TABLE OF CONTENTS Chapter No. Topic Page No. I Introduction 001 I-A Indian Financial System 001 I-B The Constituents Of Indian Banking System 003 I-C Future Lies Ahead 005 II Banking Risk 012 II-A Introduction to Banking Risk 012 II-B Risk Types and Risk Origination 018 II-C Functions of Central Department and Risk Department 019 III RBI – Credit Risk 020 III-A Credit Risk 020 III-B Building Blocks of Credit Risk Management 023 III-C Credit Rating Framework 032 III-D Credit Risk in Off-Balance Sheet Exposures 037 IV Credit Risk Models 039 V Credit Risk Scoring Models Developed By Banks 046 VI Credit Risk Models - Others 063 VI-A Altman’s Z – Scoring Model 064 VI-B KMV Model 066 VI-C Creditmetrics Approach 067 VI-D Creditrisk+ 068 VI-E VaR & Risk Management 069 VII Managing Credit Risk in Inter Bank Exposure 076 VIII Basel and Credit Risk 085 IX Credit Risk Management – A Deeper Look 118 X Non Performing Assets 152 XI RAROC Pricing/ Economic Profit 179 XII Credit Derivatives 184 XIII Credit Audit 208
Transcript
TABLE OF CONTENTSChapter
No.Topic Page No.
I Introduction 001I-A Indian Financial System 001I-B The Constituents Of Indian Banking System 003
I-C Future Lies Ahead 005II Banking Risk 012II-A Introduction to Banking Risk 012II-B Risk Types and Risk Origination 018II-C Functions of Central Department and Risk
Department019
III RBI – Credit Risk 020III-A Credit Risk 020III-B Building Blocks of Credit Risk Management 023
IV Credit Risk Models 039V Credit Risk Scoring Models Developed By Banks 046VI Credit Risk Models - Others 063VI-A Altman’s Z – Scoring Model 064VI-B KMV Model 066VI-C Creditmetrics Approach 067VI-D Creditrisk+ 068VI-E VaR & Risk Management 069VII Managing Credit Risk in Inter Bank Exposure 076VIII Basel and Credit Risk 085IX Credit Risk Management – A Deeper Look 118X Non Performing Assets 152XI RAROC Pricing/ Economic Profit 179XII Credit Derivatives 184XIII Credit Audit 208
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Credit Risk Management in Banks Project Guide – Prof. Anil Mahajan
BIBLIOGRAPHYBooksi) Risk Management In Banking - Joel Bessisii) Risk Management - ICFAIiii) Credit Risk Management - Taxmann Publicationsiv) Financial management In Banks - IIBFv) ICFAI Reader - ICFAI Pressvi) Professional Banker - ICFAI Pressvii) Business Indiaviii) Business Todayix) Business World
o From the earlier revenue = cost + profit equation i.e., customers are
charged to cover the costs incurred and the profits expected,
o Most banks have already moved into the profit =revenue - cost equation.
This has been reflected in the fact that with cost of services staying nearly equal
across banks, the banks with better cost control are able to achieve higher profits
whereas the banks with high overheads due to under-utilisation of resources, un-
remunerative branch network etc., either incurred losses or made profits not
commensurate with the capital employed.
o The new paradigm in the coming years will be cost = revenue - profit.
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Banks will increasingly act as risk managers to corporate and other entities by offering
a variety of risk management products like options, swaps and other aspects of
financial management in a multi currency scenario.
Bancassurance is catching up and Banks / Financial Institutions have started entering
insurance business. This could lead to a spurt in fee-based income of the banks.
Human Resources Management
The key to the success of any organization lies in how efficiently the organization
manages its' human resources. The principle applies equally and perhaps more aptly to
service institutions like banks. The issue is all the more relevant to the public sector
banks who are striving hard to keep pace with the technological changes and meet the
challenges of globalization.
In order to meet the global standards and to remain competitive, banks will have to
recruit specialists in various fields such as Treasury Management, Credit, Risk
Management, IT related services, HRM, etc. in keeping with the segmentation and
product innovation. As a complementary measure, fast track merit and performance
based promotion from within would have to be institutionalized to inject dynamism
and youthfulness in the workforce.
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CHAPTER II BANKING RISK
II-A INTRODUCTION TO BANKING RISK
Banking risk are defined as adverse impacts on profitability of several distinct sources of
uncertainty. Risk measurement requires capturing the source of the uncertainty and the
magnitude of its potential adverse effect on profitability. Profitability refers to both
accounting and mark-to-market measures.
Other Risks
Settlement & Performance
Risk
Country Risk
Foreign Exchange
Risk
Operational Risk
Liquidity Risk
Market Risk
Interest Risk
Credit Risk
Types of Bank Risk
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1. Credit Risk
It is the first of all risks in terms of importance. Default risk, a major source of loss, is
the customers default, meaning that they fail to comply with their obligation to service
debt. Default triggers a total or partial loss of any amount lent to the counter party.
Credit risk is also the decline in the credit standing of an obligator of the issuer of a
bond or stock. Such deterioration does not apply default, but it does imply that the
probability of default increases.
The view of credit risk differs for the banking portfolio and the trading portfolio.
o Banking portfolio
Credit risk is important as the default of a small number of important customers
can generate large losses. There are various default events:
Delay in payment obligation – do not turn out as plain defaults, are resolved in
short periods.
Restructuring of debt obligations due to a major deterioration of the credit
standing of the borrower – very close to defaults because it is viewed that the
borrower will not face payment obligation unless its funding structure changes.
Plain defaults – implies that the non payment will be permanent
Bankruptcies – possibly liquidation of the firm or merging with the accruing
firm, are possible out comes. They all trigger significant losses. Default means
any situation other than a simple delinquency.
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o Trading portfolio
Capital market value the credit risk of issuers and borrowers in prices. Unlike
loans, the credit risk of traded debts is also indicated by the agencies’ ratings,
assessing the quality of public debt issues, or through changes of the value of their
stocks. The capability of trading market assets mitigates the credit risk since there
is no need to hold these securities until the deterioration of credit risk materialises
into effective losses. But same is not the case with over-the counter instruments
such as derivatives, whose development has been spectacular in the recent period,
sale is not readily feasible.
2. Interest Rate Risk
It is the risk of a decline in earnings due to the movements of interest rates. Most of the
items of banks’ balance sheet generates revenue and costs that are interest- rate driven.
Since interest rates are unstable, so are the earnings.
Any one who lends or borrower is subject to interest rate risk. The lender earnings a
variable rate has the risk of seeing revenue reduced by a decline in interest rates. The
borrower paying a variable rate bears higher costs when interest rates increases. Both
positions are risky since they generate revenues or costs indexed to market rates. The
other side of coin in that interest rates exposure generates chances of gains as well.
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3. Market Risk
It is the risk of adverse deviations of the mark-to-market value of the trading portfolio,
due to market movements, during the period to liquidate the transactions.
The period of liquidation is critical to assess such adverse deviations. If it gets longer,
so do the deviations from the current market value.
4. Liquidity Risk
It refers to multiple dimension; inability to raise funds at normal cost; market liquidity
risk, asset liquidity risk.
Funding risk depends upon on how risky the market perceives the issuer and its
funding policy to be. It materialises as a much higher cost of funds, although the cause
lies more with the market than the specific bank. The cost, a critically profitability
driver. also depends on the bank’s credit standings.
The liquidity of the market relates to liquidity crunches because of a lack of volume. It
materialises as an impaired ability to raise money at a reasonable cost.
Asset liquidity results from lack of liquidity related to the nature of assets rather than to
the market liquidity. Holding a pool of liquid assets acts a cushion against fluctuating
market liquidity because liquid assets allow meeting short-term obligations without
recourse to external funding.
Liquidity risk which might become a major risk for the banking portfolio, follows
adopting an Assets Liability management (ALM)
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5. Operational Risks
Operational risks are those of malfunctions of the information systems, reporting
systems, internal risk-monitoring rules and internal procedures designed to take timely
corrective actions, or compliance with internal risk policy rules.
The New Basel Accord of January 2001 defines operational risk as ‘the risk of direct or
indirect loss resulting from inadequate or failed internal processes, people and systems
or form external events. It appears at different; levels – People, Processes, Technical,
and Information Technology Model risk.
It is significant in the market universe, which traditionally makes relatively intensive
usage of models for pricing purposes. It is growing more important with the extension
of modeling techniques to other risks, notably credit risk, where scarcity of data
remains a major obstacle for testing the ratability of inputs and models.
6. Foreign Exchange Risk
The currency risk is that of incurring losses due to changes in the exchange rates.
Variations in earnings result from the indexation of revenues and charges to exchange
rates or of changes of the values of assets and liabilities denominated in foreign
currencies.
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7. Country Risk
The risk of a ‘crises’ in a country.
Sovereign risk, which is the risk of default of sovereign issuers, such as central bank or
government sponsored bank.
A deterioration of economic conditions.
A deterioration of the value of the local foreign currency in terms of the bank’s base
currency.
Impossibility of transfer of funds due to legal restrictions.
A market crisis.
Country risk is a floor for the risk of a local borrower, or equivalently, that the country
ratings cap local borrower’s ratings.
8. Performance Risk
It exists when the transaction risk depends upon more on how the borrower performs
for specific projects or operations than on overall credit standings. It appears notably
when dealing with commodities. It is ‘transactional’ because it relates to a specific
transaction.
9. Solvency Risk
It is the risk of being unable to absorb losses, generated by all types of risks, with the
available capital. It differs from bankruptcy risk resulting from defaulting on debt
obligations and inability to raise funds for meeting such obligations. Solvency risk is
equivalent to the default risk of the bank.
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II-B RISK TYPES AND RISK ORIGINATION
Risks Credit Market Liquidity InterestRate
Risk Management
General Management
Portfolio Management
ALM
Risk Department
Guidelines and Goals
Portfolio Risk – Return Profile
Risk Origination
Markets
Investment Bank
Commercial Bank
Figure shows who originates what risks and which ventral function supervise them.
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II-C FUNCTIONS OF CENTRAL DEPARTMENT AND RISK DEPARTMENT
Risk Department
Monitoring & Control of all RisksCredit & Market, in addition to ALMDecision-makingCredit PolicySetting LimitsDevelopment of Internal Tools and Risk Data WarehousesRisk-adjusted PerformancesPortfolio ActionsReporting to General Management
Market Risk
LimitsMeasures & Control of RisksCompliancesMonitoringHedgingBusiness ActionsReporting to General Management
Portfolio Management
Trading Credit RiskPortfolio ReportingPortfolio RestructuringSecuritizationsPortfolio ActionsReporting to General Management
Liquidity & Interest Rate Risk Management.Measure & Control of RisksCompliancesHedgingRecommendations: Balance Sheet ActionsTransfer Pricing systemsLCOReporting to General Management
Control
AccountingRegulatory ComplianceCost accountingBudgeting & PlanningMonitoring & ControlMonitoring PerformancesReporting to General Management
Functions of
Central Department And of
Risk Department
The functions of the different central units tend to differentiate from each other when going further into the details of risk and income actins.Figure illustrates the differentiation process of central function according to their perimeter of responsibilities.
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CHAPTER III RBI – CREDIT RISK
III-A CREDIT RISK
The RBI has defined credit risk as – the possibility of losses associated with diminution in
the credit quality of borrowers or counter parties. In a bank’s credit portfolio, losses stem
from outright default due to inability or unwillingness of a customer or counterparty to
meet their commitments in relation to lending. Trading, settlement and other financial
transactions. Alternatively, losses result from reduction in portfolio value arising from
actual or perceived deterioration in credit quality.
RBI has also sated, that credit risk emanates from bank’s dealings with an individual,
corporate, bank, financial institution or a sovereign and may take any of the following
forms-
a) in case of Direct Lending : Principal and/or interest amount may not be paid
b) in case of Guarantee or Letter of Credit: funds may not be coming from the
constituents upon crystallization of the liability.
c) In case of treasury Operations: The payment or series of payments due from the
counter parties under the respective contracts may not be forthcoming or ceases.
d) In the case of security Trading Business: Funds/Securities settlement may not be
effected.
e) In the case of cross-boarder exposure: The availability and free transfer of foreign
currency funds may either frozen or restrictions imposed by the action of, or
because of political/economic conditions in the country where borrower is located.
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In spite of the fact that the RBI has been laying a lot of emphasis on strengthening of credit
appraisal and monitoring systems in banks, credit quality continues to deteriorate as
reflected in high level of non-performing which continue to increase.
Factors causing credit risk
(i) Deficiency in appraisal of loans proposals and in assessment of
creditworthiness/financial strength of borrowers.
(ii) Inadequately defined lending policies and procedures.
