Commercial banks in India are well regulated. The Indian banking system has several inherent strengths, the most
important being that the banks are well capitalised both in terms of quantity and quality of capital. Their funding
structure is stable as they are largely reliant on domestic retail deposits. Their assets are well diversified and leverage
is low. Despite these strengths, the Indian banking system faces certain headwinds. A slowing economy has raised the
extent of delinquencies in a short period of time. However, profitability has been sustained in recent quarters. Deposit
growth has lagged credit expansion for several quarters now and the composition of outside liabilities has been shifting
toward big ticket short term deposits from corporate and high net worth individuals, exposing the banks to liquidity
stress as it increases reliance on wholesale sources of funds. However, the resilience of the banking system to credit,
interest rate, equity and foreign exchange shocks remain satisfactory.
The financial performance of non-banking financial companies and urban cooperative banks has been improving
over the years and their leverage as well as maturity mismatches are being monitored. The inter-linkages among
these diverse sectors of the financial system are strong implying that the interconnectedness of the domestic financial
system will have to be closely monitored.
Risks to the Banking Sector
2.1 The risks to banking sector have been increasing
in recent years. The Banking Stability Indicator1 (Chart 2.1) suggests a continued deterioration in the
stability of the banking sector since 2010 with the
aggregate risks remaining at an elevated level during the
year. An analysis of the components contributing to
banking stability show that tight liquidity, deteriorating
asset quality and reducing soundness are the major
contributors to the decline in stability of the banking
system. However, a marginal improvement in the
indicator during the last two quarters is observed
primarily because of better liquidity condition, due to
regulatory prescriptions and enhanced profitability
ratios, arising out of lower provisioning coverage
(discussed in para 2.71).
2.2 The Banking Stability Map, which reflects the
relative changes in the vulnerabilities since the previous
FSR, further reveals that the asset quality and soundness
indicators have deteriorated vis-à-vis their position in
March 2012, while the liquidity indicators show some
improvement as at the end of September 2012, the profitability indicators in the current quarter, though
better than March 2012, show marginal deterioration as
compare to June 2012 (Chart 2.2).
Distress Dependencies and Inter-connectedness -
An Analysis
Banking Stability Measures (BSMs)
2.3 The FSR has been publishing the Banking Stability
Measures since June 2011. These measures take into
account distress dependence among the banks in a
system, thereby providing a set of tools to measure
(i) common distress of the banks in a system, (ii) distress
between specific banks, and (iii) distress in the system
associated with a specific bank. These distress
dependencies are modelled by conceptualising the
financial system as a portfolio of a specific group of
banks (Segoviano and Goodhart, 2009). In particular, the
Banking System’s Portfolio Multivariate Density
(BSMD)2, which characterises both the individual and
joint asset value movements of the portfolio of banks,
is estimated from Probabilities of Distress (PoDs)3 of the
banks4, observed empirically based on 99 per cent Value
at Risk (VaR) of daily banks’ equity price return. The
BSMD embeds the banks’ distress inter-dependence
structure that captures linear and non-linear distress
dependencies among the banks in the system and its
changes at different times of the economic cycle. During
times of distress, the financial position of banks worsens
concurrently through direct or indirect links with the
economy and markets on account of fall in asset values,
interbank lending and information asymmetries. The
banking stability measures show early signs of easing
in distress-dependencies among banks.
Common distress in the system: JPoD and BSI
2.4 The probability of distress of the entire banking
system, as measured by Joint Probability of Distress
(JPoD) seems to have reversed its upward trend and
registered a marginal decline in the recent period (since
November 2012). The Banking Stability Index (BSI), which measures the expected number of banks which
could become distressed given that at least one bank
becomes distressed also registered a similar movement
of JPoD (Chart 2.3).
Distress between specific banks: Toxicity and
Vulnerability Indices
2.5 The distress between specific banks is measured
by Toxicity and Vulnerability Indices. The Toxicity Index
(TI) is the average probability that a bank under distress
may cause distress to another bank in the system.
Toxicity of banks, which was rising since beginning of
2010, has shown some decline since October 2012. At
present, the TI of the selected banks is hovering around
0.25 (Chart 2.4).
2.6 Vulnerability Index (VI), which quantifies the
average probability of a bank being in distress given
distress in the other banks in the system, was high
during the recent financial crisis. The highest probability
was about 0.9 per cent during the crisis, which declined
significantly to close to zero. During the recent period,
the VI of the selected banks is hovering around 0.15
(Chart 2.5).
Distress in the system associated with a specific bank:
Cascade Effect
2.7 The probability that at least one bank becomes
distressed, given that a specific bank becomes distressed,
characterises the likelihood that one or more banks, in
the system become distressed. This measure quantifies
the potential ‘cascade’ effects in the system given
distress in a specific bank, which reflects the systemic
importance of a specific bank. Though these conditional
probabilities do not imply causation; these can provide
important insights into systemic inter-linkages among
the banks comprising the system. The cascade
probabilities show that the Indian banking system is
highly interlinked and had a high distress dependency
during the financial crisis period. The effect came was
down in 2010, but shows an increasing trend since
beginning of 2011 (Chart 2.6).
Network Analysis
2.8 The tools of network analysis are used to assess
the interconnectedness in the financial sector and the
contagion risks arising from the failure of one or more
financial institutions5. The analysis finds that the inter
linkages in the Indian financial system are strong. In
the event of failure of a financial institution, risks are
posed to other financial institutions which have
exposures to the failing institutions. Entities which have
lent to the failing institution face solvency risks while
entities which have borrowed from the failing institution
face liquidity risks. The greater the degree of
interconnectedness in the financial system, higher is
the risk of contagion posed by a failing financial
institution. These risks are being monitored on a
quarterly basis and have not changed significantly over
the last two years.
2.9 The Indian interbank market has grown
consistently over the last two years (Chart 2.7). The
public sector banks continue to have the largest share
in this market (Table 2.1).
2.10 The network of the banking system continued to
display a distinct tiered structure. Three to four banks
have consistently featured in the inner core over the
last two years (September 2010 to September 2012), of
which, two banks are large net borrowers. The network
of the entire financial system also remained tiered
(Charts 2.8 and 2.9).
Table 2.1: Share in the Interbank Market 6 (%) |
|
Sep 2011 |
Sep 2012 |
Public Sector Banks |
53.3 |
55.9 |
Old Private Banks |
5.4 |
2.9 |
New Private Banks |
17.8 |
15.5 |
Foreign Banks |
23.5 |
25.7 |
Source: RBI |
Risks of Contagion
2.11 The previous paragraph referred to two large
borrower banks which have remained in the inner core
of the network of the banking system consistently over
the last two years. An assessment of the contagion
impact of the simultaneous failure of these banks
indicate that they would trigger the failure of nine other
banks and result in a loss of over 18 per cent of the Tier
1 capital of the banking system (Chart 2.10).
2.12 An analysis of the potential contagion loss which
could be caused by the ten most connected banks on
different dates between September 2010 and September
2012 showed that the maximum loss caused by the
failure of any one of the above banks ranged between 7
per cent and 17 per cent of the total Tier 1 capital funds
of the banking system. The analysis further showed that
the bank causing the maximum contagion loss remained
the same over the period. The average loss to the Tier 1
capital funds of the banking system caused by the failure
of any one of the 10 banks ranged from about 4 per cent
to over 7 per cent with a peak loss of 7.3 per cent in
December 2010. These trends indicate that the
interconnectedness of the banking system of the country
will need to be continuously monitored (Chart 2.11).
