Northern, North-Eastern, Eastern, Central, Western, and Southern Region Regional Rural Banks of India
Paper Id :  17296   Submission Date :  04/02/2023   Acceptance Date :  22/02/2023   Publication Date :  25/02/2023
This is an open-access research paper/article distributed under the terms of the Creative Commons Attribution 4.0 International, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
For verification of this paper, please visit on http://www.socialresearchfoundation.com/researchtimes.php#8
Balwant Kumar Bari
Assistant Professor
Department Of Applied Economics,
Faculty Of Commerce
Shri Jai Narain Misra P.G. College (K.K.C.),Lucknow, Uttar Pradesh, India
Abstract The purpose of this study was to evaluate and contrast the credit-deposit ratios of the Regional Rural Banks of India located in the Northern, North-Eastern, Eastern, Central, Western, and Southern Regions. Both parametric tests (the ANOVA) and non-parametric tests (the Kruskal-Wallis Test) were utilized in order to carry out a comparison of the credit-deposit ratio amongst the various Regional Rural Banks of India located in the Northern, North-Eastern, Eastern, Central, Western, and Southern Regions. The one-sample Kolmogorov-Smirnov Test was used to determine whether or not the data satisfied the normality criteria before the parametric and non-parametric tests were applied. According to the results of this study, the position of the southern region is in a much stronger position than the position of the eastern region. The credit and deposit information from RRB's financial ledgers were used for the years 2017 to 2021.
Keywords Credit, Deposit, Credit-Deposit Ratio, ANOVA, Kruskal-Wallis.
Introduction
Every nation is aware that a robust banking system is a must for its country's progress in the area of financial growth. The only thing that will make it possible for capable banks to have a positive impact on the augmentation process is a banking system that is efficient and effective. (Goel & Kumar, 2016) It is widely acknowledged that the credit deposit ratio is an important indicator of the degree to which the nation's financial institutions have supported the efforts of the state to advance economically. If a state has a high credit deposit ratio, it indicates that a sizeable portion of its deposits have been put to productive use in a wide range of economic fields, and the state in question has a healthy economy overall. It would be appropriate to keep track, over a period of time, of the growth of credit in order to determine the influence that banks have had on the state's various developmental programs. Financial institutions, which serve as a "financial intermediary," have a significant role to play in the overall improvement of the economic and social climate around the world. The current financial institutions act as financial mediators by providing methods and mechanisms for shifting control over resources from those who have an excess of income over spending to those who may use it to increase the amount of productive capital. In other words, these institutions offer a means of shifting control over resources from those who have an excess of income over spending to those who may use it. (Ibrahim, 2009) In 1980, the Reserve Bank of India (RBI) requested that all public sector banks (PSBs) at rural and semi-urban areas regularly achieve a CDR of 60% in their branches. This was done to encourage the reduction of inter-regional discrepancies in loan distribution and to encourage banks to lend in the same rural and semi-urban areas where they mobilized deposits. Additionally, this was done to encourage banks to lend in the same areas where they mobilized deposits. To address the rural-urban bias that exists in banks' lending portfolios, this objective was presented to financial institutions as "advisory" in both concept and origin. It was never the intention of the CDR to serve as a standard against which to measure the success of PSBs on the municipal, state, or district levels. (Thorat & Wright, 2010) A financial institution's development, particularly the development of commercial banks, can be measured using the credit-deposit ratio. It demonstrates the total amount of credit that financial institutions have extended as a result of the deposits that they have garnered. When the ratio of deposits to loans is high, more deposits are used, which results in interest rates that are as high as they can possibly become. The certificate of deposit (CD) ratio is the primary indicator of the health of a financial institution. A ratio that is excessively high is worrying since it may indicate that there are concerns with capital adequacy, which would force banks to raise extra capital in addition to signalling that there is a strain on the available resources. Inadequate matching of assets and liabilities would also indicate that the balance sheet is unhealthy. It is essential for an economy in the process of development, such as India's, to have a comprehensive financial intermediary system as well as a commercial banking sector that can efficiently collect public savings and distribute credit to sectors that are both productive and demanding in an organized manner. The ability of the economy to maintain healthy levels of growth is largely dependent on the performance of the banking industry in terms of its ability to attract new deposits and distribute credit to other parts of the economy. Therefore, the efficacy and productivity of other economic sectors are determined by the efficiency with which the banking sector operates. (Nayan, 2018) Since the beginning of economics study, scholars have been fascinated by the procyclical nature of the lending practices of financial institutions. This phenomenon is fundamental to the formulation and execution of macroprudential regulation. Financial institutions have a propensity to engage in excessive lending during times of economic expansion, whereas during times of economic contraction, they prefer to tighten their lending standards. In many cases, cyclical responses can be seen in both the quality of loans and the quantity of loans. The pro-cyclical nature of lending and the tendency of financial institutions to take on riskier assets during credit upturns in many industrialized economies were brought to light once again and possibly more strongly than before by the global financial crisis that occurred in 2008. The crisis began in 2008 and lasted until 2010. (Pallavi Chavan, 2017)
Aim of study Based on the background of this study, the objectives are 1. To compare the no of branches among Northern, North-Eastern, Eastern, Central, Western, and Southern Region Regional Rural Banks of India. 3. To compare the Credit-Deposit Ratio among Northern, North-Eastern, Eastern, Central, Western, and Southern Region Regional Rural Banks of India.
Review of Literature