(iii) High prudential exposure limits for individual and group of borrowers.
(iv) Absence of credit concentration limits for various industries/business
segments.
(v) Inadequate value of collaterals obtained by the banks to secure the loan facility.
(vi) Over optimistic assessment of thrust/potential areas of credit.
(vii) Liberal loans sanctioning powers for bank executives without checks and
balances.
(viii) Liberal sanctioning of non-fund based limits without proper scrutiny of
borrower’s activity, financial strength, cash flows etc.
(ix) Lack of knowledge and skills of official processing loan and subjectivity in credit
deacons.
(x) Lack of effective monitoring and consistent approach towards early recognition of
problem account and initiation of timely remedial actions.
(xi) Lack of information on functioning of various industries and performance of
economy.
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(xii) Lack of proper coordination between various departments of banks looking into
credit functions.
(xiii) Lack of well defined organisational structure and clarity with regard to
responsibilities, authorities and communication channels.
(xiv) Lack of credit proper systems of credit risk rating quantifying and managing
across geographical and product lines.
(xv) Lack of effectiveness of existing credit inspection and audit systems I banks and
slow progress in removal of deficiencies as revealed in inspection/audit of branches
and controlling offices.
(xvi) Lack of reliability and integrity of data being used for managing credit risks
associated with lending.
(xvii)Banks have been harping too much on staff accountability as a result
demotivating the staff and not looking at the credit decisions from hind sight.
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III-B BUILDING BLOCKS OF CREDIT RISK MANAGEMENT:
In a bank, an effective credit risk management framework would comprise of the following
distinct building blocks:
a) Policy and Strategy
b) Organisational Structure
c) Operations/ Systems
III-B-1 POLICY AND STRATEGY
The Board of Directors of each bank shall be responsible for approving and periodically
reviewing the credit risk strategy and significant credit risk policies.
Credit Risk Policy
Every bank should have a credit risk policy document approved by the Board. The
document should include risk identification, risk measurement, risk grading/
aggregation techniques, reporting and risk control/ mitigation techniques,
documentation, legal issues and management of problem loans.
Credit risk policies should also define target markets, risk acceptance criteria, credit
approval authority, credit origination/ maintenance procedures and guidelines for
portfolio management.
The credit risk policies approved by the Board should be communicated to
branches/controlling offices. All dealing officials should clearly understand the bank’s
approach for credit sanction and should be held accountable for complying with
established policies and procedures.
Senior management of a bank shall be responsible for implementing the credit risk
policy approved by the Board.
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Credit Risk Strategy
Each bank should develop, with the approval of its Board, its own credit risk strategy or
plan that establishes the objectives guiding the bank’s credit-granting activities and adopt
necessary policies/ procedures for conducting such activities. This strategy should spell
out clearly the organisation’s credit appetite and the acceptable level of risk-reward trade-
off for its activities.
The strategy would, therefore, include a statement of the bank’s willingness to grant loans
based on the type of economic activity, geographical location, currency, market, maturity
and anticipated profitability. This would necessarily translate into the identification of
target markets and business sectors, preferred levels of diversification and concentration,
the cost of capital in granting credit and the cost of bad debts.
The credit risk strategy should provide continuity in approach as also take into account the
cyclical aspects of the economy and the resulting shifts in the composition/ quality of the
overall credit portfolio. This strategy should be viable in the long run and through various
credit cycles.
Senior management of a bank shall be responsible for implementing the credit risk
strategy approved by the Board.
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III-B-2 ORGANISATIONAL STRUCTURE
Sound organizational structure is sine qua non for successful implementation of an
effective credit risk management system. The organizational structure for credit risk
management should have the following basic features:
The Board of Directors
o It should have the overall responsibility for management of risks.
o The Board should decide the risk management policy of the bank and set limits
for liquidity, interest rate, foreign exchange and equity price risks.
The Risk Management Committee
o It will be a Board level Sub committee including CEO and heads of Credit,
Market and Operational Risk Management Committees.
o It will devise the policy and strategy for integrated risk management
containing various risk exposures of the bank including the credit risk. For this
purpose, this Committee should effectively coordinate between the Credit Risk
Management Committee (CRMC), the Asset Liability Management
Committee (ALCO) and other risk committees of the bank, if any.
o It is imperative that the independence of this Committee is preserved. The Board
should, therefore, ensure that this is not compromised at any cost.
o In the event of the Board not accepting any recommendation of this
Committee, systems should be put in place to spell out the rationale for such an
action and should be properly documented.
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o This document should be made available to the internal and external auditors for
their scrutiny and comments. The credit risk strategy and policies adopted by the
committee should be effectively communicated throughout the organisation.
Credit Risk Management Committee (CRMC).
o Each bank may, depending on the size of the organization or loan/ investment
book, constitute a high level CRMC.
o The Committee should be headed by the Chairman/CEO/ED, and should
comprise of heads of Credit Department, Treasury, Credit Risk Management
Department (CRMD) and the Chief Economist.
o The functions of the Credit Risk Management Committee should be as under:
Be responsible for the implementation of the credit risk policy/ strategy approved
by the Board.
Monitor credit risk on a bank wide basis and ensure compliance with limits
approved by the Board.
Recommend to the Board, for its approval, clear policies on standards for
presentation of credit proposals, financial covenants, rating standards and
benchmarks,
Decide delegation of credit approving powers, prudential limits on large credit
exposures, standards for loan collateral, portfolio management, loan review
mechanism, risk concentrations, risk monitoring and evaluation, pricing of loans,
provisioning, regulatory/legal compliance, etc.
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Credit Risk Management Department (CRMD)
o Concurrently, each bank should also set up CRMD, independent of the Credit
Administration Department.
o The functions of CRMD are:
Measure, control and manage credit risk on a bank-wide basis within the limits set
by the Board/ CRMC
Enforce compliance with the risk parameters and prudential limits set by the Board/
CRMC.
Lay down risk assessment systems, develop MIS, monitor quality of loan/
investment portfolio, identify problems, correct deficiencies and undertake loan
review/audit. Large banks could consider separate set up for loan review/audit.
Be accountable for protecting the quality of the entire loan/ investment portfolio.
The Department should undertake portfolio evaluations and conduct comprehensive
studies on the environment to test the resilience of the loan portfolio.
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III-B-3 OPERATIONS / SYSTEMS
Banks should have in place an appropriate credit administration, credit risk measurement and
monitoring processes. The credit administration process typically involves the following
phases:
Relationship management phase i.e. business development.
o Transaction management phase covers risk assessment, loan pricing, structuring the
facilities, internal approvals, documentation, loan administration, on going monitoring
and risk measurement.
o Portfolio management phase entails monitoring of the portfolio at a macro level and
the management of problem loans.
On the basis of the broad management framework stated above, the banks should have the
following credit risk measurement and monitoring procedures:
o Banks should establish proactive credit risk management practices like annual /
half yearly industry studies and individual obligor reviews, periodic credit calls
that are documented, periodic visits of plant and business site, and at least quarterly
management reviews of troubled exposures/weak credits.
o Banks should have a system of checks and balances in place for extension of
credit viz.:
Separation of credit risk management from credit sanction
Multiple credit approvers making financial sanction subject to approvals at
various stages viz. credit ratings, risk approvals, credit approval grid, etc.
An independent audit and risk review function.
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o The level of authority required to approve credit will increase as amounts and
transaction risks increase and as risk ratings worsen.
o Every obligor and facility must be assigned a risk rating.
o Mechanism to price facilities depending on the risk grading of the customer, and
to attribute accurately the associated risk weightings to the facilities.
o Banks should ensure that there are consistent standards for the origination,
documentation and maintenance for extensions of credit.
o Banks should have a consistent approach towards early problem recognition, the
classification of problem exposures, and remedial action.
o Banks should maintain a diversified portfolio of risk assets; have a system
to conduct regular analysis of the portfolio and to ensure on-going control of risk
concentrations.
o Credit risk limits include, obligor limits and concentration limits by industry
or geography. The Boards should authorize efficient and effective credit approval
processes for operating within the approval limits.
o In order to ensure transparency of risks taken, it is the responsibility of banks to
accurately, completely and in a timely fashion, report the comprehensive set of
credit risk data into the independent risk system.
o Banks should have systems and procedures for monitoring financial performance of
customers and for controlling outstanding within limits.
o A conservative policy for provisioning in respect of non-performing
advances may be adopted.
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o Successful credit management requires experience, judgement and commitment
to technical development. Banks should have a clear, well-documented scheme of
delegation of powers for credit sanction.
Banks must have a Management Information System (MIS), which should enable them to
manage and measure the credit risk inherent in all on- and off-balance sheet activities.
The MIS should provide adequate information on the composition of the credit portfolio,
including identification of any concentration of risk. Banks should price their loans
according to the risk profile of the borrower and the risks associated with the loans.
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TYPICAL ORGANISATIONAL STRUCTURE FOR RISK MANAGEMENT
BOARD OF DIRECTORS
Risk Planning - Definition of procedures
- Design of credit processes
Credit Risk –Systems- Integration of risk Procedures with credit systems- Design and development of support systems for risk assessment & monitoring
Risk Analytics- Credit Risk and Pricing models’ Design & Maintenance- Portfolio analysis And reporting
Risk Assessment and Monitoring - Sector review- Credit Rating- Review of Credit Proposals (new)- Asset review (existing)
CREDIT RISK MANAGEMENT COMMITTEE (COMMITTEE OF TOP EXECUTIVES INCLUDING CEO, HEADS OF CREDIT & TREASURY, AND CHIEF ECONOMIST)
RISK MANAGEMENT COMMITTEE(BOARD SUBCOMMITTEE INCLUDING CEO AND HEADS OF CREDIT, MARKET AND
OPERATIONAL RISK MANAGEMENT COMMITTEES)CORE FUNCTION: POLICY AND STRATEGY FOR INTEGRATED RISK MANAGEMENT
CREDIT RISK MANAGEMENT DEPARTMENT (CRMD)
CREDIT ADMINISTRATION DEPARTMENT (CAD)
OPERATIONALRISK MANAGEMENT COMMITTEE
ALCO/ MARKET RISKMANAGEMENT COMMITTEE
Relationship Management & Business Development- Processing the loans – Risk Assessment, Pricing, Structuring the facilities documentation, Disbursement
-Ongoing monitoring & Risk Management- Maintaining of Problem account- Monitoring of Credit Portfolio at macro level
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III-C CREDIT RATING FRAMEWORK
A Credit-risk Rating Framework (CRF) is necessary to avoid the limitations associated
with a simplistic and broad classification of loans/exposures into a “good” or a “bad”
category. The CRF deploys a number/ alphabet/ symbol as a primary summary
indicator of risks associated with a credit exposure. Such a rating framework is the
basic module for developing a credit risk management system and all advanced
models/approaches are based on this structure. In spite of the advancement in risk
management techniques, CRF is continued to be used to a great extent. These
frameworks have been primarily driven by a need to standardise and uniformly
communicate the “judgement” in credit selection procedures and are not a substitute to
the vast lending experience accumulated by the banks' professional staff.
Broadly, CRF can be used for the following purposes:
a. Individual credit selection, wherein either a borrower or a particular exposure/
facility is rated on the CRF.
b. Pricing (credit spread) and specific features of the loan facility. This would largely
constitute transaction-level analysis.
c. Portfolio-level analysis.
d. Surveillance, monitoring and internal MIS
e. Assessing the aggregate risk profile of bank/ lender. These would be relevant for
portfolio-level analysis. For instance, the spread of credit exposures across various
CRF categories, the mean and the standard deviation of losses occurring in each
CRF category and the overall migration of exposures would highlight the
aggregated credit-risk for the entire portfolio of the bank.
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Credit risk rating frame work – highlights of RBI Guidelines
(a) Banks should develop a well-structured credit risk-rating framework by using any
number of operational parameters, financial ratios, collaterals, qualitative aspects
of management and industry characteristics.
(b) The score allotted to each parameter may depend upon their risk predicting
capacity. An illustrative list of parameters have also been provided in the RBI’s
guidelines.
(c) Risk taking framework for large mid corporates, small-scale units traders etc. can
vary. Normally it should have nine grades, of which first five may represent
acceptable credit while reaming four as unacceptable risk.
(d) Rating framework should have some minimum cut off score below which no
credit proposals should be entertained. For any relaxation, clear guidelines be
given in the loan policy document specially indicating the authority who can
permit such relaxation.
(e) Risk taking exercise should be undertaken normally at quarterly interval or at
least on half yearly basis to assess the migration in the credit quality.
(f) Implementation of credit – Risk rating structure by banks
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It should serve the following purposes:
(i) Taking credit decisions: whether to lend a borrower or not. A borrower with high
rating be financed.