Contagion risks for different levels of loss given
default 9
2.13 The contagion analysis conducted so far (in
previous paragraphs and in earlier FSRs) has taken into
consideration netted bilateral exposures between banks.
Ideally, such analysis should consider gross exposures
multiplied by the loss given default (LGD) which will
give the exact amount of the loss incurred by a creditor
bank due to the failure of the debtor bank. LGDs vary
between 100 per cent (equivalent to a zero recovery rate
for the creditor) and 0 per cent (in the event that an
exposure is fully collateralised and there is no loss to
the creditor).
|
|
2.14 However, information about recovery rates and
associated LGDs are not readily available. LGD depends,
among others, on the type and amount of collateral as
well as the type of borrower and the expected proceeds
from the work out (e.g. proceeds from sale of collateral/
securities) of the assets. Also, LGD is exposure specific
i.e., different exposures to the same borrower may have
different LGDs. In the Indian context, the information
gaps are further accentuated by the fact that bankruptcy
laws are not clear and because there have been no major
instances of bank failures to provide empirical guidance
on potential LGDs.
2.15 An assessment of contagion losses caused by the
five most connected banks (as on September 30, 2012)
for different levels of LGDs indicates that below a certain
threshold (60 per cent), contagion losses are very low.
Beyond that threshold, however, contagion losses
increase sharply (Chart 2.12).
2.16 Guidelines issued by the Reserve Bank for the
implementation of the internal rating based (IRB)
approaches for calculation of capital charge for credit
risk10 indicate an LGD of 65 per cent and 75 per cent for
unsecured and non-recognised collateralised exposures,
respectively, (based on their seniority) for banks
migrating to the foundation IRB approach. Banks which
seek to migrate to the advanced IRB approach will need
to provide their own estimates of LGDs. As banks migrate
to the IRB approaches, assessment of LGDs can be
expected to improve leading to more precise assessment
of contagion risks.
Impact of distress conditions in the banking system
on contagion risks
2.17 The contagion impact of the failure of a bank is
likely to be magnified if the failure takes place in a
situation of generalised distress or shock to the banking
system. To assess the impact of distress conditions on
contagion risks, four different shocks relating to interest
rate and foreign exchange risks were considered (the
shocks used are the same as those used for stress testing
the derivatives portfolio of banks, as described in paras
2.67 and 2.68).
|
2.18 The sensitivity analysis was conducted for both
the balance sheet and the derivatives portfolio of banks.
The impact of the market movements on capital was
factored in before assessing the contagion loss. The
exercise revealed that movements in the US$/INR
exchange rate in both directions increased contagion
losses. In case of interest rate shocks, a reduction in
interest rate did not have any impact on contagion
losses. The impact on contagion loss was maximum in
case of a sharp increase in interest rates (Table 2.2 and
Chart 2.13).
Liquidity contagion using network analysis
2.19 The financial crisis highlighted the importance
of sound liquidity risk management by banks and other
financial institutions and the need to address systemic
liquidity risk. It highlighted the fact that failure of one
or more institutions could result in multiple institutions
facing simultaneous difficulties in rolling over their
short-term debts or in obtaining new short-term funding.
The network model can be used to capture the contagion
risks posed to the liquidity of the banking system in case
of failure of a large lender.
2.20 Failure of a bank affects both its lenders and
borrowers leading to solvency risk, on the one hand,
and liquidity risk, on the other. Liquidity risk is posed
to the banks who have borrowed funds from the failing
bank as these banks will need to replace the funds
borrowed.
2.21 A bank will typically maintain liquidity buffers to
tide over emergencies. These buffers comprise excess
CRR and SLR securities. The bank can also access unavailed
standing facilities extended to it by the central
bank. If these funds are not sufficient, the bank may be
able to call in short term lending to its counterparties.
In the eventuality that the bank’s liquidity buffers and
callable assets are not sufficient to meet the liquidity
shock caused by the failing bank, the bank itself may
have to be liquidated. If the borrower bank is forced to
call back its short term lending, the bank may itself
transmit a liquidity shock to its borrowers, who will, in
turn, need to find alternative funding sources. This
iterative process continues till no further loans need to be called back and hence no shock is transmitted. This
process is illustrated in the Chart 2.14.
Table 2.2: Impact of Distress Conditions on Contagion Loss |
Scenario |
Percentage loss in capital of the banking system due to the failure of the top ten connected banks |
Average Loss (%) |
Maximum Loss (%) |
Baseline |
5.0 |
11.7 |
INR depreciates |
7.2 |
15.3 |
INR appreciates |
6.4 |
11.9 |
Interest Rate Increase |
79.7 |
88.5 |
Interest Rate Decrease |
5.0 |
11.7 |
Source: RBI Staff Calculations |
2.22 An assessment of the impact of the liquidity
contagion in the Indian banking system indicates that
the failure of the large lenders in the system could have
a significant downstream impact on the availability of
liquidity in the system and could also cause a few other
banks to be, in turn, liquidated (Table 2.3). The impact
is alleviated to some extent if banks are in a position to
call in short term interbank loans.
2.23 The liquidity contagion caused by the failure of
the largest lender bank in the system as on June 30, 2012
is represented in a stylised chart (Chart 2.15). The black
triangle in the centre represents the lender bank which
is liquidated for some exogenous reason. Banks which
have borrowed from the liquidated bank will need to
replace these borrowings. In some cases, the liquidity
buffers of the banks are sufficient to absorb the liquidity
shock (banks represented by green triangles). In some
other cases, banks survive by using their buffers and
calling in short term inter-bank loans (banks represented
by orange triangles). These banks will, however, also
propagate the liquidity shock in the process of calling
in loans. For some banks, the buffers and short term
inter-bank loans will not be sufficient to replace the
funds borrowed from the trigger bank. These banks will,
in turn, be liquidated (banks represented by black
triangles) and will restart the next round of liquidity
contagion. The contagion stops when no further banks
are liquidated.
Linkages between Banking and Non-Banking Sectors
2.24 As is the case globally, the financial system in
India is also interconnected. Both funding dependencies
and direct credit exposures exist between banks, on the
one hand, and insurance companies, mutual funds and
non-banking financial companies (NBFCs), on the other.
While the banking sector is a net lender to the NBFC
sector, it is a net borrower vis-à-vis the insurance
companies and asset management companies (AMCs)
(Charts 2.16 and 2.17).
Table 2.3: Impact on Availability of Systemic Liquidity due
to the Failure of a Large Lender Bank |
(Per cent) |
|
Impact |
Bank 1 |
82 |
Bank 2 |
42 |
Bank 3 |
36 |
Bank 4 |
31 |
Bank 5 |
33 |
Note: The impact of availability of systemic liquidity is measured as a percentage of the total liquidity buffers of all SCBs as on given date
Source: RBI Staff Calculations |
2.25 The average banking sector exposure to NBFCs as
a percentage of capital funds stood at 18 per cent as at
end June 2012. However, the exposures were significant
in the case of a few banks with the exposure of 5 banks
(comprising 8.7 per cent of banking sector assets) to
NBFCs being in excess of 50 per cent of their capital
funds (Chart 2.18).