In the earlier research, it was discovered that, in comparison to all the other financial institutions, Andhra Bank has generated a greater number of loan assets from its deposits. The ratios of cash on hand to deposits held by these banks are not significantly different from one another. Andhra Bank excelled above all other financial institutions with regard to the standard credit deposit ratio. (Goel & Kumar, 2016)[1] In a separate piece of research, it was discovered that the ratio of credit to deposits varied greatly from one bank to another as well as between the various regions of the state. In the more developed districts or places, where there has been an increase in credit demand as a result of the many developmental activities that have been carried out, the credit has been absorbed more completely. (Vaz, 1993)[2] The banking industry of the Indian economy is currently considered to be one of the most significant service industries in the economy. Banks operating in both the public and private sectors are almost entirely reliant on interest income, as the fee-based profits they generate from their various services remain very low. As seen by the dropping value of this statistic, it would appear that the PSU banks are slipping behind in terms of the fee-based income they are generating in the current financial environment. This environment is marked by high interest rates. Although it had a fee-based income that was 10% lower than that of private sector banks, the company nevertheless saw a significant 29% growth during the fiscal year 2006–07. The staff, technology, advertising, and provisions for fines are all areas in which banks are required to pay a higher price, in addition to the other escalating costs. As a result, financial institutions like banks are required to generate new sources of revenue, such as income derived from fees. (Ibrahim, 2009)[3] According to the findings of another piece of research, the Central Bank of India has the highest CD ratio among the leading banks. This figure comes in at 36.48 percent, which is lower than the 36.62 percent it had the previous year. Syndicate Bank continues to  hold the highest CD ratio among the other nationalized banks, despite the fact that it has decreased from over 45 percent the year prior to over 41 percent. Therefore, additional research on the CD ratio is required in order to support the smooth mobilization of funds for increased performance in the public sector banking industry. (Kumar, 2013)[4] It was discovered in another study that the ratio of staff expenses to total costs (SE/TE) had a large and positive impact on the return on assets (ROA) and net interest margin (NIM) ratios of the bank. The research conducted on Nepalese commercial banks finds that staff expenses do not have a significant impact on net profits. This data lends credence to the hypothesis that SE and TE have an effect on NIM. The conclusions of this study are limited to the banking business in India; therefore, it is possible that they do not apply to other countries. Because this study focused exclusively on the banking industry in India, the findings could be interpreted differently in other countries. In addition, because it only looked at banking efficiency, it may be encouraged to look at other banking stability dimensions listed by the RBI and how they affect profitability. This is because the study only looked at banking efficiency. (Dsouza et al., 2022)[5] The ratio of interest income to total assets (INTTA) has a very strong positive correlation with the credit deposit ratio (CDR), which indicates that as the CDR rises, the INTTA also tends to climb. This is because the INTTA has a very strong positive association with the CDR. Return on equity (ROE), credit deposit ratio (CDR), operating profit to total assets (OPTA), and net interest margin (NIM) all have a connection with one another that is only mildly unfavourable. (Ramchandani, 2021)[6]