(ii) Pricing of the loans (fixation of interest rates): A borrower falling in higher risk
category be priced higher.
(iii) Mitigation of risk – the extent of borrowers contribution in the form of the
margin and collaterals can be demanded based on the borrower’s risk-rating
category.
(iv) Nature of facilities: Whether to sanction cash credit, term loan or demand loan to a
borrower which may depend upon its risk categorization. Demand loan or term loan for
shorter period may be considered where risk involved is high.
(v) Delegation of Loaning Power: higher loaning powers may be vested to the field
functionaries for sanction of loans to borrowers who are rated high with
practically no risk. For borrowers falling under high risk categories, approvals of
loans be considered at higher level of authority.
(vi) Selective monitoring: it is difficult for banks to pay same degree of attention to
all the loan account due to fast expansion of credit. Borrowers who fall under
high risk rating categories can be kept under closer monitoring i.e. to be
monitored more frequently than the low risk borrowers.
(vii) Ensuring Quality: Judging quality of total credit portfolio as also under various
segments i.e. industry, trade, transport, agriculture etc. (large/medium/small).
Also identifying problem accents and the risk concentration in credit portfolio.
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(viii) Mitigation of Credit: Effectively monitoring the overall credit portfolio by
looking at the movement and mitigation of the portfolio, from higher to lower
risk categories and vice versa.
(ix) Management of Credit Risk: Effective management of credit risk by evolving
effective and robust credit polices and procedures which are sensitive and
responsive to changes.
(x) Identification of the trust areas of credit which are looking up and safe as also
those which are risky having high default risk.
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Basic Architecture of CRFs
The following elements outline the basic architecture and the operating principles of any
CRF.
2.3.1 Grading system for calibration of credit risk
Nature of grading system
Number of grades used
Key outputs of CRF
2.3.2 Operating design of CRF
Which exposures are rated?
The risk rating process
Assigning and monitoring risk ratings
The mechanism of arriving at risk ratings
Standardisation and benchmark for risk ratings
Written communications and formality of procedures
2.3.3 CRFs and Portfolio Credit Risk
Portfolio surveillance and reporting
Adequate levels of provisioning for credit events
Guidelines for asset build up, aggregate profitability and pricing
Interaction with external credit assessment institutions
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III-D CREDIT RISK IN OFF-BALANCE SHEET EXPOSURES
Risk Identification and Assessment of Limits
Credit Risk in non-fund based business of banks need to be assessed in a manner
similar to the assessment of fund based business since it has the potential to become a
funded liability in case the customer is not able to meet his commitments. Financial
guarantees are generally long term in nature, and assessment of these requirements
should be similar to the evaluation of requests for term loans. As contracts are
generally for a term of 2-3 years, banks must obtain cash flows over this time horizon,
arising from the specific contract they intend to support, and determine the viability of
financing the contract.
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Risk Monitoring and Control
For reducing credit risk on account of such off balance sheet exposures, banks may
adopt a variety of measures some of which are indicated below:
i) Banks must ensure that the security, which is available to the funded lines, also
covers the Letter of Credit lines and the guarantee facilities. On some occasions, it
will be appropriate to take a charge over the fixed assets as well, especially in the
case of long-term guarantees.
ii) In the case of guarantees covering contracts, banks must ensure that the clients
have the requisite technical skills and experience to execute the contracts. The
value of the contracts must be determined on a case-by-case basis, and separate
limits should be set up for each contract. The progress vis-à-vis physical and
financial indicators should be monitored regularly, and any slippages should be
highlighted in the credit review.
iii) The strategy to sanction non-fund facilities with a view to increase earnings should
be properly balanced vis-à-vis the risk involved and extended only after a thorough
assessment of credit risk is undertaken.
The architecture and operating principles are discussed in detail in the ensuing paragraphs.
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CHAPTER IV CREDIT RISK MODELS
A credit risk model seeks to determine, directly or indirectly,
Our past experience and our assumptions about the future,
What is the present value of a given loan or fixed income security?
The (quantifiable) risk that the promised cash flows will not be forthcoming.
The increasing importance of credit risk modelling should be seen as the consequence
of the following three factors:
o Banks are becoming increasingly quantitative in their treatment of credit
risk.
o New markets are emerging in credit derivatives and the marketability of
existing loans is increasing through securitisation/ loan sales market.
o Regulators are concerned to improve the current system of bank capital
requirements especially as it relates to credit risk.
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Importance
o These models provide the decision maker with insight or knowledge that
would not otherwise be readily available or that could be marshalled at
prohibitive cost.
o In a marketplace where margins are fast disappearing and the pressure to
lower pricing is unrelenting, models give their users a competitive edge.
o The credit risk models are intended to aid banks in quantifying, aggregating
and managing risk across geographical and product lines.
o The outputs of these models also play increasingly important roles in banks’
risk management and performance measurement processes, customer
profitability analysis, risk-based pricing, active portfolio management and
capital structure decisions.
o Credit risk modelling may result in better internal risk management and
may have the potential to be used in the supervisory oversight of banking
organisations.
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In the measurement of credit risk, models may be classified along three different
dimensions:
1 .Technique1s: The following are the more commonly used techniques:
(a) Econometric Techniques such as linear and multiple discriminate analysis,
multiple regression, logic analysis and probability of default, etc.
(b) Neural networks are computer-based systems that use the same data
employed in the econometric techniques but arrive at the decision model
using alternative implementations of a trial and error method.
(c) Optimisation models are mathematical programming techniques that
discover the optimum weights for borrower and loan attributes that minimize
lender error and maximise profits.
(d) Rule-based or expert systems are characterised by a set of decision rules, a
knowledge base consisting of data such as industry financial ratios, and a
structured inquiry process to be used by the analyst in obtaining the data on a
particular borrower.
(e) Hybrid Systems In these systems simulation are driven in part by a direct
causal relationship, the parameters of which are determined through
estimation techniques.
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2. Domain of application: These models are used in a variety of domains:
(a) Credit approval: Models are used on a stand alone basis or in conjunction with
a judgemental override system for approving credit in the consumer lending
business. The use of such models has expanded to include small business
lending. They are generally not used in approving large corporate loans, but
they may be one of the inputs to a decision.
(b) Credit rating determination: Quantitative models are used in deriving
‘shadow bond rating’ for unrated securities and commercial loans. These
ratings in turn influence portfolio limits and other lending limits used by the
institution. In some instances, the credit rating predicted by the model is used
within an institution to challenge the rating assigned by the traditional credit
analysis process.
(c) Credit risk models may be used to suggest the risk premia that should be
charged in view of the probability of loss and the size of the loss given default.
Using a mark-to-market model, an institution may evaluate the costs and
benefits of holding a financial asset. Unexpected losses implied by a credit
model may be used to set the capital charge in pricing.
(d) Early warning: Credit models are used to flag potential problems in the
portfolio to facilitate early corrective action.
(e) Common credit language: Credit models may be used to select assets from a
pool to construct a portfolio acceptable to investors at the time of asset
securitisation or to achieve the minimum credit quality needed to obtain the
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desired credit rating. Underwriters may use such models for due diligence on
the portfolio (such as a collateralized pool of commercial loans).
(f) Collection strategies: Credit models may be used in deciding on the best
collection or workout strategy to pursue. If, for example, a credit model
indicates that a borrower is experiencing short-term liquidity problems rather
than a decline in credit fundamentals, then an appropriate workout may be
devised.
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MMS Finance Final Term End Project Krupesh Thakkar – 59
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3. Credit Risk Models: Approaches
The literature on quantitative risk modelling has two different approaches to credit risk
measurement.
(a) The first approach is the development of statistical models through analysis of
historical data. This approach was frequently used in the last two decades. The
statistical approach tries to rate the firms on a discrete or continuous scale. The
linear model introduced by Altman (1967), also known as the Z-score Model,
separates defaulting firms from non-defaulting ones on the basis of certain
financial ratios. Altman, Hartzell, and Peck (1995, 1996) have modified the
original Z-score model to develop a model specific to emerging markets. This
model is known as the Emerging Market Scoring (EMS) model.
(b) The second type of modelling approach tries to capture distribution of the firm's
asset-value over a period of time. The second type of modelling approach tries
to capture distribution of the firm's asset-value over a period of time. This
model is based on the expected default frequency (EDF) model. It calculates the
asset value of a firm from the market value of its equity using an option pricing
based approach that recognizes equity as a call option on the underlying asset of
the firm. It tries to estimate the asset value path of the firm over a time horizon.
The default risk is the probability of the estimated asset value falling below a
pre-specified default point. This model is based conceptually on Merton's
(1974) contingent claim framework and has been working very well for
estimating default risk in a liquid market.
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(c) Closely related to credit risk models are portfolio risk models. In the last three
years, important advances have been made in modelling credit risk in lending
portfolios. The new models are designed to quantify credit risk on a portfolio
basis, and thus are applied at the time of diversification as well as portfolio
based pricing. These models estimate the loss distribution associated with the
portfolio and identify the risky components by assessing the risk contribution of
each member in the portfolio.
Banks may adopt any model depending on their size, complexity, risk bearing capacity
and risk appetite, etc. However, the credit risk models followed by banks should, at the
least, achieve the following:
o Result in differentiating the degree of credit risk in different credit exposures of a
bank. The system could provide for transaction-based or borrower-based rating or
both. It is recommended that all exposures are to be rated. Restricting risk
measurement to only large sized exposures may fail to capture the portfolio risk in
entirety for variety of reasons. For instance, a large sized exposure for a short time
may be less risky than a small sized exposure for a long time
o Identify concentration in the portfolios
o Identify problem credits before they become NPAs
o Identify adequacy/ inadequacy of loan provisions
o Help in pricing of credit
o Recognise variations in macro-economic factors and a possible impact under
alternative scenarios
o Determine the impact on profitability of transactions and relationship.
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CHAPTER V CREDIT RISK SCORING-MODELS DEVELOPED BY BANKS
Keeping in view the parameters used by some banks in their credit risk scoring and
rating systems in line with RBI broad guidelines and those used by eminent persons in
their models, an attempt has been made to evolve a simple but effective model by using
parameters which have significant “Predictive Power”, are more objective/sensitive in
nature and are related to the following four main heads.
I. Operational/Financial Performance of the Unit
II. Banks Accounts and securities available
III. Business/Industry Outlook
IV. Promoters/Management
I. Operational/financial performance of the unit: - the parameters are
(i) plant capacity utilization in
relation to installed
capacity
(ii) Break-even point in relation to
installed plant capacity
(iii) Sales trend in last 3 years
(iv) Profit earned during last 3
years
(v) Achievement of sales
projections
(vi) achievement of profit
projection
(vii) net profit to net sales ratio
(viii) return of capital employed
(ix) ratio of current assets to current
liability
(x) Debt – equity ratio
(xi) Debt-service coverage ratio
(xii) Ratio of net sales per annum to
working capital
(xiii) Ratio of net sales per annum to
fixed/total assets
(xiv) Inventory turnover ratio
(xv) Average collection period of
receivables
(xvi) Average payment period of accounts
payable
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II. Bank accounts & Securities available
(i) Conduct of fund and non-fund based accounts with bank/financial institutions –
whether there are regular/irregular
(ii) Compliance of terms/conditions stipulated by banks/financial institutions while
scanning the loans
(iii) Position of annual renewal/review of the loans facilities.
(iv) Position with regard to submission of balance sheet and profit/loss accounts,
monitoring data and inventory statement etc.
(v) Nature and value of securities (primary/collateral) offered to cover the loan
facilities.
(vi) Validity of creation of charge on the securities.
(vii) Interest and other income being earned by the banks.
(viii) Tenability of loan documents in the court of law.
(ix) Position of contingent liabilities, if any.
(x) Transparency and disclosure in audited annual accounts
(xi) Diversion of short-term funds for long term users
(xii) Unauthorized withdrawal of funds for personal use or diversion of funds for
investments in allied/associate and other firms.
(xiii) Utilization of loans sanctioned by banks/financial institutions for purpose other
than those for which these have been lent.
(xiv) Auditors comments on quality and valuation of current/fixed assets
III Business and Industry Outlook
(i) Intensity of market competition faced by the industry.