2.26 Insurance Companies are also interconnected
with the banking system as major lenders to banks which
means that insurance companies could be adversely
affected in case of any major distress in the banking
sector (Chart 2.19).
2.27 The NBFC sector was significantly dependant on
the banking system for their funding needs12. For the
selected sample, on an average, borrowings from SCBs
comprised over 100 per cent of the capital funds for the
NBFC sector. The dependency was higher in case of a
few companies for which the ratio was in excess of 200
per cent.
2.28 Some outlier banks were significantly dependent
on mutual funds for their funding needs though for the
banking sector on an average, borrowings from mutual
funds constituted only about 20 per cent of their capital
funds. However, as discussed in the previous FSR, the
borrowing of banks from mutual funds was primarily
short term which could leave the banks with a potential
liquidity risk in case of any stress in the mutual fund
industry (Chart 2.20).
Soundness and Resilience
Scheduled Commercial Banks (SCBs)
Balance Sheet Size and Structure
2.29 Total bank credit grew at 15.9 per cent, while total
deposits growth was 14.3 per cent as at end September
2012 (Y-o-Y). Despite faster credit growth relative to
deposit expansion, the Credit-Deposit (C-D) ratio has
declined to 74.4 per cent as at end September 2012 from
76.0 per cent as at end March 2012. The incremental
C-D ratio has also declined during the half year since
March 2012, indicating the trend that banks have
deployed a greater share of incremental deposits in
investments and other assets.
2.30 The steepest fall in growth rate of gross advances
(y-o-y) as at end-September 2012 from the previous
quarter was for the foreign banks; from 17.3 per cent to
6.5 per cent, followed by old private sector banks from
23.1 per cent to 18.6 per cent. There was moderate fall
in the growth rate of advances for the public sector banks
to 15.0 per cent, while the new private sector banks had
a slight increase in the growth rate of advances at 22.7
per cent (Chart 2.21).
Capital to risk weighted assets ratio (CRAR)
2.31 The overall capital adequacy ratio (CRAR) has
deteriorated since March 2012 though it remained well
above the regulatory minimum. The decline in CRAR
was observed to be more pronounced for the public
sector banks (Chart 2.22). The growth in risk weighted
assets of the foreign banks was lower over the period
under reference, partly explaining the improvement in
their CRAR position (Chart 2.23).
Credit risk
Asset Quality
2.32 The asset quality of banks has seen considerable
deterioration during the half year ended September
2012. Gross non-performing advances (GNPA) ratio for
all banks rose sharply to 3.6 per cent as at end September
2012 from 2.9 per cent as at end March 2012. Net NPA
ratio stood at 1.7 per cent as at end September 2012, as
against 1.2 per cent as at end March 2012. Among the bank groups, the public sector banks witnessed a high
degree of deterioration in asset quality (Chart 2.24).
2.33 The growth rate of GNPAs at 45.7 per cent (y-o-y)
as at end September 2012 outpaced that of gross
advances during same period, highlighting the rising
concerns on asset quality (Chart 2.25).
2.34 The concerns on asset quality are also underscored
by the increasing trend in the slippage ratio as well as
ratio of slippages to actual recoveries (excluding upgradations).
Except for foreign banks, these ratios
increased for all bank groups since March 2011. However,
slippage to recovery ratio for all the bank groups
improved marginally during the quarter ended
September 2012 (Chart 2.26 (i) and (ii)). With the growth rate in GNPAs continuing to tread well above the credit
growth and movements in slippages remaining upward,
the profitability of banks may come under pressure in
the coming quarters.
Restructuring of advances
2.35 Restructuring of loans (Box 2.1), particularly of
big ticket loans under the corporate debt restructuring
(CDR) mechanism, has recently come under closer scrutiny due to the steep rise in the number and value
of such advances (Chart 2.27 and 2.28).
2.36 Between March 2009 and March 2012, while total
gross advances of the banking system grew by less than
20 per cent (compound annual growth rate), the
restructured standard advances grew by over 40 per cent.
The proportion of restructured standard advances to
gross total advances increased from 3.5 per cent in March 2011 to 4.7 per cent in March 2012. This has further
increased to 5.9 per cent as at the end of September
2012.
Box 2.1: Restructuring of Advances
Restructuring is an accepted practice worldwide through which
lenders nurture problematic, but viable borrowal accounts. It is
a legitimate strategy adopted by lenders and borrowers
especially during times of distress to preserve the economic
value of the viable loan accounts. Restructuring has been
followed in India for many years and the guidelines in this
regard have evolved over a period taking into account
international best practices, status of development of financial
markets and changing economic conditions. The extant
restructuring guidelines cover three broad categories (i) large
corporate advances with multiple/consortium banking under
Corporate Debt Restructuring (CDR), (ii) SME Debt restructuring
mechanism and (iii) Restructuring of other advances. This
system has fulfilled its objective to a large extent. These
guidelines on restructuring have evolved in the context of
international experience.
It is a fact that restructuring of advances across the banking
sector has increased during the current financial year as also
during the last financial year. This is a matter of concern.
As regards restructuring under CDR mechanism, this has also
been in line with increase in non-CDR restructuring. According
to data furnished by CDR Cell, there has been a spurt in the
number of cases referred to CDR Cell from the year 2011-12
onwards. As against 49 cases involving `226.2 billion referred
during 2010-11, 87 cases involving `678.9 billion were referred
during 2011-12. During the period April - August of the current
year, there are 59 cases involving `306.4 billion being referred
to CDR. The reasons for rise in restructuring may be attributed
to the effects of global recession coupled with internal factors
like domestic slow down, which have played a significant role
in the deterioration in asset quality.
Aggressive lending by banks in the past, banks not exercising
oversight on diversification into non-core areas by companies,
banks not enforcing discipline on companies regarding
unhedged forex exposures and delay in disbursements are areas
on which banks ought to exercise much better control. Delay
in administrative clearances is an equally important reason for
pressure on asset quality which needs correction. The spurt in
restructuring of advances is a matter of concern, though it may
not have systemic dimension. The Reserve Bank is closely
monitoring the position. Some course correction at the level of
all stake holders may definitely improve the situation.
With a view to reviewing existing guidelines on restructuring
of advances and suggest revisions taking into account the best international practices and accounting standards, the Reserve
Bank had constituted a Working Group (WG) under the
chairmanship of Shri B. Mahapatra, Executive Director, Reserve
Bank of India. The WG has examined the issues and its major
recommendations can be summarised as below:
-
The regulatory forbearance available on asset classification
on restructuring presently needs to be withdrawn after two
years.
-
During the interregnum, provision on standard restructured
accounts which get the asset classification benefit on
restructuring be increased from the present 2 per cent to 5
per cent, in a phased manner in case of existing accounts
(stock) and immediately in case of newly restructured
accounts (flow).
-
In view of the importance of infrastructure sector, asset
classification benefit on restructuring may however be
allowed for a longer period in cases where restructuring is
due to change in date of commencement of commercial
operation of infrastructure projects.
-
A cap of, say 10 per cent, to be prescribed on amount of
restructured debt which can be converted into preference/
equity shares.
-
RBI may prescribe the broad benchmarks for viability
parameters based on those used by CDR Cell; and banks
may adopt them with suitable adjustments, if any, for
specific sectors.
-
Compulsory promoters stake in the restructured accounts
to be increased by way of higher sacrifice and personal
guarantee.
