The Chartered Accountant • Journal of ICAI December 2021 • Vol. 70 • No. 6 • pp. 101–106 (Journal pp. 745–750)
BANKING & FINANCE • EMPIRICAL CREDIT RISK ANALYSIS

Is the Size of a Bank a Credit Risk Variable? A Study on Indian Public Sector Commercial Banks

Dr. Renu Arora (Faculty, Mata Sundri College for Women, University of Delhi)

Author is a faculty in Mata Sundri College for Women, DU. She can be reached at 28.renuaroroa@gmail.com and eboard@icai.in.

1. Introduction: Consolidation Wave & The Bank Size Hypothesis

For the last five years, the Finance Minister of the Government of India is announcing mergers/consolidation of small public sector banks (PSBs) with a few large public sector banks and even the privatization of few of these banks. This consolidation of Indian PSBs is aimed at finally four large PSBs only. Reasons are efficient banking, reaping benefits of large-scale banking, reducing overlap of banking services in local areas; and the very important reason of managing poor asset quality and low capital adequacy ratios in the small PSBs.

The mounting pile of non-performing assets which has considerably reduced the credit growth in PSBs, gives perceptions of whether the size of a public sector bank is a credit risk variable in real sense. This study researches this phenomenon of impact of size of an Indian public sector bank on efficiency of its credit risk determinants– GNPA and NNPA ratios, Restructured Assets Ratios, Stressed Assets Ratios, Sensitive Assets Ratios, Capital Adequacy Ratios, Net Interest Margin and Return on Assets, from 2006 to 2017. The year 2017 has been selected being the concluding year when merger and consolidation exercise begins with Associate Banks of State Bank of India merged into the State Bank of India on 01 April, 2017. From April 1, 2020, ten PSBs were amalgamated into four, taking the total number to 12 (The Business Standard, 2021, February, 03).

The present study into the impact of the size of the PSBs on their credit risk management (CRM) efficiency has been organized in five sections. The next section reviews the existing literature, section 3 and 4 are on the framework of study and data analysis. Last section concludes and recommends.

2. Review of Literature

The most immediate challenge for banks worldwide is a possible rise in corporate insolvencies and non-performing assets (NPLs) (RBI, 2021- Financial Stability Report, July). To achieve banking stability, banks are required to maintain quality assets that aid in achieving profitability (Swamy, 2015). The growing incidence of poor bank asset quality calls for a renewed look at the factors that impact the performance of banks (Swamy, 2015). One such factor of interest is size of a bank. The empirical analysis suggests that asset measure of size could yield meaningful results relating to borrowers’ loan response (Ranjan and Dhal, 2003).

Large v. Small Banks: Empirical Evidence

Larger banks have exhibited better credit risk management with lower NPA levels (Swamy, 2015). There are other studies as well. Chronologically, we start with Ranjan & Dhal (2003). Ranjan & Dhal (2003) had studied NPAs of Indian PSBs from 1990 to 2003. According to them, the bank size measured in terms of assets, has negative impact on NPAs, while the measure of bank size in terms of capital has positive and significant effect on gross NPAs but negligible effect on net NPAs (Ranjan & Dhal, 2003). Thus, appropriate measure of size assumes importance (Ranjan & Dhal, 2003).

Nair, Gopikumar & Asha (2018) studied 50 Indian banks, both in public and private sector from 2006-17, the same period as discussed in this paper, to research the “effect of size, capitalization and non-performing assets on the cost efficiency of Indian banks” (Nair, Gopikumar & Asha, 2018). They concluded that “Bank capitalization contributes negatively whereas, bank size contributes positively to bank’s cost efficiency” (Nair, Gopikumar & Asha, 2018). Their paper uses cost-function approach for estimating and modeling inefficiency (Nair, Gopikumar & Asha, 2018).

Sarkar & Sarkar’s (2018), “empirical analysis suggests that while board size plays an insignificant role in bank outcomes, board independence plays a significant role”. They favor privatization of banking services for enhanced efficiency.

However, empirical studies on a sample of 47 public and private Indian commercial banks from 2000-14, Arrawatia et al. (2019) find that “the results are qualitatively similar across different ownership structures”. They suggest that forecasting models for nonperforming assets should also consider macro-economic and industry-specific factors along with the bank-specific factors (Arrawatia et al., 2019). One such bank-specific factor is the size of the bank.

Gupta, Mahakud & McMillan (2020) analyzed 64 public, private and foreign banks in India from 1998-2016 and “focuses on assessing the role of various bank-specific, industry-specific and macroeconomic determinants in Indian commercial banks performance” (Gupta, Mahakud & McMillan, 2020). The results show that bank size, nonperforming loan ratio and revenue diversification are the major determinants of the commercial banks performance in India (Gupta, Mahakud & McMillan, 2020). The larger banks are less profitable (Gupta, Mahakud & McMillan, 2020).