(ii) Technology used and whether it is successfully implemented and chances of
its obsolescence
(iii) Market demand and growth potential for the products
(iv) Quality of product(s) and their market acceptability
(v) Threats of substitutes available and likely to come in the market
(vi) Export potential for the products
(vii) Position with regard to availability of raw material
(viii) Import barriers, if any, imposed by the Government
(ix) Units’ locational advantages and disadvantages
(x) General outlook and capital market perception of the industry
(xi) Threat of dumping products by foreign companies
(xii) Type of product(s) whether customized or are for general use
(xiii) Foreign exchange component (risk) in total business covering both
exports/imports
(xiv) Nature of product(s), their applications and shelf life
(xv) Volatility of prices of finished goods and basic inputs/materials used
(xvi) Fluctuations in demand/supply of products both present and expected in
future
IV. Promoters/Management
(i) Ownership pattern of the unit, i.e. whether Public/Private Ltd. Partnership, Prop.
Ship etc.
(ii) Qualifications, experiences and knowledge of industry/business
(iii) Integrity, commitment and sincerity
(iv) Market reputation and creditability
(v) Track record of debt repayment
(vi) financial strength and their capacity to raise more funds
(vii) Pending statutory dues and litigations, if any.
(viii) Functioning of top management personnel
(ix) History of dividends/bonus issues declared
(x) Future succession plan.
Before designing any credit risk scoring and rating systems by using some of the
parameters which have more predictive powers, sensitive and objective, it would be
appropriate consider some of the models for assessment units, health and default
probabilities.
We will look at these parameters and their scoring in details
I. Operational and Financial Performance (Max score 80)
Operational and Financial Performance of the unit being rated may be judged from
certain parameters explained below:
1. Plant Capacity Utilization (Max Score 10)
It is an important which can tell a lot about the Unit’s functioning. Low plant capacity
utilization is a disturbing feature which can be due to various reasons like, lack of
demand, imbalance in plant/machinery, frequent break downs due to plant being old etc.
whatever may be the reason, it would have an adverse effect on unit’s functioning and
ultimately on its profitability. It may be mentioned that level of plant capacity utilization
may very from the nature of industry, process of manufacture etc. it will be desirable to
compare this parameter with the average capacity utilization of other 4/5 peer units
engaged in similar activity and having plant/machinery more or less of same installed
capacity. In case the average capacity utilization of peer units in X then score allotted for
various levels of plant capacity utilization may be as under.
Plant Capacity Utilisation
> 1.25X 1.10 to 1.25X
X to < 1.10X
0.9X to< X
0.8X to 0.9X
.7X to<.80X
<.70X
Score 10 9 8 6 4 2 0OR
In case data about peer units is not available, the score will be allotted based on
comparison of actual utilization of plant capacity with the projections accepted by the
bank while sanctioning the loan.
Plant Capacity Utilisation (%)
100% or more
95-99% 90-94% 85-89% 80-84% 75-79% <75%
Score 10 9 8 6 4 2 0
2. Current Ratio (Max Score 10)
This ratio helps in measuring the liquidity and solvency of a company. Higher ratio may
be good for the creditors but a very high ratio may have impact on the company’s
profitability. The distribution of score for various levels of current Ratio is indicated
below:
Current Ratio 1.50 or more 1.30 to <1.50 1.15 to <1.30 1.0 to < 1.15 < 1.0Score 10 8 6 3 04
3. Return on Capital Employed (Max Score 10)
The percentage return on capital employed is a good indicator fro company’s earning
capacity. Any company having return on capital lower than cost of capital employed is
undesirable. The score distribution is:
ROCE >20% 17 to 20% 14 to <17% 12 to <14% 10 to <12% < 10%Score 10 8 6 4 2 0
Current Assets Current Ratio =
Current Liabilities
PBITROCE = Capital Employed
4. Debt Service Coverage Ratio (Max Score 10)
The ratio measures the capacity of the company to service its debt i.e. repaying the term
liabilities and interest thereon. The score to be allotted are:
DSCR >2.0 1.8 to 2.0 1.6 to < 1.8 1.3 to < 1.6 1.0 to < 1.3 <1.0Score 10 9 7 5 2 0
5. Debt Equity Ratio (Max Score 10)
The ratio pf Promoters/Shareholders stake in business when compared to total debts,
Lower D/E Ratio means, higher long term stability in case the ratio is gradually coming
down, represents plough back of profit.
D/E Ratio Upto 1.0 >1.0 to 1.5 .>1.5 to 2.0 .>2.0 to 2.5 > 2.5 to 3.0 .>3.0Score 10 9 7 5 2 0
6. Achievement of Net Sales Projections (Max Score 10)
The level of achievement of net sales when compared to projections is an important
indicator for unit’s efficient functioning.
% achievement of Net Sales Projection
95% and more
90% to < 95%
85% to < 90%
80% to < 85%
75% to<80%
Below 75%
Score 10 9 7 5 3 0
Net Profit + Dep+ InterestDSCR = Annual Repayments of term loan + interest there on
Total Debts D/E =
Tangible Net Worth
7. Achievement of Net Profit Projections (Max Score 10)
The level of achievement of net profit when compared to projection is important indicator
fro unit’s efficient functioning and control on its expenditure.
% achievement of Net Profit Proj.
95% and more
90% to < 95%
85% to < 90%
80% to < 85%
75% to<80%
Below 75%
Score 10 9 7 5 3 0
8. Future Cash Flow Projection (Max Score 10)
Banks obtain Cash flow Statements from the borrowing companies to assess as to whether the
company would have enough profit generation and surplus funds to repay its term loan
installments or to meet the capital expenditure as envisaged in the projections given by the
company. The various situations and scores are:
Future Cash Flows
Company will have enough profit and surplus generation of funds to meet its obligations including payment of interest and loan installments
Company will have enough profit and surplus funds after taking into account the loans already sanctioned to be released shortly.
Company will have enough profit and surplus funds after taking into account only the loans applied for by the company which are yet to be sanctioned/released.
Company may not have enough profit and surplus funds to meet its loan repayments obligations and may default.
Score 10 7 4 0
II. Conduct of Bank accounts & Availability of Collaterals (Max Score 45)
The conduct of bank accounts with banks/FIs is to be evaluated in the context of
regularity in accounts which may depend on timely payment of interest and installments
of the loans. In addition, the conduct of accounts can be gauged from compliance of
terms/conditions related to the loan and timely submission of data/information to the
bank and securities offered by the borrower to secure bank loans. Other aspect related to
this head may include operations in non-fund based limits, diversion of funds. The
parameters and score allotted to them are given below.
1. Conduct of Bank Accounts Regular/Irregular) (Max Score 10)
Accounts running regular & their conduct satisfactory
Accounts remained irregular for 15 days
Accounts remained irregular for 16-30 days
Accounts remained irregular for 31-45 days
Accounts remained irregular for More than 45 days
Score 10 8 6 3 0
2. Compliance of Terms and Conditions of Sanction (Max Score 5)
All conditions complied Conditions relating to security creation complied while others still remain to be complied.
Conditions of security creation are yet to be complied while other conditions complied.
Conditions have not been complied
Score 5 4 2 0
3. Discipline in timely submission of Financial Data/Stock Statements etc. (Max Score 5)
% to total sanctioned limits both fund and non-fund based
>200% 175 to 200%
150 to <175%
125 to <150%
100 to < 125%
<100%
Score 10 8 6 4 2 0
5. Operations in Non-Fund Based Loan Limits (Max Score 5)
Non-fund based loan limits generally include Letter of Guarantee, Letter of Credit Limit.
These are called non-fund based limits as these as these do not involve extending any
funds or money. Those, however, involve commitments by banks on behalf of their
customers to pay in the event of default by the customers. Of late it is observed that many
a timers the non-fund based limits get converted into fund based as the borrowers some
times delay and even default in honoring their commitment. It is why RBI has advised
banks that appraisal standards while sanctioning non-fund based limits should not be
diluted.
Operations in non-fund based limits
Borrower honors his commitments and arranges funds whenever L/C or L/G liability falls due.
Borrower generally arranges funds whenever liabilities devolve/or takes maximum 15 days in meeting his liabilities.
Borrower generally delays in arranging the funds whenever the liability devolve. The period of delay goes upto 30 days.
Borrower generally delays in arranging funds whenever non-fund based limits devolve. The delay is generally more than 30 days.
Score 5 4 2 0
6. Diversion of Funds (Max Score 10)
Banks take a serous view whenever they observe that the borrowers are diverting funds to
their allied and associates concerns particularly when they are themselves not doing well.
The diversion may affect the company’s liquidity and operations.
Diversion of funds
Company is not diversing any funds
Company has diverted funds my be from short terms to long terms to be utilised in the company itself to meet emergent needs.
Company has diverted funds to its allied associate concerns by marinating current ratio and D/E ratio within banks acceptable limits.
Company has diverted funds to its allied/associate concerns and for repayment of unsecured loans by affecting it CR and/or DER beyond norms acceptable to banks.
Score 10 7 4 0
III. Industry/Business Outlook (Max Score 40)
Future outlook of ay unit can be gauged from certain parameters.
1. Growth Rate – in terms of % during last two years (Max Score 10)
Organisational structure and Succession plan 5 5 4 3 2 0
Market Reputation and Past Track Record 5 5 4 3 2 0
2. Management of Inventory and Receivables In Relation to Net Sales in Months
(Max Score 5)
The above measure is months and indicates as to how efficiently the inventory and
receivables are being managed. Lower the period more efficient is the management.
Ratio Value Max Score < 3mths 3 to<4 mths 4 to<5 mths 5 to<6 mths 6 mths &aboveScore 5 5 4 3 2 0
3. Realisability of Receivables and valuation of Inventory. (Max Score 5)
Realisability of Receivables and valuation of Inventory
Max Score
Comments given by Bank’s Inspector/ Stock Auditors are satisfactory
Comments given raised some doubts but no shortfall in value is indicated
Comments given indicate some shortfall in value say maximum upto 5%
Comments given are adverse which are indicative of poor quality of receivables/inventory
Score 5 5 4 2 0
4. Transparency in Accounting Statements (Max Score 5)
Transparency in Accounting Statements (related to disclosure by management and qualifications by auditors)
Max Score
Standard accounting practices are being followed which are consistent. Management has made disclosures and there re no qualifications from the auditors.
Standard accounting practices are being followed which are consistent. Management has made disclosures and auditors have given qualifications which are not damaging.
Accounts lack transparency as disclosures are not adequate. Auditors have given qualifications which re damaging and may erode company’s net worth.
Score 5 5 3 0
Average Inventory + Receivables
Net Sales per Month
Summary of Various Parameters
A. Operational / Financial Performance
1. Plant Capacity Utilization2. Current Ratio3. ROCE4. DER5. DSCR6. Achievement of Net Sales Projection7. Achievement of Net Profit Projections8. Future Cash Flows
Max Score 80
1010101010101010
B. Conduct of Bank Accounting & Availability of Securities
1. Accounts running regular / irregular2. Compliance in terms/conditions of sanction3. Discipline in timely/submission of data/information4. Primary & collateral Securities5. Operations in non-fund based loan limits6. Diversion of funds
Max Score 45
100505100510
C. Industry /Business Outlook
1. Expected Growth Rate2. Threat of Competition from existing and new entrants
and substitutes3. Technology Development and threat of obsolesce4. General Outlook/Capital Market Perception
2. Management of Inventory & Receivable in relation to its Sales
3. Realisability of Receivables & Valuation of inventory 4. Transparency in accounting Statements
Max score 35
2005
0505
Grand Total (A+B+C+D) 200
The borrowers are to be rated on the basis of score received out of 100 and therefore the
score received to be reduced to 50% as the total score of all the parameter under
A+B+C+D works out to be 200.
Risk Categorisation of Borrowers
Score Rating /Grade Risk Categorisation
90 or more AAA Particularly no risk80-89% AA Minimal Risk70-79% A+ Modest Risk60-69% A Marginal Risk50-59% B+ Medium Risk (Generally Border line/likely NPAs)40-49% B High Risk (Generally sub-standard & doubtful category
of NPAs) 30-39% C Very High Risk (Generally doubtful category of NPAs)
Below 30% D Caution (Generally loss category of NPAs)
CHAPTER VI CREDIT RISK MODELS - OTHERS
SUGGESTED CREDIT RISK SCORING & RATING MODELS
Keeping in view the parameters used by some banks in their credit risk scoring and rating
systems in line with RBI broad guidelines and those used by eminent persons in their
models, an attempt has been made to evolve a simple but effective model by using
parameters which have significantly “Predictive Power”, are more objective/sensitive in
nature and are related to the following four main heads.