-
Right of recompense may be made mandatory in all cases.
-
Disclosure requirements to be made comprehensive but to
exclude standard restructured accounts which have shown
consistent satisfactory performance.
Second Quarter Review of Monetary Policy 2012-13 on October
30, 2012 has announced an increase in the provision for
restructured standard accounts from the existing 2.0 per cent
to 2.75 per cent in line with a major recommendation of the
WG. It has also been announced that draft guidelines on the
subject taking into account the recommendations of the WG as
also the comments received in this regard will be issued by
end-January 2013.
2.37 Some industrial sectors like iron & steel,
infrastructure and textile experienced a much greater
degree of restructuring of advances in the recent period
(chart 2.29).
Credit Risk to Power Sector
2.38 The risks faced by banks in lending to the power
sector were highlighted in the previous FSR. Pressure
on asset quality in the power sector has worsened since
then. Impairments have risen in the preceding year
ending September 2012 (Chart 2.30(i)). Instances of restructuring too have registered a steep increase in the
recent quarters. The large exposure to this sector
remains an area of concern for banks (Charts 2.30(ii)).
Assessment of Provision Coverage
2.39 An analysis of provision coverage of SCBs was
attempted in the context of recent spurt in the NPAs.
The impairment levels in Indian banks compare
favourably with those of global banks. However, the provision coverage ratio is relatively lower and has also
shown a declining trend in recent quarters. In view of
this, it may be advisable for banks to increase their
provisioning levels (Chart 2.31 and Chart 2.32)
Credit Risk- Stress Testing using Sensitivity Analysis
2.40 Sensitivity analysis or single factor stress tests13 were conducted on the banking system’s credit portfolios
using different scenarios14. The results show that the banking system would be resilient to various stress
scenarios (Table 2.4).
Macro Stress Test - Credit Risk
2.41 In order to test the resilience of the Indian
banking system against macroeconomic shocks, a series
of macro stress tests at system, bank-group and sectoral
level were performed using times series econometric
tools15.
2.42 The macro stress tests encompass a series of risk
scenarios incorporating a baseline and two adverse
macroeconomic scenarios representing medium and
severe risk (Table 2.5). The adverse scenarios were
derived based on up to 1 standard deviation for medium
risk and 1.25 to 2.0 standard deviation for severe risk
(10 years historical data).
System Level Credit Risk
2.43 The macro stress test suggests that, if the current
adverse macroeconomic condition persists, the system
level GNPA ratios could rise from 3.6 per cent as at the
end of September 2012 to 4.0 per cent by end March
2013 and 4.4 per cent by end March 2014. The GNPA
ratio could go up to 4.8 per cent and 7.6 per cent under
the severe risk scenario in the respective periods. Under
the severe stress scenario, the system level CRAR of SCBs
could decline to 10.9 per cent by March 2014, which is
still above the regulatory requirement of 9 per cent
(Table 2.6 and Chart 2.33).
Bank Group Level Credit Risk
2.44 Among the four bank-groups, namely, public
sector banks (PSB), old private banks (OPB), new private
banks(NPB) and foreign banks(FB), PSBs might continue
to register highest GNPA ratio. Under baseline scenario,
the GNPA ratio of PSBs may rise to 4.3 per cent by March
2013 from 4.0 per cent of September 2012. Whereas,
GNPA ratios of OPB, NPB and FB may rise to 2.6 per cent,
2.7 per cent and 3.2 per cent by March 2013 from the 2.2 per cent, 2.1 per cent and 2.9 per cent of September
2012, respectively (Chart 2.34).
Table 2.4: Stress Tests - Credit Risk: Gross Credit – September 2012 |
(Per cent) |
|
System Level |
CRAR |
Core CRAR (Tier I) |
NPA Ratio |
Baseline: |
All Banks |
13.6 |
10.0 |
3.6 |
Select 60 Banks |
13.5 |
9.8 |
3.6 |
Stress Scenarios: |
Shock 1 |
12.0 |
8.3 |
5.4 |
Shock 2 |
11.2 |
7.4 |
7.1 |
Shock 1 : NPAs increase by 50% |
Shock 2 : NPAs increase by 100% |
Source: RBI Supervisory Returns and Staff Calculations. |
Table 2.5: Macroeconomic Scenario Assumptions 16 |
(Per cent) |
FY |
|
Baseline |
Medium Stress* |
Severe Stress* |
2012-13 |
GDP Growth |
5.8 |
5.2 |
3.5 |
WPI Inflation |
7.7 |
9.5 |
11.5 |
Short-term Interest Rate |
8.0 |
9.1 |
10.5 |
Exports to GDP Ratio |
15.7 |
14.2 |
12.7 |
Gross Fiscal Deficit |
5.3 |
5.8 |
6.3 |
2013-14 |
GDP Growth |
6.9 |
4.7 |
2.6 |
WPI Inflation |
6.7 |
9.4 |
12.0 |
Short-term Interest Rate |
7.4 |
9.3 |
11.1 |
Exports to GDP Ratio |
16.0 |
14.0 |
12.0 |
Gross Fiscal Deficit |
4.8 |
6.2 |
7.5 |
Note *: For Financial year 2012-13, the average numbers for the selected
macrovariables under medium and severe stress is based on the December
2012
& March 2013 quarters only. |
Table 2.6: Projection of System Level GNPA Ratios of SCBs |
(Per cent of total advances) |
Scenario |
Sep-12 (Actual) |
Mar-13 |
Mar-14 |
Mar-13 |
Mar-14 |
Multivariate Logit
Regression |
Multivariate
Regression |
Baseline |
|
3.9 |
4.4 |
3.8 |
4.1 |
Medium Risk |
3.6 |
4.0 |
5.3 |
3.9 |
5.1 |
Severe Risk |
|
4.0 |
6.4 |
4.0 |
6.1 |
|
|
VAR |
Quantile Regression |
Baseline |
|
3.8 |
4.4 |
4.0 |
4.4 |
Medium Risk |
3.6 |
3.9 |
6.0 |
4.4 |
6.0 |
Severe Risk |
|
4.0 |
7.6 |
4.8 |
7.6 |
Note: The GNPAs derived based on VAR and quantile regression, especially for severe shock scenario, are relatively higher. This is because, VAR methodology takes into account feedback impact of credit quality to macro variables and interaction effects leading to higher impact. Whereas, in the case of quantile regression, which deals with the tail risks; the credit quality of the banks, at present, is already under stress and further shocks to macro variables impact the NPA more. |
|
2.45 Among the bank-groups, PSBs are expected to
register lowest CRAR followed by the old private sector
banks. Under severe stress scenario, the CRAR of PSBs
may decline to 11.4 per cent and 9.9 per cent by March
2013 and March 2014, respectively, which is still above
than the regulatory requirement of 9 per cent
(Chart 2.35).
Sectoral Credit Risk
2.46 Macro stress test of sectoral credit risk revealed
that among the selected seven sectors, Agriculture is
expected register highest NPA at 5.8 per cent by March
2013, followed by Engineering, Iron & Steel and
Construction. However, the adverse macroeconomic
shocks seem to have maximum impact on Engineering
and Iron & Steel (Table 2.7).