Main Text

1.1  Significance of the Study

This study contributed the existing knowledge of  ratio analysis among Northern, North-Eastern, Eastern, Central, Western, and Southern Region Regional Rural Banks of India. This study will help to understand the no of branches and CD ratio. All the Northern, North-Eastern, Eastern, Central, Western, and Southern Region Regional Rural Banks of India will be benefited and can see the real picture of financial performance in terms of no of branches and CD ratio

Methodology
The experimental study design was utilized in the course of this investigation.
Sampling

The study samples/ data were collected from the secondary data source focusing on the annual report spanning from the years 2017 to 2021 from the RBI website.

Tools Used The one-sample Kolmogorov-Smirnov Test was used to determine whether or not the data satisfied the normality criteria before the parametric and non-parametric tests were applied. Both parametric tests (the ANOVA) and non-parametric tests (the Kruskal-Wallis Test) were used to compare the six regions that make up the Regional Rural Banks of India: The Northern, North-Eastern, Eastern, Central, and Western Regions. The Southern Region Regional Rural Banks of India served as the comparison group. The trend analysis was also utilized in the process of projecting the CD ratio into the future up until the year 2025. The secondary data are all shown in crores. This study looks at four different parameters: the amount of credit in crores, the amount of deposits in crores, the ratio of credit to deposits, and the number of branches in India.
Analysis

In this section, analysis was carried out using SPSS statistical software. The SPSS output are as follows:






Table 1: One-Sample Kolmogorov-Smirnov Test

 

Credit (in Crore)

Deposits (in Crore)

Credit-Deposit Ratio

No of Branches

N

30

30

30

30

Normal Parameters,b

Mean

46432.17

72033.00

59.2500

3646.67

Std. Deviation

34521.695

40999.742

19.82600

2041.110

Most Extreme Differences

Absolute

.149

.149

.157

.186

Positive

.149

.149

.157

.186

Negative

-.135

-.096

-.117

-.160

Test Statistic

.149

.149

.157

.186

Asymp. Sig. (2-tailed)

.086c

.089c

.056c

.010c

a. Test distribution is Normal.

b. Calculated from data.

c. Lilliefors Significance Correction.

Source: SPSS 23.0 version
The significance value for the one-sample Kolmogorov-Smirnov Test was found to be greater than 0.05, indicating that the data for credit (in crores), deposits (in crores), and the credit-deposit ratio are normal. On the other hand, the significance value for number of branches was found to be less than 0.05, indicating that the data for number of branches is not normal. In order to compare the six regions based on the aforementioned criteria, an ANOVA and a Kruskal-Wallis Test were carried out.
Non-Parametric Tests for No of Branches- Kruskal-Wallis Test 
Table 2: Ranks: No of Branches

 

Region

N

Mean Rank

No of Branches

NORTHERN REGION

5

13.00

NORTH-EASTERN REGION

5

3.00

EASTERN REGION

5

18.00

CENTRAL REGION

5

28.00

WESTERN REGION

5

8.00

SOUTHERN REGION

5

23.00

Total

30

 

Source: SPSS 23.0 version
Table 3: Test Statistics,b

 

No of Branches

Chi-Square

28.238

df

5

Asymp. Sig.