VI-A ALTMAN’S Z- SCORING MODELS
The Multiple Discriminate Analysis – MDA Model or Z Score Model uses some
financial ratios having significant discriminating power to differentiate weak and
healthy units. Where:
Z = B1X1 + B2X2 + B3X3 + - - - - - - - BnXn
The value of z is arrived at by adding the total value of various discriminate
coefficient and independent variables. In the formula given above X, X, X, etc.
represent financial ratios and B1,B2,B3 are the weights attached to them based on
their predictive power. Altman’s sample comprised thirty-three pairs of
manufacturing firms, where industry and size were used as the paring criteria. After
considering various combinations of the twenty-two accounting and non-accounting
variables, Altman suggested the following pattern of discriminate coefficient and
Pillar II aims at improving supervisory review process and stresses supervisory review as a
critical complement to capital requirement and market discipline. It also emphases that
supervisors need to take a comprehensive view on how banks handle their risk
management and internal capital allocation process. As per the new accord the traditional
regulation by the regulator has been outdated and control in the form of direct supervision
is coming to the forefront.
The second pillar emphasizes the need for banks to assess their capital adequacy positions
relative to their overall risks and for supervisors to review the same. The supervisors will
also take appropriate actions after making proper assessments.
This pillar adds strong risk assessment capabilities by banks as well as supervisors. It will
be necessary for the banks to have adequate capital to protect against adverse or uncertain
economic conditions.
There may also be a stress test of the assets held by the bank. The supervisors may require
a bank to reduce risk exposures so that its existing capital resources match its minimum
capital requirement.
Pillar (3) : Market Discipline
This is complementary to Pillar (1) and Pillar (2). The Committee has sought to encourage
market discipline by developing a set of disclosure requirements which
allow the stakeholders, shareholders and other market participants to assess key
information about a bank’s risk profile and level of capital resources to absorb the
unexpected losses.
The third pillar relates to market discipline or public disclosure. The potential of market
discipline to reinforce capital regulation depends on the disclosure of reliable and timely
information with a view to enabling banks’ counter parties to make well-founded risk
assessments. Pillar III complements the other two pillars. The accord seeks to encourage
market discipline by developing a set of disclosure requirements.
The corporate governance has already been implemented and more and more disclosures
are now required in the balance sheet of banks. Further the banks should also have proper
policies and guidelines in place for action and compliance by various functionaries.
This pillar (3) of the new capital accord can generate significant benefits in managing
banks and supervisors to minimize risk and improve stability. Market discipline can
contribute to a safe and sound banking environment.
Other Issues
Capital Requirement Under Basel II Accord
(from Federal Reserve Bulletin-Sept.03)
Implementation of New Accord
Though the proposals of Basel II accord are suitable for a wide range of banks in different
countries but within the G-10, the Committee members have agreed to a common
implementation date for the new accord of year end 2006. In the G-10 countries this
framework will be applied to the entire banking system. For other countries, the
Committee provides that the regulator may first strengthen the supervisory system and
develop a time table and approach for implementation. But many national supervisors have
already begun to plan for the transition to Basel II. A framework will be developed for
assisting Non G- 10 country supervisors and banks in the transition stage to both the
standardized and foundation IRB approaches of the New Accord. However, the frame
work is still under preparation requiring suitable amendments on the basis of most recent
Regulatory capital (Definition unchanged) Minimum required --------------------------- = Capital Required ratio Measure of risk exposure (8% minimum unchanged)(Risk-weighted assets)(Measure revised)
Even though the broad features are mostly similar for each type of exposure, different
methodology is adopted and in each case, two concepts are identified.
EXPECTED LOSS
Rs.
Probability of Default
(PD)%
Loss Severity Given Default
(Severity)%
Loan EquivalentExposure
(Exposure)Rs
What is the probability of the counterparty
defaulting?
If default occurs, how much of this do we
expect to lose?
If default occurs, how much exposure do we
expect to have?
Borrower Risk Facility Risk Related
Risk factors are based on
Long run average probability of default (PD) of borrowers in each rating grade.
Loss given default (LGD).
Exposure at default (EAD)
Maturity (M)
Granularity of portfolio (which is determined by the concentration of a bank’s
exposure to a single borrower or a group of closely related borrowers)
However, the accord imposes on banks to meet the following requirements to the
satisfaction of the supervisory authority.
(a) There is a risk management system in the bank which is conceptually sound and is
implemented with integrity.
(b) The models granted by bank have a proven tack record of reasonable performance
in the eyes of the supervisory authority.
(c) There should be an independent risk control unit which directly reports to the
senior management and board of Directors.
(d) The output of the risk management unit should be an integral component of the
planning process and day-today operations of the bank.
(iii) Advanced IRB approach
In IRB foundation approach, estimates of default risk of obligor are provided by the
bank using internal estimates whereas other risk drivers are applied as per
supervisory norms.
However in case of IRB advanced approach, all the risk drivers except for
granularity would be based on banks internal methodologies.
Issues/Constraints and suggestions under credit risk
The nominal capital benefit accruing from credit risk due to lesser capital
requirement for claims on external rated accounts/retail portfolio/residential
property is to be shifted to unrated claims on banks, lower rated borrowers, past
due loans and high risk exposures and hence the overall capital requirement may
not be reduced much.
Issues and Constraints SuggestionsIn case of corporate claims, different risk weights are applied based on external ratings. External ratings agencies like S & P is using ‘‘ 7 σ’’ approach for assigning highest category rating. In India, due to scarcity of capital, the borrowers having economic capital @ 7 σ basis is very rare.
Supervisory authorities may permit banks to risk weight all corporate claims and advances above Rs.5 crore (above the cut of limit of retail advance) instead of external ratings in view of very limited number of external rated companies in India.
Banks should use solicited ratings from eligibleECAIs. (National supervisory authorities may,however, allow banks to use unsolicited ratings in the same way as solicited ratings)
There may be the potential for ECAIs to use unsolicited ratings to put pressure on entities to obtain solicited ratings though powers are given toSupervisors for de-recognizing such ECAIs.
Exposure to retail portfolio with risk weight at 75%
Granularity criterion may be avoided in view of fixing of maximum aggregated retail exposure to one counterpart of 1 million Euro or Rs.5 cr.
Lending fully secured by mortgages on residential property that is or will be occupied by the borrower, or that is rented, will be risk weighted at 35%.
The criteria shall be extended to all claims secured by mortgages
The unsecured portion of any loan (other than a qualifying residential mortgage loan) that is past due for more than 90 days, net of specific provisions, will be risk-weighted more.
The unsecured portion of any loan (other than any mortgage) that is past due for more than 90 days, net of specific provisions, shall be risk-weighted more
Securitization trenches that are rated between BB+ and BB- will be risk weighted at 350%.It is also noted that higher risk weight will adversely affect the expansion of asset securitization in India. It is also possible that banks may ‘cherry-pick’ their portfolios for securitization. As a consequence, banks may retain the worse assets in their B/S aftersecuritising higher quality assets.
The risk weight of 350% is very high and hence maximum cut off may be fixed as applicable to advances.
Capital relief in respect of CRM techniques. Banks shall give certain Capital relief in case of effective use of CRM techniques since it reduces credit risk or transfers credit risk after cons idering the increase of residual risks.
Issues and Constraints SuggestionsIn case of IRB approach, the entire advances should be rated, which is impracticable in present Indian scenario.
A major chunk of advances (Regulatory Advances like social lending) are difficult to rate by the bank. The regulator has to come out with uniform guidelines.
Capital adequacy ratio of the bank has to be certified by the statutory auditors. While considering the Indian banking scenario and size of the assets, auditors may be finding it difficult /time consuming to assess the rating of individual assets and portfolio of assets. In view of the above, auditors are likely to give disclaimer in their reports.
In IRB approach, retail advances shall be excluded from rating of individual advances and hence 75% RW shall be assigned on portfolio wise.
Recoveries has to be increased to minimize loss given default which in turn will reduce theunexpected losses of portfolio.
Effective legislation/ reduction of time consumption of legal process are required.
The securitization is in the nascent stage. Securitization (both asset backed and mortgaged backed) of assets by banks shall be popularized to reduce banks capital requirements.
It is expected that expected losses to be covered through pricing and unexpected losses through capital allocation. As expected losses are not transforming to proper pricing due to unhealthy competition, economic capital requirement is high.
Suitable monitoring system shall be developed by supervisors to overcome this practice. Also pricing based on rating may be extended to good individual borrowers to minimize the disparity.
CHAPTER IX CREDIT RISK MANAGEMENT – A DEEPER LOOK
Credit Risk Management has been practiced since commencement of banking activity
but the discussion of risk management, the tool used in different risk management areas
and the resources deployed in terms of skills and technology have shown considerable
sophistication in recent years. The tone has been set by increasing competition for loan
business, declining spreads and the heightened risk surrounding industrial and
commercial activity.
As we have already seen the Basel Committee on Banking Supervision set up by the
bank for International Settlements (BIS) has issued some broad principles for
management of credit risk by banks. These are:
o Establishing an appropriate credit risk environment.
o Operating under a sound credit granting process.
o Maintaining an appropriate credit administration, risk measurement and
monitoring process.
o Ensuring adequate controls over credit risks.
o Role of bank supervisors/bank regulatory authorities in ensuring that banks have
an effective system in place to identify measure, monitor and control credit risk.
Credit risk management covers both the decision-making process, before the credit
decision is made, the follow-up of credit facilities, plus all monitoring and reporting
processes. The decision making process covers all the steps associated with a client’s
credit application, from the original account officer’s proposal to all credit officers who
examine the credit application, or to a credit committee which reviews/approves the
proposal. The decision based on various credit evaluation parameters based on
financial data, plus judgmental assessment of the market outlook, of the borrower, of
the management and of the shareholders. The follow-up is done through periodic
reporting reviews of the bank commitments by customer, industry and country. In
addition, “warning systems” are put in pace to signal the deterioration of the situation
of the borrower before default whenever possible. A work-out process, by which all
actions to minimize possible losses are considered and taken care can be trigged if a
default occurs.
Limits Systems and credit Screening
Credit Risk is sought to be limited by strict exposures limits aimed at limiting losses in
the event of a default. Before any credit decision is made, an authorisation has to be
specified. The authorisation states the maximum amount at risk with any customer, or
group of customers. Within the authorisation, credit decisions can be made, provided
that they meet the standards of credit risk acceptance laid down by the bank. The usage
of credit lines should remain below the limit approved. The risk reporting system
should be able to consolidate all the facilities that are made available to a customer in
order to constantly check that the line usage remains within limits.
The basic principles followed while setting up limits are simple to understand as under:
(1) Avoid a situation in which any single loss endangers the bank;
(2) To diversify and broad base the commitments across various dimensions such as
customers, industries and geographical regions;
(3) To avoid lending to any borrower an amount that would increase its debt beyond its
debt servicing capacity.
The equity of the borrower sets up some reasonable limits to its debt given
acceptable levels of its debt/equity ratio. The capital of the bank sets up another limit to
lending given the diversification requirements and/or the credit policy guidelines. The
bank regulatory authorities also often prescribe exposure limits in relation to a bank’s
capital and maximum credit exposure to an individual customer as also credit exposure
in the aggregate.
Ultimately, with a full-blown quantitative risk management systems, the
capital of the bank could be allocated to all credit lines. Such allocation of capital
requires special systems to measure risks at the level of a transaction and at the level of
the bank portfolio, including diversification effects. Risk based capital allocation is a
sophisticated systems, which goes well beyond the recording of amounts at risk. This
allocation can serve the purpose of limiting the consolidated risk according to the
actual available capital. It also makes explicit the capital usage of various credit lines.
Limits can potentially be defined in terms of capital usage. Most practices, however, do
not reach this stage, but the trend is to focus on the capital usage of credit lines because
of regulation and its emphasis on risk based capital.
Is Limits systems widely used?
It is not as relevant as it appears. When the bank is dealing with a limited number of
big customers, it is difficult to set limits. First, lending is based on a continuous
relationship. Setting limits and relationship banking are interacting processes. Second,
big corporations with an excellent credit standing are less subject to limits given the
high quality of their risk. In other words, “relationship banking” and “name lending”
tend to reduce the importance of quantitative limits. However, bank regulators do
prescribe that banks observe a system of lending limits while providing loans.
For individuals, the credit application process can be considerably simplified,
compared to what it is for corporate or financial sector borrowers. There are a large
number of customers so that statistical methods rather than customized risk appraisal
systems become relevant. Authorisations result from the appraisal of the credit standing
of borrowers based upon their observable characteristics such as yearly income,
property, values, and employment characteristics and so on. For individuals the
appraisals of the risk quality can often rely on credit scoring. Scoring so arrived at
estimates the quality of the risk as a function of a limited number of selected
characteristics / parameters.
The limit system centralises the information about the borrowers, in terms of both
authorisations and usage of credit lines. In addition to limiting the amount of risk, the
centralisation is also a basis for monitoring portfolio orientations, such as increasing
the portfolio diversification, or reducing concentration in a particular industry or
industrial group, or any other portfolio parameters.