Concentration Risk
2.47 Banks’ total credit (funded plus non-funded)
exposures (TCE) to individual large borrowers (top 20)
shows that the concentration of exposure reduced both
in terms of per cent of capital fund as well as gross
advances. While the TCE as per cent of capital fund
declined from 186.9 per cent at end Mar-10 to 167.4 per
cent by end Jun-12, the TCE as percent of gross advances declined from 32.8 to 27.8 per cent during the same
period (Table 2.8).
Table 2.7: Projected Sectoral NPA |
(Per cent of total advances) |
Sector |
Sep-12
(Actual) |
Mar-13 |
Mar-14 |
Baseline |
Medium Risk |
Severe Risk |
Baseline |
Medium Risk |
Severe Risk |
Agriculture |
5.2 |
5.8 |
5.8 |
5.9 |
6.5 |
6.9 |
7.3 |
Construction |
3.7 |
3.5 |
3.6 |
3.7 |
3.3 |
3.7 |
4.1 |
Cement |
2.0 |
2.5 |
2.6 |
2.7 |
3.4 |
3.9 |
4.6 |
Infrastructure |
1.5 |
1.8 |
1.9 |
2.0 |
2.0 |
2.4 |
2.9 |
Iron and Steel |
3.9 |
4.3 |
4.4 |
4.7 |
4.7 |
5.8 |
7.0 |
Engineering |
3.5 |
4.2 |
4.4 |
4.7 |
4.3 |
5.4 |
6.6 |
Automobiles |
0.9 |
1.7 |
1.7 |
1.7 |
1.9 |
2.3 |
2.6 |
Source: RBI Supervisory Returns and RBI Staff Calculations |
2.48 Share of banks’ funded exposure to their top 20
individual borrowers in banks’ total gross advances
declined from 22.0 per cent as at end March 2010 to 18.5
per cent by end June 2012, at system level (Chart 2.36).
In respect of banks groups, the concentration has been
quite high for foreign banks, which may be because of
their limited customer/borrower base. Further, the
concentration declined in the case of NPBs during the
1st quarter of FY 2012-13.
2.49 The stress tests on concentration risk of SCBs
show that the impact under various stress scenarios are
not significant. The share of top three borrowers to the
total credit is about 8.0 per cent (at system level). There
is a regulatory cap imposed on banks on their credit
exposures to individual and group borrowers. The
exposure ceiling limit is 15 percent of capital funds in
case of a single borrower and 40 percent of capital funds
in the case of a borrower group. The reduction in CRAR
under the assumed scenario of default of top three
individual borrowers would be 240 basis points and the
system should be able to withstand this default.
However, at individual level, a few banks with high
concentration might be seriously impacted under
stressed conditions.
Liquidity Risk
2.50 The liquidity position of banks has improved over
the last six months, reflecting the effect of the reduction
in the CRR and SLR. The ratio of liquid assets to total
assets has increased from 28.9 per cent as at end March
2012 to 30.1 per cent at end September 2012.
2.51 A detailed analysis of the ‘quality’ of liquidity is
captured by the liquidity ratios (Table 2.9). The ratio of
volatile liabilities to earning assets, (with both numerator
and denominator adjusted for temporary assets)
measures the extent to which banks’ basic earning assets
are funded by less stable sources of funds. This ratio
was 40.9 per cent as on September 2010 and has steadily
increased to 43.9 percent as at end September 2012,
which points towards banks increasingly resorting to
short term bulk deposits.
2.52 The ratio of loans including mandatory cash
reserves and statutory liquidity investments to total assets has decreased from 82.4 per cent in September
2010 to around 60 percent over the period of last two
years, partly reflecting the decrease in statutory reserve
ratios over the period of last two years. The decreased
ratio although reflecting the slowdown in credit growth
also indicates that ‘illiquidity’ embedded in the balance
sheet has come down. The ratio in terms of core deposits
has moved from 1.6 in September 2010 to 1.2 as at
September 2012 indicating a decrease in purchased
liquidity.
Table 2.8: Banks’ Exposure to their Top 20 Individual Borrowers |
(Per cent) |
Bank Group |
Total Credit Exposure (TCE) |
Mar-10 |
Mar-11 |
Mar-12 |
Jun-12 |
TCE as % of Capital Fund |
PSBs |
201.4 |
185.4 |
175.4 |
178.7 |
OPBs |
191.5 |
189.8 |
191.5 |
194.0 |
NPBs |
149.3 |
150.0 |
138.4 |
110.9 |
FBs |
178.2 |
179.8 |
196.7 |
206.3 |
All SCBs |
186.9 |
177.3 |
170.4 |
167.4 |
TCE as % of Gross Advances |
PSBs |
28.7 |
25.8 |
24.2 |
24.6 |
OPBs |
28.4 |
27.2 |
25.6 |
25.8 |
NPBs |
43.6 |
40.1 |
36.5 |
28.5 |
FBs |
70.7 |
69.4 |
73.8 |
74.2 |
All SCBs |
32.8 |
30.0 |
28.5 |
27.8 |
Source: RBI Supervisory Returns |
Table 2.9: Liquidity Ratios |
(Per cent) |
|
Sep-10 |
Sep-11 |
Sep-12 |
(Volatile Liabilities - Temporary Assets) / (Earning Assets - Temporary Assets) |
40.9 |
42.0 |
43.9 |
Core Deposits / Total Assets |
51.0 |
49.5 |
51.2 |
(Loans + Mandatory CRR + Mandatory SLR + Fixed Assets )/ Total Assets |
82.4 |
59.5 |
60.6 |
[Loans + Mandatory CRR + Mandatory SLR + Fixed Assets ] / Core Deposits |
1.6 |
1.2 |
1.2 |
Source: RBI Supervisory Returns |
Bulk Deposits
2.53 Retail deposits (Current Account, Savings and
Term deposits) are inherently more stable as they are
diversified and less prone to premature withdrawal. A
few public sector banks continued to display a high
degree of reliance on ‘bulk’ deposits (i.e. deposits of `10
million and above for the analysis). In some cases the
bulk deposits constituted more than 50 per cent of the
total liabilities as at end September 2012. Excess SLR
securities holdings constitute a bulwark against runs on
banks relying on such wholesale sources of funds.
Position in respect of bulk deposits and the mitigant in
the form of excess SLR holdings is presented in
Chart 2.37.
2.54 According to bank group classification, the
proportion of the bulk deposits in total deposits
remained high for foreign banks, though there has been
slight decline in the last six months. The proportion of
the bulk deposits in total deposits has shown signs of
stabilising after increasing in last few quarters for the
public sector banks. Since term deposits can be
withdrawn prematurely17, such bulk deposits remain
prone to withdrawal and/ or non-rollover, posing
liquidity risks to the banks relying on such deposits.
While a higher proportion of bulk deposits and
borrowings in total liabilities of banks make them
vulnerable to liquidity shocks, the proportion of their
investments in liquid government securities acts as a
mitigating factor.
2.55 Deposit growth of banks has been lagging loan
growth for several quarters. This exposes the banks to liquidity stresses as it increases reliance on wholesale
sources of funds. In order to boost retail deposits growth,
certain product innovations like variable rate deposits
could be considered (Box 2.2).
Box 2.2: Variable Rate Deposits
RBI allowed commercial banks to fix their own interest rates on
domestic term deposits of various maturities with the prior
approval of their respective Board of Directors/Asset Liability
Management Committee (ALCO), effective October 22, 1997.