The Effect of Merger & Consolidation

Gandhi (2016), the Deputy Governor, RBI stated, “It has been argued that India has too many PSBs with similar characteristics and a consolidation among PSBs can result in reaping rich benefits of economies of scale and scope”. Though, he also argued in favor of consolidation beyond mergers. “The merged entities can now reap benefits of synergy, especially in the case of branch network presence across regions. For example, United Bank of India, which had a large presence in the eastern region, will now benefit from the more diversified branch network of Punjab National Bank which had a vast network in the northern and central region before the merger” (Reserve Bank of India, 2020- Trends & Progress of Banking in India).

The Press Information Bureau, GOI (2020) informed, “Amalgamation to enable creation of digitally driven consolidated banks with global heft and business synergies…greater scale and synergy through consolidation would lead to cost benefits which should enable the PSBs enhance their competitiveness and positively impact the Indian banking system”.

Further, positive outlook was reported by the New Indian Express on 03 August, 2021, though in contrast, its headline was not very encouraging. It reported “Post-merger, public sector banks (PSBs) have seen an improvement in profitability in the year ended March 2021 despite the coronavirus pandemic induced disruptions… In FY21, PSBs reported a combined net profit for the first time in five years… Only two of the 12 public sector banks — Punjab & Sind Bank and Central Bank of India — reported a net loss for the year” (The New Indian Express, 2020).

Mergers helped strengthen the capital buffers of banks that were facing challenges in meeting regulatory requirements (Reserve Bank of India, 2020- Trends & Progress of Banking in India). United Bank of India had pre-merger Capital Adequacy Ratio of 5.6 per cent only against the minimum required of 9 per cent under RBI prudential norms. Post-merger, the combined ratio of Punjab National Bank merged with Oriental Bank of Commerce and United Bank of India stood at 12.63 per cent (Reserve Bank of India, 2020- Trends & Progress of Banking in India, Table 3, p.58).

The divergent views are also there. In the loans and advances, the PSB market share has gone down to around 60 per cent with the scaling up of private banks (Business Today. In, 2021). With new banks including small finance banks (SFBs) offering higher deposit rates, the deposit share of PSBs may also come under attack (Business Today. In, 2021). In the banks’ consolidation process, the human resource factor has also been underlined to be worst affected and requires upskilling, as per experts on banking and legislators. The mega merger of public sector banks (PSBs) has led to a “turmoil” as the state-owned banks do not have the necessary talent for specialised functions like risk management and new financial technologies, the Parliamentary Standing Committee on Finance said in its report (The Business Standard, 2021, February, 03).

3. Research Objective & Framework of the Study

In the background of these studies, this paper sets the research objective to empirically evaluate the historical and primary data on PSBs to research whether the size of a public sector bank is a significant credit risk determinant. Efficient credit risk management ensures high profitability as loans and advances are banks’ primary source of income.

Sample Selection & Size Classification Criteria (2006–2017)

In a study from 2006-2017, immediately before the start of large size merger and consolidation of Indian PSBs, based on historical data; and also based on the primary survey on 337 credit and risk managers of 12 of such PSBs, the author finds that the size of the bank is a credit risk variable.

Large and small PSBs in the study were segregated on the basis of share of assets of a PSB in total assets of all the PSBs in the median year of study, i.e., 2012, with a cut-off percentage of 2.5%. A sample of six large and six small PSBs was drawn:

  • Six Large PSBs: State Bank of India, Punjab National Bank, Bank of Baroda, Oriental Bank of Commerce, IDBI Bank, and Syndicate Bank.
  • Six Small PSBs: Punjab & Sind Bank, Dena Bank, Vijaya Bank, United Bank of India, Andhra Bank, and State Bank of Bikaner & Jaipur (SBBJ).

In case we tally the consolidation exercise of this merger of large PSBs with small PSBs, most of the small PSBs in the sample have either merged or will be merged with large banks. For example, State Bank of Bikaner and Jaipur along with other SBI associate banks merged with the State Bank of India (SBI). Dena Bank and Vijaya Bank were merged with Bank of Baroda in 2019 (Sikdar, 2021). In the recent past, the government handed over the IDBI Bank to LIC (Business Today. In, 2021). After the merger exercise, Punjab National Bank, Oriental Bank of Commerce, and United Bank of India combined to form one lender; Canara Bank took over Syndicate Bank; while Union Bank of India amalgamated with Andhra Bank and Corporation Bank (The Business Standard, 2021, February, 03).