.000

a. Kruskal Wallis Test

b. Grouping Variable: Region

Source: SPSS 23.0 version
It is evident from the Kruskal-Wallis Test that the sig. value (0.000) is less than 0.05, which leads to the rejection of the first null hypothesis (H01: There is no significant difference in the number of branches among Northern, North-Eastern, Eastern, Central, Western, and Southern Region Regional Rural Banks of India). As a result of this, it is possible to draw the conclusion that there was a significant difference in the number of branches among Northern, North-Eastern.
Figure 1:Mean  Ranks: No of Branches

 

Source: SPSS 23.0 version

The mean rank plot makes it abundantly evident that the region of India with the lowest number of branches is located in the north-eastern part of the country, while the region in the centre of the country has the highest number of branches.

Parametric Test for Credit-Deposit Ratio-ANOVA

The ratio of deposits to credit might vary from bank to bank; however, when it comes to lending, a larger ratio of deposits to credit of up to 90–100% is preferred.

Table 4: Descriptives: Credit-Deposit Ratio

 

N

Mean

Std. Deviation

Std. Error

95% Confidence Interval for Mean

Minimum

Maximum

Lower Bound

Upper Bound

NORTHERN REGION

5

66.7800

1.35536

.60614

65.0971

68.4629

65.60

68.30

NORTH-EASTERN REGION

5

40.9600

3.47030

1.55197

36.6511

45.2689

37.50

45.40

EASTERN REGION

5

38.0200

1.86199

.83271

35.7080

40.3320

35.70

40.70

CENTRAL REGION

5

53.4200

1.01587

.45431

52.1586

54.6814

52.80

55.20

WESTERN REGION

5

60.1800

2.42012

1.08231

57.1750

63.1850

57.70

63.00

SOUTHERN REGION

5

96.1400

5.33320

2.38508

89.5180

102.7620

87.20

100.70

Total

30

59.2500

19.82600

3.61972

51.8469

66.6531

35.70

100.70

Source: SPSS 23.0 version

Table 5: ANOVA: Credit-Deposit Ratio 

 

Sum of Squares

df

Mean Square

F

Sig.

Between Groups

11188.319

5

2237.664

254.864

.000

Within Groups

210.716

24

8.780

 

 

Total

11399.035

29

 

 

 

In light of the fact that the sig. value (0.000) is lower than 0.05, which can be deduced from the ANOVA table, it is reasonable to conclude that the second null hypothesis should be rejected (H02: There is no significant difference in the credit-deposit ratio among Northern, North-Eastern, Eastern, Central, Western, and Southern Region Regional Rural Banks of India). It is possible to draw the following conclusion as a result: the credit-deposit ratio was significantly different in the Northern, North-Eastern, Eastern, Central, Western, and Southern Regions of the Regional Rural Banks of India.




Figure 2: Credit-Deposit Ratio Mean Plot

 

Source: SPSS 23.0 version

According to the mean plots, the CD Ratio is highest in the southern region (96.1400), while it is lowest in the eastern region (38.0200); as a result, it is possible to draw the conclusion that the position of the southern region is significantly better than the position of the eastern region.