External Ratings
The best known systems are those of specialized credit rating agencies. For example,
Moody’s uses a simplified rating scale, plus a detailed rating scale. The simplified
scale includes 6 levels. It is briefly described in the following module. Standard &
Poor’s uses similar scales.
Such ratings characterise debt issues rather than issuers. The reason is that some debt
issues, from the same borrower, could be less risky than others. Investors are more
interested in the risk of an issue, given its specific protection, than in the issuer. Ratings
qualify the risk of losses in the event of default, a combination of default probabilities
and recoveries. The ratings signify rankings, not quantitative measures of risk quality.
Common rating systems include from 6 to 10 different ranks, which are sufficient to
discriminate among risk classes.
For the internal use of banks, there are other options to be considered. First, ratings
could qualify the credit standing of the borrower, instead of combining it with recovery
risk.
Ratings attached to facilities are useful whenever guarantees are attached to individual
facilities. For transactions structured with guarantees and collaterals the quality of the
protection becomes more important than the credit standing of the borrower. Whether it
is necessary to have a dedicated rating system for facilities or not is a management
decision. However, to have a fine pricing system for different facilities to meet the
demands of competition, a bank would feel the need for a dedicated rating system to
ensure that its pricing system is risk-based.
A rating system can also serve as a tool for credit policy. For instance, some minimum
rating might be required to make a loan, or to delegate authority to credit officers. They
can be allowed or not allowed to enter transactions based on the borrower rating.
A rating system requires robustness to be accepted as a reliable tool. For corporate
borrowers, the criteria for assessing risk are well known: profitability, growth, industry
outlook, competitive advantages, management and shareholders, in addition to the
standard set of financial and operational performance rations. Ratings are required
while lending to financial institutions as well. However, the rating criteria differ
significantly from those applicable to corporate borrowers. Since the financial industry
is highly regulated, the policy of the regulating bodies, which can vary greatly between
countries, is an important factor for those institutions that operate internationally. In
addition, the rating system for individual borrowers is obviously different from that
applicable to corporate borrowers as mentioned earlier.
Internal Ratings
Internal rating systems exist in many institutions. As per the system borrowers are
ranked according to their credit quality. Sometimes, facilities are also rated, in order to
capture the quality for protection against the default of the borrower that is embedded
with the facility. Such protection can be obtained through the status of privileged debt
or collateral, guarantees or any other contractual agreement.
Rating System: Design
Finally, the design of the rating system changes across institutions. While a few will
prefer a fairly detailed rating system, with explicit rules for appraising criteria and
weighting them, others may focus more on the judgmental appraisal of risk quality,
with guidelines specifying the criteria to be appraised before making a judgment.
Credit Enhancement
Guarantees and loan covenants are the main vehicles of credit enhancement. Credit
enhancements are sought when a bank does not feel comfortable about the decision on
the basis of a borrower’s rating alone. An enhancement helps a bank not only to take
the credit decision but also to price the facility more competitively. The borrower may
not object to the credit enhancement particularly if it helps him in obtaining a lower
price from the bank. They aim at reducing the amount of loss in the event of default
because they increase the recoveries. The covenants trigger preemptive actions
whenever the credit standing deteriorates. Collaterals and third party guarantees serve
as an insurance, whose value is uncertain, in the event of default. Covenants are
virtually sort of an aid to active monitoring of risks.
Covenants
Covenants create additional obligations for the borrower. For instance, if the borrower
breaks the covenants, the lender can be entitled to a prompt repayment of its debt. This
is a powerful incentive to comply with the covenants. In practice, some waivers can be
accepted. The actual goal of covenants is to initiate negotiations with the borrower
before default, not to trigger default as such. There are financial covenants based on the
usual financial ratios. For instance, the debt / equity ratio can be specified to remain
below a stated limit; if the actual ratio exceeds the limit the lender would be entitled to
call off the credit facility. Legal covenants restrict the initiatives of the borrowers.
Typically, they seek to reduce diversification beyond the borrower’s core business or
restrict the uses of the funds of the borrower so that he repays the bank debt first,
before anything else. But there are alternatives to design the set of covenants according
to the specifics of a borrower or a transaction.
Structured Transactions
Credit enhancing devices can be sophisticated such as those in case of structured
transactions. The structure of the transaction aims at isolating the risk of the transaction
from that of the borrowing entity. Guarantees and covenants are the basic ingredients
of a transaction structure. The level of protection can also be improved with other
specific features. For instance, reserve accounts can be set up and / or built up
progressively with time whenever some target indicator hits a trigger value. The build-
up of cash balances or of collateral, serves as a first-level protection for the lender that
has privileged access to them.
Securitisation
A good example of a structured transaction is securitisation. Whenever some assets are
securitised, they serve as collateral for debt issues sold to investors. The risk of those
debt issues has to be limited and rated, so that investors know what they buy.
Typically, the flows generated by the collateral assets will be routed again to the low
risk investors as a priority. The structure isolates investors from the original credit risk
of the assets being securitised.
Credit enhancing vehicles are numerous and are being increasingly used. They range
from stand by letters of credit, complex structures for Leveraged Buy Outs (LBO),
project finance, assets acquisition or securitisation. The credit enhancement is obtained
by the separation, partial or almost total, of the risk of the transaction from the risk of
the borrower.
Credit enhancing vehicles achieve this purpose through risk transformation as well as
risk reduction. The collateral changes the credit risk into a recovery risk plus an asset
value risk. Third-party guarantees transform the default risk of the debtor into a smaller
joint default risk. Covenants, or other devices mitigating credit risk, are useful triggers
for active risk monitoring whenever the credit standing of the borrower deteriorates.
Credit Risk in banking transactions & measuring credit risk in it
From a quantitative standpoint, credit risk is measured by the loss in the event of a
default. Credit risk results from a combination of default risk, exposure risk and
recovery risk.
The resulting loss L is random and can be seen as the product of a random variable
characterising default D ( a percentage), an uncertain exposure X (a value) and an
uncertain recovery rate R ( a percentage):
Loss = D x X x (1-R)
Let us summaries the issue of measuring risk. Although a symbolic formulation, it
shows that the upstream random factors that influence exposures and recoveries have to
be investigated. It also suggests that the measure should, ideally cover all 3
components.
Let us introduce common measures of the components of credit risk from default risk
to exposure risk and recovery risk.
Internal Ratings
External Ratings
Default Statistics
From Internal Ratings to External Ratings and Default Statistics
1. Default Risk
An adequate quantitative measure of default risk is the probability of default. The
available measures are either ratings or historical statistics on defaults, which can be
used as proxies for default risk. Another method to quantify default risk is to derive an
estimate of default probability based on a borrowing entity’s characteristics.
The Historical Frequencies of Defaults
There is significant correlation between ratings and default frequencies. Such data are
published yearly by rating agencies for various periods for different rating classes.
It is important to note that most bank clients particularly in developing countries are
not rated by agencies, but are rated internally. If a correspondence can be established
between the internal rating scale and the rating scales of agencies, it provides a link
between internal ratings and historical default frequencies. In a way the methodology is
simple to implement, although the correspondence between internal rating scales can
be approximated and not exact.
Agency ratings and default frequencies
The data available from rating agencies provide relevant information from a statistical
standpoint. They include, for each rating class:
o the frequencies of defaults, yearly or for longer periods of time
o the volatility across time of yearly frequencies, which results from changes in
general economic conditions
o the transition matrices between ratings classes. These give the percentages of issues
in which ratings X changed into rating Y during a certain period. Such percentages
are available for all couples of ratings classes X and Y.
The default rates are close to zero for the best risk qualities. They increase to around
8% a year for the lowest rating class. It can be the magnitude of yearly default rates for
the 6 rating classes in Moody’s simplified rating scale. Actual values vary every year.
The top 3 ratings characterise “investment grade” borrowers. The other 3 classes are
called “speculative grade” because of their much higher associated risk. For investment
grade borrowers, the default rate ranges from 0.02% to 0.08% a year.
The relationship between ratings and default rates is far from proportional. The
increase in the default rate when ratings decline has an exponential shape. The increase
in default rate from one class to the next changes drastically when going down the
rating scale. In order to improve the rating by one grade, the required variation of
default rate will be 6.5% for the last 2 classes of the scale, but a small decrease of
0.02% suffices to improve the grade from Aa to Aaa.
Moody’s Ratings Yearly Default Rates
Aaa 0.02%Aa 0.04%A 0.08%
Baa 0.20%Ba 1.80%B 8.30%
This observed law has important implications. The ratings drive the cost of lending by
banks. Improving the ratings class it can be done theoretically by improving the overall
solvency of the borrower. But the required improvement of solvency to gain one rating
class, measured in terms of default rate, is much higher in the lower grades of the scale
than in the upper grades.
4%
3%
2%
1%
0%Mean
%
Years
Def
ault
Rat
es Time Series of Default Rates
Volatility
Graph Default Rates : Time Series
Are Default rates volatile?
Default rates become unstable with the passing of time. The volatility of yearly
historical default rates is the standard deviation of observed values. The volatility
increases with the level of default rate, that is, when the rating diminishes. This is
consistent with the fact that low default rates are closer to the zero value floor which
limits their variations. Such volatilities are available from time series of default rates
observed across varying horizons.
If the volatility is high, the potential deviations of the default rate around the average
can be significant. If the volatility is low, deviations are small. The unexpected loss
will be higher in the first case. The default rate volatility is a simple base for measuring
the unexpected loss for loan portfolios. The unexpected loss is proportional to this
standard deviation. The expected loss is proportional to the average default rate.
Default Rates and Horizon
The cumulated default rates increase with the horizon. The longer the period the higher
the chances of observing a default. The growth of cumulated default rates with horizon
is not proportional. For high ratings, or low default rates, the increase is more than
proportional. For low ratings and high default rates, it is less than proportional. High-
risk borrowers improve their risk, when they survive for a longer time. Low risk
borrowers face risk deterioration when time passes. All these observable facts are
important in differentiating the risks across time and in valuing both expected and
unexpected losses.
Years Years
Cum
ulat
ed D
efau
lt R
ate
Vola
tility
of
Def
ault
Rat
e
Low Rating
High Rating
As time passes, the risk tends to change. It either improves or deteriorates. These shifts
are captured by the transition frequencies between risk classes. Such frequencies can be
tabulated for each pair of ratings. Within a given period, the transition frequencies can
be recorded as a transition rate (%) between classes. Transitions occur mostly in the
neighbouring classes of ratings and there is a concentration of high frequencies along
the first diagonal of the matrix. In this example, the probability of transition from class
A to B is 2% while the probability of an unchanged rating of A is 95%.
Figure 1 Time Profiles and Volatility of Default Rates
2. Exposure Risk
Exposure is the amount at risk in the event of default without considering recoveries.
Since the default occurs at an unknown future date, the amounts at risk that count are
future amounts at risk. When they are known, they must be derived from the time
profile of exposure. When they are unknown, they have to be estimated, based on
assumptions, conventions or modelling of future exposures. The type of commitment
given by the bank to the borrower is important since it sets up the upper limits of
possible future exposures.
Inter-bank exposure and country risk
A suitable framework has to be evolved to provide a centralized overview on the
aggregate exposure on other banks. Bank-wise exposure limits could be set on the basis
of assessment of financial performance, operating efficiency, management quality, past
experience supervision and control mechanism etc. Like corporate clients, banks
should also be rated and placed in a range on the basis of their credit quality. The limits
so arrived at have to be allocated to various operating centers and followed up at
regular / periodic intervals. Regarding exposure on overseas banks, banks can use the
country ratings accorded by international rating agencies and classify the countries into
low risks, moderate risk and high risk. Banks should endeavor for developing an
internal matrix that reckons the counterparty and country risks. The maximum
exposure should be subjected to adherence of country and bank exposure limits already
in place. The exposure should be monitored at least on a weekly basis till the time
banks are equipped to monitor on daily / online basis.
Credit Risk and the Balance Sheet
A time profile of exposures is defined when there is a contractual repayment schedule.
In all other cases, assumptions or projections are required to be made to estimate future
exposures. An important area for future estimates covers committed lines of credit, of
which usage is not yet 100%. Only the current usage is known, plus the level of the
authorization and the time remaining before its maturity or review date. These lines,
which are not fully used, are treated as given contingencies and recorded off-balance
sheet. For proper risk measurement, it is necessary that such contingencies are captured
in the bank’s MIS.