The Annual Monetary and Credit Policy for the year 2002-03
had noted the following: “The average cost of deposits for major
banks continues to be relatively high. Further, a substantial
portion of deposits is in the form of long-term deposits at fixed
interest rates. Thus, flexibility available to banks to reduce
interest rates in the short-run, without adversely affecting their
return on assets, is limited.” The Policy document, accordingly,
favoured introduction of flexible interest rate deposits with
reset at six-monthly intervals where the interest rate could be
higher or lower vis-à-vis the fixed rate deposit for similar maturity depending on banks’ perception regarding inflation
and the interest rate outlook over the longer period.
Furthermore, banks were also urged to devise schemes for
encouraging depositors to convert their existing long-term fixed
rate past deposits into variable rate deposits. Commercial banks
could consider paying the depositors at the contracted rate for
the period of deposit already run and waive the penalty for
premature withdrawal if the same deposit is renewed at the
variable rate.
Notwithstanding the fact that about 80 per cent of the loans
extended by banks are floating rate instruments, only a few
banks had introduced floating rate deposit products during the
last 10 years.
Stress Test - Liquidity Risk
2.56 Liquidity risk analysis has been done using
different definitions of liquid assets18. The stress
scenarios are constructed to test the ability of banks to
meet a run on their deposits using only their liquid
assets. Under the stress scenarios, there were indications
of deterioration in the liquidity position of some banks,
though SLR investments helped them to ward off the
liquidity pressure (Definition-1; Table 2.10).
2.57 The liquidity stress tests conducted on banks
groups reveal that foreign banks have a better liquid
asset position to guard against any stress, primarily due
to their higher proportion of short term investments /
excess SLR and most of their advances portfolio being
short-term (less than one year).
Interest Rate Risk
2.58 Investments accounted for 29.8 per cent of assets
of the banking system, as at end September 2012. Stress
tests carried out to evaluate the valuation impact by
marking to market the banking book under different
scenarios revealed that the banking system was capable
of withstanding such shocks. The maximum impact due to upward movement of yield curve, was on the low
maturity buckets on the banking book. Under the
scenarios (Shock 1; Table 2.11), the capital position of
the banking system is reduced sharply by 320 bps. On
the other hand, the impact of direct interest rate risk on
the trading book was not high (only about 80 bps).
Therefore, overall impact under the assumed scenarios
would still be manageable.
Table 2.10: Liquidity Risk: SCBs – September 2012 |
Liquid Assets Definition |
Liquid Assets Ratio (%) |
Public Sector Banks |
Old Private Banks |
New Private Banks |
Foreign Banks |
All SCBs |
Definition 1: Baseline |
25.7 |
23.8 |
21.4 |
25.9 |
24.9 |
Shock 1: |
10 per cent total deposit withdrawal 30 days |
16.5 |
14.8 |
13.5 |
20.0 |
16.2 |
Shock 2: |
3 per cent deposit withdrawal each day for 5 days |
13.1 |
11.3 |
10.5 |
18.2 |
13.0 |
Definition 2: Baseline |
5.4 |
4.2 |
2.9 |
11.9 |
5.4 |
Shock 1: |
10 per cent total deposit withdrawal 30 days |
-6.2 |
-7.2 |
-6.9 |
4.8 |
-5.6 |
Shock 2: |
3 per cent deposit withdrawal each day for 5 days |
-10.6 |
-11.6 |
-10.5 |
2.6 |
-9.6 |
Definition 1: Cash, Inter-bank-deposits, All-SLR-Investments
Definition 2: Cash, Inter-bank-deposits, Excess SLR |
Source: RBI Supervisory Returns and RBI Staff Calculations |
Equity Price Risk
2.59 The impact of assumed fall in equity prices by 40
per cent does not impact significantly as the equity
market exposure of banks in India is not high. One
specific reason is that there are regulatory limits
prescribed for the capital market exposure of banks. The
system level CRAR falls to 12.9 per cent under stress
from the baseline at 13.6 per cent and no bank is severely
impacted.
Foreign Exchange Risk
2.60 Banks have direct exposure that is visible in
balance sheet items like foreign exchange liabilities and
commitments provided to overseas branches. While the
Indian banking system’s liabilities to overseas entities
has grown over the last several years, it has dwindled
as a proportion of total liabilities (Chart 2.38). Likewise,
their foreign claims (assets abroad on an ultimate risk
basis) too have grown strongly but have remained largely
unchanged as a proportion of total assets (Chart 2.39).
This suggests low direct exposures to exchange rate risks
(indirect foreign exchange risk, through unhedged
corporate exposure is discussed in para 1.23 of
Chapter I).
2.61 The relatively more flexible ‘internal models’
approach under Basel-II allows each bank to measure its
exposure after incorporating the relationships among
its various trading and non-trading operations (model
risk is discussed in para 3.9 of Chapter III). However,
the use of ‘internal models’ approach for analysis of the
foreign exchange risk across various banks is constrained,
due to the differences in the business models of banks
and other related factors.
2.62 The foreign exchange risk under various scenarios
(where INR appreciation of 10 and 20 per cent and
depreciation of 10 and 20 per cent are assumed), do not
show much impact on the commercial banks mainly because of low net open currency positions of individual
banks. The reduction in CRAR is only 20 basis points
under the assumed scenarios.
Table 2.11: Interest Rate Risk – Trading and Banking Books September 2012 |
(Per cent) |
|
CRAR (system level) |
Core CRAR (system level) |
Baseline: |
All Banks |
13.6 |
10.0 |
Select 60 Banks |
13.5 |
9.8 |
Stress Scenarios - Interest Rate Risk : Valuation Impact
(Modified Duration Analysis) |
|
Banking Book |
Trading Book |
Banking Book |
Trading Book |
Shock 1 |
10.3 |
12.7 |
6.7 |
9.1 |
Shock 2 |
11.6 |
13.1 |
8.0 |
9.4 |
Shock 1 - Parallel upward shift of the INR yield curve by 250 bps
Shock 2 - Inversion of the INR yield curve 250 to -100 linearly |
Source: RBI Supervisory Returns and RBI Staff Calculations |
Derivatives Portfolio of Banks
2.63 Derivatives could engender systemic risk on
account of the size of the over-the-counter (OTC)
segment of the derivatives market and the high
concentration of financial obligations, with a relatively
small number of banks serving as counterparties to a
large number of OTC derivative transactions.
2.64 The derivatives market in India grew sharply in
the years leading up to the global financial crisis.
Though the portfolio size has shrunk since 2008, it still
remains large with the notional outstanding principal
of the derivatives portfolio of banks constituting over
1500 per cent of banks’ capital funds and over 160 per
cent of its total assets as on March 31, 2012 (Chart 2.40 and Table 2.12). A significant degree of concentration
exists in the Indian derivative markets with foreign
banks as a group constituting 70 per cent of the
outstanding notional principal in the derivatives
market, disproportionate to their share in balance sheet
assets of the banking system at 7 per cent. Further, the
share of the top five banks in notional principal
outstanding constituted 43 per cent of the outstanding
notional of the derivatives portfolio of all scheduled
commercial banks as on March 31, 2012.