Result and Discussion
The results of the Kolmogorov-Smirnov test on a single sample indicate that the data for credit (in crore), deposits (in crore), and the credit-deposit ratio are normal. On the other hand, the test indicates that the data for the number of branches are not normal because the significance value is less than 0.05. The analysis of variance (ANOVA) and the Kruskal-Wallis’s test are the methods that are utilized in order to compare the six regions with regard to the aforementioned parameters. It is evident from the Kruskal-Wallis Test that the sig value (0.000) is less than 0.05, which means that the first null hypothesis, which states that there is no significant difference in the number of branches between the Northern, North-Eastern, Eastern, Central, Western, and Southern Regions of the Regional Rural Banks of India, cannot be accepted. As a result, one can draw the conclusion that there was a material disparity in the number of branches between the Northern, North-Eastern, Eastern, Central, Western, and Southern Regions of the Regional Rural Banks. The mean ranking plot makes it abundantly clear that the portion of India known as the central part has the highest number of branches, while the section of India known as the north-eastern region has the lowest number of branches. Due to the fact that the sig value (0.000) is less than 0.05, the second null hypothesis, which states that there is no significant difference in the credit-deposit ratio among the Northern, North-Eastern, Eastern, Central, Western, and Southern Region Regional Rural Banks of India, can be safely rejected. 
Findings Accordingly, one can draw the conclusion that the credit-deposit ratio was significantly different in the Northern, North-Eastern, Eastern, Central, Western, and Southern Regions of India's Regional Rural Banks. This is because there was a considerable variance in the number of deposits. According to the mean plots, the CD Ratio is highest in the southern region (96.1400), while it is lowest in the eastern region (38.0200). This suggests that the southern region is in a far better situation than the eastern region.
Conclusion The CD Ratio for the eastern region is the lowest (38.0200), while it is the highest (96.1400) for the southern region. This indicates that the southern region is in a far better situation than the eastern region. The mean ranking plot makes it abundantly clear that the portion of India known as the central part has the highest number of branches, while the section of India known as the north-eastern region has the lowest number of branches.
Limitation of the Study The limitation of this study was the secondary data of no of branches and CD ratio among Northern, North-Eastern, Eastern, Central, Western, and Southern Region Regional Rural Banks of India between 2017 to 2021.
Acknowledgement The author is thankful to the Department of Applied Economics, Faculty of Commerce, Shri Jai Narain Misra P.G. College (K.K.C.) Lucknow – 226001, Uttar Pradesh (India) for proving the infrastructural support like Library, National and Internal Journals, Books, Computer Labs, Internet facilities etc. for conducting this useful research on the Comparative Study of the Credit-Deposit Ratio among Northern, North-Eastern, Eastern, Central, Western, and Southern Region Regional Rural Banks of India.
References
1. Goel, S., & Kumar, R. (2016). Analysis of Cash - Deposit Ratio & Credit Deposit Ratio of Public Sector Banks in India. International Journal of Research in Management, Science & Technology, 4(2), 72–74. 2. Ibrahim, M. S. (2009). Credit Deposit Ratio and Net Interest Margin (Nim) of Indian Commercial Banks – an Analysis. Smart Journal of Business Management Studies, 5(2), 27–38. 3. Thorat, Y. S. P., & Wright, G. A. N. (2010). MicroSave India Focus Note 43. Time, April, 2–3. 4. Nayan, K. (2018). Credit Deposit Ratio of Commercial Banks in India: with special reference to Bihar. International Journal of Creative Research Thoughts (IJCRT), 327–338 5. Pallavi Chavan, L. G. (2017). Bank Lending and Loan Quality : The Case of India. Bank For International Settlements, December. 6. Goel, S., & Kumar, R. (2016). Analysis of Cash - Deposit Ratio & Credit Deposit Ratio of Public Sector Banks in India. International Journal of Research in Management, Science & Technology, 4(2), 72–74. 7. Vaz, I. T. (1993). Credit Deposit Ratio in Uttar Pradesh. Reserve Bank of India. 8. Ibrahim, M. S. (2009). Credit Deposit Ratio and Net Interest Margin (Nim) of Indian Commercial Banks – an Analysis. Smart Journal of Business Management Studies, 5(2), 27–38. 9. Kumar, D. (2013). Performance of banking through credit-deposit ratio in Bihar: A study of last decade. International Journal of Application or Innovation in Engineering & Management, 2(10), 210–218 10. Dsouza, S., Rabbani, M. R., Hawaldar, I. T., & Jain, A. K. (2022). Impact of Bank Efficiency on the Profitability of the Banks in India: An Empirical Analysis Using Panel Data Approach. International Journal of Financial Studies. 11. Ramchandani, K. & K. J. (2021). Impact of Credit Deposit Ratio on Bank Profitability: Evidence from Scheduled Commercial Banks of India. International Journal of Economics, Commerce, and Business Management, 4(4), 183–190.