Not all lines are fully committed. In some cases, there is no commitment, except that
the bank is willing to increase usage up to certain limits if the borrower wants to. The
bank might have informed the customer that he could increase his borrowing. Since the
bank is not legally committed to do so, the unused fraction of the credit line does not
have to be recorded off balance sheet. The situation is similar when authorizations are
purely internal; the client has no idea of the amount that the bank is willing to lend, and
the bank commitment does not go beyond the current line usage.
The current exposure is the current line usage. There is exposure uncertainty as long as
the bank is ready to go beyond the current usage. Future exposure will certainly differ
from the current usage, because of newly opened lines of credit. In such cases, the
expected exposure becomes more relevant than the current usage. Often, only current
exposures are recorded and reported. But expected exposures might be more relevant to
assess future risks.
Product Lines
Balance Sheet Off-Balance Sheet
Projections & Assumptions
Further expected Exposures
Exposures RiskCurrent Exposure
Contingencies
From a risk stand point, off-balance sheet transactions raise specific issues. The risks
appear only conditional depending upon the initiative of a counter party or a third
party. For instance, with a confirmed line of credit, the customer can decide at any time
to draw that line up to the authorized amount. In such case, the given contingency turns
into a credit line, which then appears in the balance sheet. Given contingencies are
options, which can be exercised by the customers or a third party at a future date.
Received contingencies are options, which can be exercised at the initiative of the
bank. Risks generated off-balance sheet are conditional risks, not certain risks.
Off-balance sheet risks appear in the balance sheet only when the options are exercised.
It should be understood that the risk in such cases is potential rather than current.
In regard to given contingencies, it can be argued that since the bank has to comply
with the exercise of the option, 100% of the amount committed is at risk, even though
it is not yet drawn. A potential risk could also be valued at less than 100%. The reason
is that while some contingencies given such as committed lines of credit are very likely
to be used. Others are very unlikely to be drawn, such as guarantee given to a third
party in the event of default of the customer. The approach adopted by bank regulators
is to use a 50% weight to value the potential risk generated by off-balance sheet
transactions due to the limited probability of cost outlays. From the above
consideration, there is a case for differentiating exposures depending upon the nature of
contingencies.
Expected Exposures – The Time Profile
The measure of credit risk exposure depends upon the type of credit lines current,
projected exposure or the level of authorization that can be used.
The time profile of exposures varies widely with the type of transactions. We illustrate
some possible shapes based upon credit authorization profiles, either for amortizing
loan or for committed lines of which usage is uncertain as under:
Time profiles of credit exposure can be expressed as under:
Expo
sure
Expo
sure
Time Time
Bullet Loan, orCommodity Line of Credit Amortising Loan
3. Recovery Risk
Guarantees and covenants diminish risk because they reduce the loss in the event of
default. The loss in the event of default is the amount at risk at default time less
recoveries. Normally, recoveries require legal procedures, expenses and a significant
lapse of time. Loss in the event of default can be estimated before or after the costs of
waiting and workout costs. From a measurement standpoint, the valuation of such
guarantees is an Herculean task, if it is feasible at all. There are many uncertainties
involved. Some historical recovery rates vary widely around the average. Going
beyond some forfeit valuation is not an easy task given the uncertainty in recoveries
from guarantees. The following is a list of some credit risk enhancing effects of
guarantees along with some remarks relevant from a valuation standpoint.
All guarantees are subject to legal risk, i.e. the risk that the guarantees may not be
enforced if they happen to be used. Legal risk depends upon the type of guarantees.
Some guarantees are more enforceable than others. Letters of intent or letters of
comfort have less force than legal commitments without recourse. The legal risk also
depends upon the current environment at the time of default and after. Whenever legal
procedures are activated, the protection of guarantees becomes subject to the outcome
of such procedures. Beyond legal risk, guarantees transform and reduce risks.
Collateral can be seized and sold by the lender, thereby reducing or even canceling the
loss. The original credit risk turns into a recovery risk plus an asset value risk.
Recovery risk depends upon the nature of assets, their location, their integrity and the
legal environment. The risk on the liquidation value also varies according to the nature
of collateralized assets. It is zero with cash. The mark-to-market value of securities
held as collateral has a volatility that can be derived from market volatility combined
with the sensitivity of the securities. The methodology developed for market risk also
applies for any capital market collateral. The risk on the liquidation value of other
types of collateral, such as real estate, aeroplanes, ships and fixed equipment, is less
easy to capture. In some cases, existing data are relevant. The value of aeroplanes, for
example, can be tabulated according to their age and their remaining life. But in this
and other cases, the expected value of such collaterals remains subject to judgment
based on the characteristics of the assets.
Third party Guarantees
Third party guarantees have a two-fold risk. First, there is the legal risk of not being
able to enforce the guarantee, which depends upon the nature of the guarantee.
Secondly, default risk is enhanced because third-party guarantees transfer the credit
risk form the borrower to the guarantor at the time of default. The effect on risk is that
the default probability of the borrower is changed into a joint probability of default of
both borrower and guarantor. Usually, a joint probability of default is much lower than
a single probability. For instance, when the defaults of the borrower and the guarantor
are actually independent, the joint probability of default is the product of the
probabilities of default of each one. If the borrower and the guarantor have a 1% & a
0.5% default probability, their joint default probability becomes 0.5% X 1% = 0.005%
which is quite close to zero.
In general, the joint probability depends upon the interdependence of defaults of the
borrower and the guarantor. For example, if the guarantor is the holding company and
the borrower a subsidiary, the defaults are probably not independent. They can be
totally linked if the borrower cannot default unless the holding company defaults and
vice versa. In such case, the default probability is the same for the borrower and the
guarantor and the joint default probability of both becomes equal to that common
value.
Covenants allow for preventive action on the happening of certain events preceding a
default. On the other hand, guarantees can be considered as insurance policies that are
activated only when default occurs. They are consistent with a more passive risk
management. Covenants enhance the effect of proactive credit risk management. Their
Collateral
Covenants
Transform Credit Risk into Asset Risk
Risk Transform from Borrower to the
“Guarantor + Borrower”
Third Party Guarantee
Allow Corrective Actions
actual values depend upon how active the credit risk monitoring and management
processes are. There is no simple methodology capable of quantifying such intangible
assets as covenants.
How the risk changes as a result of impact of guarantees can be followed as under:
Guarantees and Loss in the Event of Default
The loss in the event of default is the amount at risk less the recoveries. It is increased
by any workout costs such as the carrying cost of collateral or the expenses involved in
these recovery efforts.
Credit Risk and the Potential Losses
As mentioned earlier, Loss Given Default or LGD depends upon the values assigned to
the three basic parameters: default probability, exposure and recoveries.
Expected Loss
The expected loss is the product of the loss given default and the default probability.
The LGD is the amount at risk or exposure, less recoveries.
LGD = exposure – recovery
= exposure x (1 – recovery rate%)
How exposure transforms & leads to Loss Given Default can be understood from the
following diagram:
Guarantees, Collaterals, Covenants
Recoveries
Loss in the event ofDefault
Workout Expenses
Exposures
The expected loss synthesizes both the Loss Given Default and the quality of risk:
Expected Loss = LGD x default probability
= exposure x (1 – recovery rate%) x default probability (%)
Thus, we can say that the expected loss captures in a single measure the three
components of credit risk: exposure, default probability and recovery.
Unexpected Losses and Risk-based Capital
The expected loss is a statistical loss that will occur on an average or a certain tendency
for the uncertain losses. The unexpected loss captures the deviation from such an
average. It can be inferred, for instance, from the variations of the default rate that is
from its volatility.
With a portfolio of 100 borrowers and unit outstanding balances of 10, it is almost
unlikely that a bank will lose the total outstanding balance of 1000 unless all borrowers
default at the same time. If we assume an average default rate of 1% and a recovery of
0, the expected loss is 1% x 1000 = 10. It can be understood as the loss of 10, the unit
exposure, for an average value of the number of defaults equal to 1.
However, there could probably be serious changes that the number of defaults
increases to 2 or 3, or even higher. The dispersion around the average of observed
default rates is measured by the historical volatility of observed default rates. The
volatility can be derived from available statistics. If we assume the default rate
volatility is 3%, the loss volatility is simply 3% x 1000 = 30.
Unexpected losses can be derived as a multiple of this volatility, the multiple
corresponding to some tolerance level. Statistics of default can therefore be applied
directly and in a simple manner to determine expected and unexpected losses. This can
be developed in greater detail providing loss calculations given the risk specifics of
portfolios of loans. The losses thus estimated can then be compared with risk tolerance
levels specified by the bank’s board / management based on risk appetite of the
organization and appropriate actions initiated.
It will be observed that the estimate of unexpected losses has been derived from the
deviations of default rates alone. Actually, the deviations of losses from their average
depend also upon the deviations of the recovery rates and the exposures from their
expected values. Unfortunately, such deviations are more difficult to quantify than
those of default rates. Often they are not made explicit, which makes the unexpected
loss estimate rather inaccurate.
In addition the definition of unexpected loss when all the three factors are uncertain
raises some conceptual issues. For a very conservative approach, one can ask what is
he worst-case value loss. We could use the combination of all three worst-case
parameters. The equation would be as follows:
WC (Loss) = WC (Exposure) x [1 – WC (recovery rate)] x WC (default rate)
Where WC denotes “worst case” in practical situations. However, such calculation is
based on the assumption that all worst case values occur simultaneously, which sounds
unrealistic and over-conservative. This illustrates one of the difficulties in estimating
unexpected risks. They depend upon the correlations between the underlying
parameters which themselves have uncertainties.
Default probabilities over different horizons
Yearly probabilities can be changed into probabilities for longer periods with the help
of statistics available for various horizons. The probabilities of default over various
time periods can be used to assess the credit risk of a loan up to maturity. This allows
one to change the measure of credit risk with the horizon of the exposure and to capture
the effect of the time profile of exposures. In general, the default probability changes
over time because the risk itself changes over time.
Such changes are recorded as transitions across ratings. In a first phase, it is easier to
define the effect of time when the yearly default probability is assumed constant (1%).
Then the increase in credit risk with the horizon is due to the fact that the constant
probability of default is applied to a longer time period.
In each period, there are only two possibilities: default or non-default. When periods
are chained, the number of possible situations increases, since the borrower can default
in any one of the periods considered. In the example given as under we have
endeavored to show three periods. If the company defaulted between date 0 and date 3,
it has to be in any of the first three periods. At the end of the three periods, only four
cases are possible: either the borrower did not default or he defaulted in any one of the
three periods.
0
These four events have different probabilities which can all be derived from the
constant yearly probability. The probability of no default is the product of the
probability of not defaulting in each of the periods, which is 99% for each period. The
probability of defaulting in period 3 is the probability of not defaulting before, times
the probability of defaulting at 3. The probability of defaulting in period 2 is the
probability of defaulting at 2 without having defaulted in 1. Finally, the probability of
defaulting in period 1 is 1%.
Hence the probability of default between date 0 and date 3 is the probability that
default occurs in either period 1, 2 or 3. It is the sum of these individual probabilities of
default:
0.01 + 0.01 x 0.99 + 0.01 x 0.99 x 0.99 = 0.01 x [1+0.99+(0.99x0.99)] = 0.0297
Dates
0 20
31Probability
Default (D)
0.01
0.990.99
D
ND
0.99 0.01
D
ND
0.99
0.01
0.99 x 0.01
0.99 x 0.99 x 0.01
0.99 x 0.99 x 0.99
The surviving probability after date 3 is 1 minus the default probability before date 3 or
0.9703. This is equal to the probability of no defaults, i.e. 0.99 x 0.99 x 0.99. It can be
envisaged that the default probability over n periods is less than the yearly
probabilities. For instance, 2.97% is less than three times the yearly probability of 1%.
This is because the default at period t is conditional upon no default before, an event
that has a probability always lower than 1.
The default probability between 0 and n, nPd, is approximately equal to the product of
yearly default probabilities 1Pd by the number of periods, as long as yearly default
probabilities are very low:
nPd = n x 1Pd
It can be checked above that 2.97% is very close to 3%. The 3% value assumes that the
defaults in each year are independent events. This is not true because the default at t is
actually dependent on non-default before.
Default Risk – Term Structure
Let us define the use of default rates across time horizons. Defaults observed over the
period are the basis of default rate calculations.
The number of yearly defaults can be related to the original population of issuers at the
very beginning of the multiple year observation period. The yearly defaults are
cumulated over years and then divided by the original number of issuers. These
percentages are “cumulated” default rates over various time horizons.
Future yearly default rates or “forward rates” can be calculated in numerous ways. The
ratio of the number of yearly defaults to the original sample is a first version of a
“forward” rate. For instance, there are three new defaults in year 2, which is 3% of the
original 100 population. This figure is also obtained as the difference between two
cumulated default rates of years 2 and 1 or 8% - 5% = 3%.