4. Empirical Data Analysis & Results

The historical data on this study was collected for six large and six small PSBs from 2006-2017 from the Statistical Tables relating to Banks in India (RBI). The credit risk variables under the study are:

  • GNPA Ratio: Gross Non-performing Assets to Gross Advances.
  • NNPA Ratio: Net Non-performing Assets to Net Advances.
  • Sensitive Assets Ratio: Covers advances to capital/commodity market brokers and real estate advances.
  • Stressed Assets Ratio: Takes GNPAs plus restructured loans to Total Advances.
  • NIM (Net Interest Margin) & ROA (Return on Assets): Profitability ratios, used to measure the effect of credit risk variables on operational efficiency.
  • CRAR: Capital to Risk Adjusted Assets Ratio, famously known as Capital Adequacy Ratio.

“NIM (Net Interest Margin) and ROA (Return on Assets) are profitability ratios, used to measure the effect of credit risk variables on operational efficiency. CRAR is Capital to Risk Adjusted Assets Ratio and famously known as Capital Adequacy Ratio.”

During the periods from 2006-17, the large PSBs have been better capitalized than the small PSBs. Though GNPA ratio is higher in large PSBs, the Stressed Assets Ratio is highly stressed in small PSBs, the real indicator of credit risk stress. Loans to sensitive sectors, is also a great discomfort factor setting high cautions. This is a highly remunerative loan segment but in case of defaults, can create a big pile of bad loans, which happened for IDBI Bank and Vijaya Bank.

Table 1: Mean (%) & SD Values of Credit Risk Variables in Sample PSBs (2006-17)

Sl. No. Credit Risk Ratios Large PSBs Mean % (S.D.) Small PSBs Mean % (S.D.)
1. GNPA Ratio 4.39 (3.29) 4.24 (3.31)
2. NNPA Ratio 2.31 (2.08) 2.59 (2.45)
3. Sensitive Assets Ratio 17.38 (1.82) 15.91 (3.09)
4. Restructured Debt Ratio 4.01 (2.48) 4.65 (3.28)
5. Stressed Assets Ratio 8.51 (4.71) 9.00 (5.71)
6. NIM (Net Interest Margin) 2.37 (0.35) 2.45 (0.41)
7. ROA (Return on Assets) 0.65 (0.50) 0.63 (0.42)
8. CRAR (Capital Adequacy Ratio) 12.65 (0.82) 12.13 (1.03)

(Source: Author’s analytical studies based on RBI’s Statistical Tables related to Banks in India, 2006-17, http://rbidocs.rbi.org.in)

Figure 1 Visualization Context: Figure 1 illustrates comparative mean and standard deviation dispersions across all 8 credit risk parameters between large and small PSBs, highlighting greater volatility and stress burdens among smaller banking institutions.

When we measure year-wise movement of these ratios (Table 2), the highest stress is appearing in 2015-16 and 2016-17, putting the regulator and policy makers on toes to control state run banking, and one such measure adopted was merger and consolidation of small PSBs into large PSBs.

Table 2: Year-wise Mean and Growth Rate Values for Credit Risk Ratios (in %)

YEAR GNPA Ratio
Mean / GR
NNPA Ratio
Mean / GR
Sensitive Assets
Mean / GR
Restructured Debt
Mean / GR
Stressed Assets
Mean / GR
NIM
Mean / GR
ROA
Mean / GR
CRAR
Mean / GR
2006-07 2.75
-
0.94
-
18.38
-
0.64
-
3.43
-
2.83
-
0.93
-
12.19
-
2007-08 2.05
-25.5
0.84
-10.5
18.29
-0.51
0.85
32.51
2.94
-14.3
2.89
-19.3
0.97
4.4
11.97
-1.76
2008-09 1.74
-15.0
0.74
-12.2
16.56
-9.43
2.73
223.2
4.33
47.28
2.24
-2.08
0.92
-5.25
13.35
11.46
2009-10 1.91
9.71
0.92
24.77
16.17
-2.35
3.51
28.32
5.16
19.3
2.25
0.60
0.94
2.36
13.07
-2.05
2010-11 2.05
7.41
0.98
6.23
16.49
1.95
2.75
-21.6
4.84
-6.26
2.77
-23.25
0.96
1.95
13.26
1.47
2011-12 2.79
36.05
1.43
45.54
15.10
-8.42
4.44
61.47
7.16
47.91
2.71
-2.34
0.91
-5.3
13.18
-0.65
2012-13 3.23
15.61
1.90
32.98
15.07
-0.18
7.20
62.27
10.49
46.52
2.51
-7.32
0.79
-12.5
12.30
-6.7
2013-14 4.56
41.3
2.84
49.69
16.52
9.6
7.62
5.81
12.29
17.18
2.38
-5.18
0.43
-45.8
11.97
-2.65
2014-15 5.05
10.8
3.10
9.0
15.12
-8.48
9.01
18.25
14.19
15.47
2.21
-7.18
0.41
-5.03
11.96
-0.08
2015-16 8.83
74.76
5.37
73.23
17.39
15.04
5.39
-40.2
15.59
9.88
2.21
-0.19
-0.17
-141.0
11.56
-3.32
2016-17 12.50
41.5
7.86
46.4
17.99
3.43
3.50
-35.0
15.53
-0.43
2.09
-5.06
-0.16
-7.43
11.59
0.223
Total Mean
(2006-17)
4.32 2.45 16.64 4.33 8.72 2.41 0.63 12.40