2.65 The bulk of outstanding derivative transactions
are interbank transactions – for the 26 banks with the
largest derivatives exposures, the interbank segment of
the derivatives market constituted, on an average, 76
per cent of the total outstanding derivatives as at
September 2012 (Chart 2.41). This accentuates the interconnectedness
between banks and increases the risk of
contagion arising from the failure of any bank. Contagion
analysis shows that in case of the top six banks in terms
of derivatives exposure, the loss from failure of any one
bank increases significantly when non fund based
exposures are considered along with fund based
exposures (Chart 2.42).
Credit risk emanating from derivative receivables
2.66 The net mark to market (MTM) value of the
derivatives portfolio for the banks in the sample varied
across the two segments – with most banks registering negative net MTM in case of the interbank segment and
positive net MTM in case of the customer segment. The
receivables from the customer segment constituted 26
per cent of the total receivables of banks. The gross
receivables from customers were relatively small vis-à-vis
the capital funds in case of public and private sector
banks, while they were significantly higher in foreign
banks. The credit risk emanating from these positions
will need to be carefully monitored (Chart 2.43).
|
Table 2.12: Relative Size of the Derivatives Market in India –March 2012 |
` billion |
All Banks |
Top 5 banks* |
Top 10 banks* |
Derivatives Notional Principal |
127000 |
55000 |
87000 |
Total Assets |
78000 |
7000 |
12000 |
Capital Funds |
8000 |
1000 |
2000 |
Notional Principal as % of Assets |
162.8 |
785.7 |
725.0 |
Notional Principal as % of Capital |
1587.5 |
5500.0 |
4350.0 |
Note : i. *Top banks as per derivatives notional principal
ii. Amount rounded off to nearest `1000 billion
Source : RBI Supervisory Returns |
Sensitivity of the derivatives portfolio to market risks
2.67 A series of stress tests was carried out on the
derivatives portfolio as on September 30, 2012 by a
sample of 26 banks based on a common set of four
interest rate and exchange rate sensitivity shocks20. The
sample of banks and shocks were the same as used for
the analysis presented in the June 2012 issue of the FSR.
The results of the stress testing indicate that the
sensitivity of the derivatives portfolio to market
movements has increased in the period since the
publication of the previous FSR, as the average change
in net MTM as a ratio of capital based on a worst case
analysis across the four shocks (the maximum impact
across the set of four shocks) has increased from 2 per
cent as at March 2012 to 10 per cent as at September
2012. The impact of individual shocks, however, displays
mixed trends (Chart 2.44).
|
|
2.68 The average impact of the application of shocks
stood at about 10 per cent of capital funds. However,
there were some outlier banks where the impact was
significantly higher (Chart 2.45).
Profitability
2.69 An analysis of main components of income shows
that the growth in interest income as well as interest
expense has declined during the half year ended
September 12, but the decline was comparatively sharper
in case of interest expense. This, apart from other
factors, has contributed to growth in earnings before
provisions and taxes (EBPT). The profit after tax has also
grown at a rate of 36.8 per cent, reaching close to the
growth rate of 37.4 per cent observed in September 2007
(Chart 2.46).
2.70 The profitability during the current half year has
been supported by a faster growth in other items of
income like miscellaneous income, profit from trading
and forex during the first half year (Chart 2.47). The
commission income from selling insurance and mutual
fund products by banks has also increased in recent
period.
2.71 The provision cover of many large banks, mainly
the public sector banks, has steadily declined during last
few quarters (Chart 2.48). The fall in provision coverage
ratio (without write-offs), apart from other factors has
perhaps helped banks in reporting an improved profit
performance over the last two quarters, even as NPAs have increased during the period. This effect is more
marked in the cases of public sector banks, as they have
experienced the fastest growth in NPAs and restructured
assets.
2.72 The net interest margin (NIM) at the system level
has remained stable at about 3.0 per cent but declined
slightly for a few large public sector banks. Going ahead,
the NIM of the banks may remain under pressure as the
benefit of a possible decline in cost of funds is likely to
be offset by declining asset yields.
Regional Rural Banks
2.73 An analysis of financial soundness indicators and
balance sheet components of Regional Rural Banks
(RRBs) reveals that the financial performance of RRBs
bas been improving (Table 2.13). Fewer banks made
losses during 2011-12 compared to 2010-11(3 as opposed
to 7 earlier) and the loss amount too has shrunk from
`710 million to `280 million. While there has been 17.7
per cent growth in advances, deposits have grown to the
extent of 12.1 per cent on a y-o-y basis. As on date, 19
RRBs in 6 states have been amalgamated across 12
sponsor banks. 71 RRBs are now in existence against 82
RRB prior to amalgamation.
Urban Co-operative Banks
2.74 There were 51 Scheduled UCBs (SUCBs) as on
September 30, 2012. An analysis of all SUCBs revealed
that overall CRAR declined from 12.8 per cent as on
March 31, 2012 to 12.6 per cent as on June 30, 2012 and
thereafter increased marginally to 12.7 per cent as on
September 30, 2012. GNPA ratio increased from 4.6 per
cent as on March 31, 2012 to 5.9 per cent as on June 30,
2012 and increased further to 6.1 per cent as on
September 30, 2012. Annualised RoA improved from 0.9
per cent as on March 31, 2012 to 1.3 per cent as on June
30, 2012 and thereafter declined to 1.1 per cent as on
September 30, 2012. Liquidity Ratio based on stock
approach for the SUCBs which was 34.0 per cent as on
March 31, 2012 as well as June 30, 2012 improved
marginally to 34.1 per cent as on September 30, 2012.
Provision Coverage Ratio of SUCBs declined from 76.2
per cent as on March 31, 2012 to 66.0 per cent as on June
30, 2012 and thereafter improved to 66.2 per cent as on
September 30, 2012 (Table 2.14).
Table 2.13: Performance Parameters of RRBs |
(` Million) |
S. N. |
Parameters |
2010-11 |
2011-12 |
% Growth |
1 |
Owned Fund |
13,8390 |
16,4620 |
18.95 |
2 |
Deposit |
1,66,2320 |
1863360 |
12.09 |
3 |
Gross Loan (O/s) |
98,9170 |
1163850 |
17.66 |
4 |
CD Ratio |
59.51 |
62.46 |
4.96 |
5 |
Accumulated Losses |
1,5320 |
13320 |
-13.05 |
6 |
Net Profit |
1,7860 |
18860 |
5.59 |
7 |
Loss (No. of RRBs) |
710 (7) |
280 (3) |
-60.56 |
8 |
Gross NPA % |
3.75 |
5.03 |
34.13 |
9 |
Net NPA % |
2.05 |
2.98 |
45.36 |
10 |
Branch Productivity |
165.7 |
179.0 |
8.02 |
11 |
Staff Productivity |
37.8 |
40.7 |
7.67 |
Source: NABARD |
Table 2.14: Select Financial Soundness Indicators of SUCBs |
(Per cent) |
Financial Soundness Indicators |
March 2012 |
June 2012 |
September 2012 |
1. CRAR |
12.8 |
12.6 |
12.7 |
2. Gross NPAs to Gross Advances |
4.6 |
5.9 |
6.1 |
3. Return on Assets (annualised) |
0.9 |
1.3 |
1.1 |
4. Liquidity Ratio |
34.0 |
34.0 |
34.1 |
5. Provision Coverage Ratio |
76.2 |
66.0 |
66.2 |
Note: 1. Data exclude MMCB;
2. Data are provisional and based on OSS Returns;
3. Liquidity Ratio = 100 * (Cash + due from banks + SLR investment) / Total Assets;
4. PCR is compiled as “NPA provisions held as per cent of Gross NPAs”. |
Stress Test - SUCBs - Credit Risk
2.75 Stress tests on credit risk were carried out for
SUCBs using the data based on Off-Site Surveillance
(OSS) returns as on September 30, 2012. The impact of
credit risk shocks on the CRAR of SUCBs was assessed
under two different scenarios assuming an increase in
the GNPA by 50 per cent and 100 per cent respectively.