A second version is to relate the same number of defaults i.e. three defaults to be
surviving population only at the beginning of the current period. The surviving
population at the beginning of the year 2 is 100 – 5 = 95, or the original sample minus
the five defaults of the first year. The new yearly default rate for year 2 is 3 / 95 =
3.16%. It is also called a “marginal” default rate. It measures a forward default
frequency conditional upon no prior default.
Periods Year 1 Year 2 Year 3Number of Defaults 5 3 2
Cumulated number of Defaults 5 8 10
Cumulated Default Rates 5% 8% 10%
The aforesaid forward rates, calculated on an historical basis, have to be carefully
selected depending upon the objective of the analysis.
Default Rates – Transition Matrices
The transition probabilities between risk classes allow for the calculation of the
expected default rate of each period, given the transition and the variability of default
rates over time.
Yearly default probabilities are also mentioned. The default probability is 0.01% for
the borrower of risk class A and 0.02% for the borrower of risk class B. The
probability of defaulting before date 3 i.e. the end of the period 2 is the default
probability over year 1 plus the default probability over year 2. The yearly probability
is 0.01%. In year 2, either it stays at 0.01% if the risk class does not change or it
increases to 0.02% if the risk class becomes B. The default probability in year 2 is
derived from the probabilities of these two events, which are given in the transition
matrix:
0.95 x (0.01 + 0.01) + 0.05 x (0.01 + 0.02) = 0.0205
More often, transition matrices allow one to determine the expected frequency
distribution of migration to various ratings in the future. For instance, an issuer in the A
class can stay in A with a 95% frequency, move to B with a 4% frequency and default
with a 1% frequency. In general, migration matrices cover all defined classes over
various horizons. The distribution, starting from any given risk class, virtually looks
like a tree. The distribution widens when the time horizon becomes longer and when
the number of distinct classes grows.
Transition matrices are a simple method to project the changing structure by risk class
of a portfolio or to project the changing credit quality over time of a single issuer.
Various examples of potential applications are given in Credit Metrics, Technical
documents by J.P.Morgan & Co.Inc. (1997). As an example, the distribution of the
potential values of a bond in future can be inferred from these migration tables. The
future distribution of ratings is translated into a distribution of future possible market
spreads associated with the ratings. Once it is included in the discount rate applied to
future flows, they generate a distribution of future market values, each one associated
with a percentage frequency. The usual statistics with reference to mean and volatility
can be derived from such distributions.
Risk Classes
Dates
A
20
31
0.95
0.05B
C
0.01
0.99
Default Probability
Transition Frequency and Default Rates
Risk Class
B
Risk Class A
Risk Class B
Risk Class C
Risk Class D
_--------------
Default
1%
91%
5%
1%
0%
2%
Total 100%
Risk Class Frequency
Migration Tree
CHAPTER X N ON PERFORMING ASSETS
In simple terms, a non-performing advance can be defined as an advance where
payment of interest and /or installment of principal (in case of term loans) remain
unpaid in turn making the account irregular (out of order) for period prescribed by the
RBI.
A non-performing asset in the banking sector also is termed as an asset not contributing
to the income of the Bank. In other words it is the zero yielding assets that are
considered. The non-performing assets, interalia, includes surplus cash and bankers
balances hold over the optimal levels, amounts lying in the suspense account,
investments in shares or debentures and other securities not yielding any dividend or
interest, advances where interest is not forthcoming and even the principal amount is
difficult to recover.
After an account is classified as NPA, bank cannot book Interest charged in the
account as its income till the account remains in the NPA category. Besides, the bank
has also to make substantial loan loss provisions on such accounts as per norms laid
down by RBI.
Hence, NPAs act as a drag on bank’s profitability, a fact which is well understood by
banks who are now taking all possible steps to bring down their NPA portfolio.
It may be mentioned that banks with their best efforts have made some progress to
bring down their existing NPAs but due to heavy slippage of standard accounts to NPA
category, the overall position continues to deteriorate. Further, analysis of data relating
to NPAs may also reveal that major portion of the reduction has been either due to
comprise settlements / write off of the NPAs or on account of insurance claims
received from DICGC / ECGC. As regards reduction in NPAs due to up gradation, the
same has been quite negligible. Thus, there is a need for effective system of monitoring
of existing NPAs and of borderline NPAs, which are likely to slip to NPA category for
checking their slippage by initiating expeditious corrective actions.
The high level of NPAs in banks and financial institutions has been a matter of grave
concern to the public as bank credit is the catalyst to the economic growth of the
country and any bottleneck in the smooth flow of credit, one cause for which is the
mounting NPAs, is bound to create adverse repercussions in the economy. NPAs are
not therefore the concern of only lenders.
NPAs have a deleterious effect on the return on assets in several ways –
o They erode current profits through provisioning requirements
o They result in reduced interest income
o They require higher provisioning requirements affecting profits and
accretion to capital funds and capacity to increase good quality risk assets in future,
and
They limit recycling of funds, set in asset-liability mismatches, etc.
RBI Definition of NPA
In the year 1992, as a follow-up of Narsimhan committee recommendations, the RBI
introduced the concept of non -performing assets, based on Income Recognition
criterion, and directed banks to classify their advances into the following four
categories of assets:
Standard,
Substandard,
Doubtful, and
Loss.
Categories Of NPAs
Substandard Assets
A sub standard asset is one, which has remained NPA for a period less than or equal to 12
months, from March 31, 2005. (Earlier 18 months). In such cases, the current net worth of
the borrower / gaunter or the current market value of security charged is not enough to
ensure recovery of the dues to the banks in full. In other words, such an asset will have
well defined credit weakness that jeopardize the liquidation of the debt and are
characterised by the distinct possibility that the banks will sustain some loss, if deficiency
are not correct.
Doubtful Assets
A doubtful assets is one which, which has remained NPA for a period exceeding twelve
months. A loan classified as doubtful has all the weakness inherent in assets that were
classified sub-standard, with the added characteristic that the weakness make collection or
liquidation in full – on the basis of currently known facts, conditions and values-highly
questionable and improbable.
Loss assets
A loss asset is one where loss has been identified by the bank or interest or external
auditors or the RBI inspection but the amount has not been written off wholly. In other
words, such an asset is considered uncollectible and of such little vale that its continuance
as a bankable assets not warranted although there may be some salvage or recovery value.
Causes Of Loan Accounts Slipping To NPA Category
Before we discuss the monitoring system for NPAs, we must understand the possible
causes of accounts slipping to this category. The causes can be grouped under the
following three main heads – borrowers related, bank related and of general nature:
1. Borrower Related –
Lack of proper project planning and inefficient key management personnels.
Diversion of working capital funds by promoters for expansion, modernization,
taking up new projects, investing in associate concerns, etc.
Differences and disputes amongst promoters resulting in unauthorized withdrawals
of funds from the bank accounts.
Problems faced by importers and exporters due to devaluation of rupee and
fluctuations of various currencies in international market.
Delay on the part of the borrowers to bring the margin money (their own
contributions) to finance the project and compliance of the terms and conditions of
sanction resulting in delayed disbursement of loans by banks.
Low priority given by the promoters in upgradation of the technology and
inadequate attention to research and development (R&D) function.
Lack of effective monitoring at project implementation stage resulting in time and
cost over-runs.
Strained labor relations resulting in strikes and lockouts.
2. Bank Related –
Lack of proper pre-sanction appraisal of the loan proposals.
Sanction of the loan facilities based on optimistic and / or on pessimistic sales /
profitability projections resulting in over / under financing of projects.
Lack of effective post-sanction monitoring and follow-up of the borrower accounts,
resulting in delayed detection of problems and corrective actions.
Delay in release of term loans particularly by financial institutions resulting in
diversion of working capital funds causing liquidity problems and irregularity in
bank’s accounts.
Directed lending by banks to priority sector, more particularly to small
entrepreneurs who lack experience, expertise and financial standing.
Slow decision making process particularly with regard to sanction and
disbursement of loans for revival of potentially viable sick units.
3. General Causes
Time consuming and slow legal process for recovery of bank dues and absence of
punitive measures for borrowers who are willful defaulters.
Non or delayed implementation of new as well as expansion of the existing
projects due to failure of public issues on account of depressed capital market.
Closure of some units due to insurgency in some states, labor unrest / strikes /
lockouts, etc. as also due to natural calamities.
Slow functioning of judiciary including Debt Recovery Tribunals (DRTs), Board
of Industrial and Financial Reconstruction (BIFR), etc. Difficulties even in
execution of the decrees awarded by the courts.
Inadequate infrastructural facilities, particularly the supply of power and essential
inputs.
Lack of support by Central / State Government and delayed release of allocated
funds to various projects resulting in cost and time over-run.
Liberalization in the economy and coming up of the multinational companies in
The country with better technologies, giving tough time to local industries.
The causes listed above are illustrative in nature and there could be many more
depending upon type of industry, location of unit, etc.
Monitoring Of Existing NPAs
With a view to tackle NPAs, banks shall have to develop an effective monitoring
system which may help them in creating data base for understanding total NPA
portfolio as well as individual NPA accounts particularly those at borderline for
formulating general policy and accounts specific action plan. We are aware that the
reduction in NPAs can also be affected by write-off of the accounts where either
securities are not available or the securities available are not easily realizable and even
if these are sold the recovery may not be sufficient even to cover the cost of pursuing
recovery of the dues.
We may also come across NPAs where borrowers are serious and taking all possible
steps even inducting own funds to run their units and willing to regularize the accounts
through tagging of the sale proceeds. There may also be units which are NPAs but
potentially viable and which may turnaround not just with the funds inducted by the
promoters, but may also require some additional financial assistance from the banks.
For taking any decision on specific account either for inducting funds for revival,
effecting recovery through tagging of sale, initiating legal action for recovery of dues,
bank shall need detailed information in the form of history sheet in such account,
covering the background of the account, reasons for account becoming NPA, whether
the unit is functioning or lying closed, present position of the bank account, realizable
value of the security, financial standing of the borrower / guarantor, availability of
insurance cover from DICGC / ECGC, future profit generation, repayment capacity of
the unit, etc. The history sheet should also provide information with regard to meetings
/ contacts, if any made by bank’s officials with the borrower for regularization /
adjustment of the account and reaction of the borrower, along with comments /
recommendations of the branch as well as controlling offices.
Creation of Data Base for NPAs
In addition to taking action in specific accounts as discussed above, banks may have to
frame policy guidelines for the guidance of the field staff for effecting recovery in NPAs
for which they may have to create some data base on the following lines:
1. Classification of NPA accounts under various categories, i.e. Sub-standard, Doubtful
and Loss and reduction / recovery achieved or likely to be achieved under each head
through upgradation, amount written off, cash recovery, etc. as well as any addition
taken place due to slippage of standard account to NPA category. Further, NPA
accounts can be bifurcated under secured and unsecured categories and also under
various heads – whether suit filed, decreed, sick units under rehabilitation and other
accounts awaiting actions.
2. NPA data be collected under various heads – priority sector and non-priority sector
as well as those related to various industrial segments namely steel, cement, textile,
chemicals, etc. Such data can help in knowing the industries where NPAs are
concentrating for taking a view about flow of credit.
3. Bank should also have data on movement in NPAs portfolio, i.e. reduction /
addition under various assets categories, i.e. sub-standard, doubtful and loss both
amount-wise as well as according to the availability of securities under various heads
4. RBI has prescribed a system of “Off-site Surveillance” to review performance of
banks under various parameters on quarterly basis which also include progress with
regard to reduction and recovery in NPAs. Under the system RBI has prescribed
well-designed formats which are in five sections are briefly described as follows:
Section 1: Position of performing and non-performing loans facility-wise, i.e. cash
credits, overdrafts, bills purchased / discounted, term loans, etc. Further, the facilities
which are in performing category are to be reported under two main heads i.e. (i)
regular and (ii) irregular (overdue less than 90 days). As regards facilities which are
under NPA category are also to be reported under two main heads i.e. which are NPAs
for less than two years and those for more than two years. The section also contains
position of interest on NPAs which is in arrears.
Section 2: The section contains data on loan accounts both under performing and NPA
category. Further, NPA accounts are required to be classified under various heads i.e.
sub-standard, doubtful and loss. The provisions made by the bank in each asset code
category are also required to be mentioned.
Section 3: It provides the movement under various categories of loan accounts i.e. the
change in classification under sub-standard, doubtful and loss during the quarter under
review. The data also includes new advances made and amount recovered in NPAs.
Section 4: The section gives bifurcation of performing standard and non-performing
accounts under various sectors i.e. priority sector (agriculture, SSI, others) and non-