(Source: Author’s analytical studies based on RBI’s Statistical Tables related to Banks in India, 2006-17, http://rbidocs.rbi.org.in)

Bank-Wise Stress Disparities (Figure 2 Context):

Bank-wise analyses for 2006-17 (Figure 2), demarcates that the IDBI bank was under severe pressure of credit risk among large banks, and Punjab & Sind Bank, Dena Bank, United Bank of India and Andhra Bank in credit risk turmoil. IDBI Bank has since been privatized and placed under the control of LIC of India.

5. Primary Survey Findings on 337 Credit & Risk Managers

The survey results from a structured questionnaire, which was placed on 337 credit risk professionals in the sampled 12 PSBs, has found a higher level of disintegrated systems and processes, inconsistencies in risk management practices, more subjective risk assessments, lower degree of site inspections and reduced sharing of risk information across multiple lending arrangements in smaller PSBs.

Infrastructure Vulnerabilities Identified in Small PSBs

The respondent credit managers of small PSBs also find that their banks have larger gaps in risk infrastructure than in the large PSBs. Risk Infrastructure includes: data analytical capabilities, staff trainings, IT management, industry studies etc.

6. Conclusions & Policy Recommendations

The problem of managing asset quality in PSBs is grave. RBI repealed all restructuring schemes for commercial bank loans from February, 2018 though for COVID-19 period defaults, restructuring with added strictures has been provided. Indiscriminate rescheduling and restructuring of stressed loans has been found to be the major reason for piling up of bad loans in PSBs.

“The problem of managing asset quality in PSBs is grave. RBI repealed all restructuring schemes for commercial bank loans from February, 2018 though for COVID-19 period defaults, restructuring with added strictures has been provided.”

Moreover, after the buffer provided through suspension of Insolvency and Bankruptcy Code, 2016 for COVID-19 defaults has ended, serious asset quality deterioration will surface, even for large consolidated PSBs. RBI admits that “The modest GNPA ratio of 7.5 per cent at end- September 2020 veils the strong undercurrent of slippage” (RBI, 2020- Trends & Progress of Banking in India).

“Presently, the consolidation in state run banking has improved the capital adequacy ratios and Net Interest Margin. Their financial results for the next two three years will provide more foresight.”

Presently, the consolidation in state run banking has improved the capital adequacy ratios and Net Interest Margin. Their financial results for the next two three years will provide more foresight. Along with consolidation, segmentation in banking both in public and private sectors, with differentiated banking services, for example payment banking, wholesale banking, infrastructure banking, global banking, may enhance the core competencies in banking services.

Crucial Area of Caution – SME Credit Safeguards:

Though, one area of caution remains. Large banks tend to lend to large firms and small banks only tend to small firms (Mkhaiber & Werner, 2021). In India, where small and medium enterprises play a pivotal role in economic growth, sufficient funding for this sector has to be ensured even with consolidation of PSBs in mega global banks.

References

  1. Arrawatia, R. et al. (2019), ‘Asset Quality Determinants of Indian Banks: Empirical Evidence and Policy Issues’, Journal of Public Affairs-An International Journal, pp. 1-11, [Online], Wiley Online Library, http://doi.org/10.1002/pa.1937
  2. Business Today.In. (2021), “Banking Preview 2021: Consolidation, Privatisation among 5 Themes to Watch Out For”, August 03, http://www.businesstoday.in/industry
  3. Gandhi, R. (2016), “Consolidation among Public Sector Banks”, Speech, Mint South Banking Enclave, 22 April, Bangalore, RBI Bulletin May, http://rbidocs.rbi.org.in
  4. Gupta, N., Mahakud, J., & McMillan, D. (2020), “Ownership, Bank Size, Capitalization and Bank Performance: Evidence from India”, Cogent Economics & Finance, August, pp. 1-24, http://doi.org/10.1080/23322039.2020.1808282
  5. Mkhaiber, A. & Werner, R.A. (2021), “The Relationship between Bank Size and Propensity to Lend to Small Firms: New Empirical Evidence from a Large Sample”, Journal of International Money and Finance, Vol. 110, http://doi.org/10.1016/j.jimonfin.2020.102281
  6. Nair, S., Gopikumar, V. & Asha, V. (2018), ‘An Empirical Analysis of Banking Sector Efficiency in Emerging Economies’, International Journal of Pure and Applied Mathematics, Vol. 118 No 9, pp. 467-483, http://www.ijpam.eu