The results show that SUCBs could withstand shocks
assumed under the first scenario easily, though they
would come under some stress under the second
scenario (Chart 2.49).
Stress Tests – SUCBs - Liquidity Risk
2.76 Stress tests on liquidity risk were carried out
under two different scenarios assuming an increase in
cash outflows in the 1 to 28 days time bucket by 50 per
cent and 100 per cent respectively. It was assumed that
there was no change in cash inflows under both the
scenarios. The banks would be considered to be impacted
as a result of the stress if the mismatch or negative gap
(i.e. the cash inflow less cash outflow) in the 1 to 28
days time bucket exceeds 20 per cent of outflows. The
stress test results indicate that the SUCBs would be
significantly impacted even under the less severe stress
scenario (Chart 2.50).
Non-Banking Financial Companies (NBFCs)
2.77 In India, this sector has been in the regulated
space and its growth and development has been under
the oversight of the Reserve Bank. Among NBFCs, the
highest monitoring attention is accorded to firms
identified as systemically important, specifically, the
Non-Bank Financial Companies - Non-Deposit Taking
– Systemically Important (NBFC-ND-SI). The CRAR norms
were extended to NBFCs-ND-SIs and they are required
to maintain a minimum capital, consisting of Tier-I and
Tier- II capital, of not less than 15 per cent of their
aggregate risk-weighted assets.
2.78 The aggregate CRAR of the ND-SI sector stood at
25.7 per cent for the quarter ended June 2012 (Chart 2.51).
While it is high, the ratio has been deteriorating in the
last few quarters. The gross NPA ratio21 of the NBFC sector has remained stable around 2.0 per cent for the
past many quarters (Chart 2.52).
Profitability Ratios
2.79 The return on assets (net profit as a percentage
of total assets) of the NBFCs-ND-SI sector stood at 2.1
per cent for the quarter ended June 2012 as compared
with 2.5 per cent for the same quarter in the previous
year (Chart 2.53).
Sources & Uses of Funds of NBFC Sector
2.80 NBFCs (ND-SI) collect funds from a wide range of
sources including debentures, borrowings from banks,
financial institutions, commercial paper, inter-corporate
borrowings etc (Chart 2.54). Owned fund is another
prospective source of finance for NBFCs (ND-SI) and is
accounted for 26 per cent of total liabilities. Of these
sources of funds, accessing funds through debentures
constitute a major portion of total funds followed by
borrowings from banks. On the assets side, loans &
advances is the major use of funds and is accounted for
72 per cent of total uses of funds.
2.81 Advances of NBFCs to real estate sector on an
average accounted for 4.5 per cent of total advances of
the ND-SI sector (Chart 2.55).
2.82 Capital market exposure(CME) includes
(i) investments in listed instruments and (ii) advances
to capital market related activities. CME of the NBFC
sector on an average accounted for 9.0 per cent of total
assets of the ND-SI sector, while CME to owned funds
of the sector accounted for 34.5 per cent (Chart 2.56).
Infrastructure Finance Companies (IFCs)
2.83 Aggregate balance sheet size of the eight IFCs
increased by 27.5 per cent during 2011-12 on top of 25.3
per cent growth witnessed in the previous year.
Debentures of these companies increased more than 2.5
times during the period of three years i.e. from March
2010 to March 2012 (Chart 2.57). This may be largely
due to raising of huge funds through non-convertible
debentures. Bank borrowings of IFCs increased
marginally by 0.7 per cent in 2011-12 as against 14.3 per
cent growth witnessed in the previous year.
2.84 Leverage ratio of the IFCs hovered between 5.1
and 5.7 during the period under review. The share of
bank borrowings in total liabilities decreased from 17.5
per cent as on March 31, 2010 to 12.5 per cent as on
March 31, 2012, while the share of debentures increased
from 34.5 per cent to 56.9 per cent during the same
period. Return on assets of the IFCs, witnessed
decelerating trend, it declined from 2.5 per cent as on
March 2010 to 2.1 per cent as on March 2012. In tandem
with RoA, return on equity also decelerated (declined
from 15.1 per cent to 14 per cent) during the period
under review.
Stress testing the NBFC sector (NBFC-D and ND-SI)
2.85 A stress test on credit risk for NBFC sector
(includes both deposit taking and ND-SI) for the period
ended June 2012 was carried out under two scenarios
(i) where gross NPA increased two times and (ii) gross
NPA increased 5 times from the current level. It was
observed that in the first scenario, CRAR dropped by 0.7
percentage points from 26 per cent to 25.3 per cent while
in the second scenario CRAR dropped by 2.5 percentage
points (CRAR dropped from 26 per cent to 23.5 per cent).
It may be concluded that even though there was shortfall
in provisioning under both the scenarios, the impact on CRAR was negligible as the sector had a higher level of
CRAR at 26 per cent as against the bench mark CRAR of
15 per cent.
Stress Testing Major Individual NBFCs
2.86 A stress test on credit risk for major individual
NBFCs for the period ended June 2012 was also carried
out under two scenarios (i) where gross NPA increased
two times and (ii) gross NPA increased 5 times from the
current level. Under first scenario, it was observed that
4.9 per cent companies would have CRAR less than
regulatory CRAR of 15 per cent while in second scenario,
CRAR of 9.5 per cent companies was found to be less
than regulatory CRAR of 15 per cent.
Pension System in India22
2.87 During financial crises a steep fall in asset prices
trigger redemption pressure which is a potential
destabiliser for the fund management industry. In such
stressed scenario, only long-term funds such as, pension
funds can be a source of financial stability providing
buying support. The larger the pension funds’ investible
resources, the stronger will be the stabilising force. In
India, a continued reliance on unsustainable pay-as-yougo
pension schemes in the government has the potential
for an adverse impact on financial stability by raising fiscal deficit. In the case of civil servants, a transition
from the pay-as-you-go Defined Benefit to a fully funded
Defined Contribution pension system has already been
made for the centre and for a large majority of the states.
However there exist a large number of Defined Benefit
schemes for the unorganised sector both at the level of
the centre and the states. These schemes which mainly
target either the people Below Poverty Line (BPL) or
occupational groups vary in terms of the benefit
structures, administrative mechanisms and coverage.
Often the scheme is announced without any actuarial
estimation of the future liability or the funding
requirement. However, unless a fiscally sustainable
mechanism for delivering this goal is designed risks
would be either an inadequate coverage or a poor benefit
structure.
2.88 Infrastructure financing gap act as a drag on
economic growth. Pension funds being long-term funds
can be used to finance infrastructure projects. The
working sub-group on infrastructure, Planning
Commission has estimated available resources to the
tune of `1507 billion to come from insurance/pension
fund. It has also recommended the necessity of
regulatory reforms for insurance/pension funds to
mobilise savings through these channels into
infrastructure.
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