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Internal Credit Rating Practices of Indian Banks

The overarching goal of the second Basel accord is aligning the capital requirements of banks with risk sensitivity. The accord emphasises the quantification of capital requirements on the basis of internal rating models. The internal credit rating models of banks are expected to produce the probability of default and loss given default to estimate the capital requirements of credit risk. This paper presents an analysis of the current status of internal credit rating practices of Indian banks. The survey reveals that the components of internal rating systems, their architecture, and operation differ substantially across banks. The range of grades and risks associated with each grade vary across banks analysed. This implies that lending decisions may vary across banks. There are differences among the rating systems of various banks. This paper presents a set of actions to improve the quality of internal rating models of Indian banks.

Internal Credit Rating Practices of Indian Banks

The overarching goal of the second Basel accord is aligning the capital requirements of banks with risk sensitivity. The accord emphasises the quantification of capital requirements on the basis of internal rating models. The internal credit rating models of banks are expected to produce the probability of default and loss given default to estimate the capital requirements of credit risk. This paper presents an analysis of the current status of internal credit rating practices of Indian banks. The survey reveals that the components of internal rating systems, their architecture, and operation differ substantially across banks. The range of grades and risks associated with each grade vary across banks analysed. This implies that lending decisions may vary across banks. There are differences among the rating systems of various banks. This paper presents a set of actions to improve the quality of internal rating models of Indian banks.

M JAYADEV

T
he initiatives for global best practices and banking standards began with the constitution of the Basel Committee in 1975. The first Basel Accord of 1988 (Basel I) emphasised the importance of minimum capital adequacy to address credit risk by devising the standardised approach. Capital adequacy is defined as the ratio of capital funds and risk weighted assets. Here the Basel Committee adopted a portfolio approach for deciding risk weighted assets. Each asset in the balance sheet carries a risk weight and sum total of these products are called as risk weighted assets. In India, the Reserve Bank of India (RBI) has suggested risk weights of 0, 20, 50, 75, 100 and 125 percentages for various types of assets. The rule is that a bank’s capital should not be less than 8 per cent (in India it is 9 per cent) of its risk weighted assets. However, Basel I has a number of limitations, particularly its insensitiveness to the risk of specific assets. It assumes a “one size fits all” approach by prescribing a standard risk capital requirement globally.

I Introduction

The New Basel Capital Accord (Basel II) addresses these deficiencies and focuses more on risk management by suggesting an internal rating framework for assessment of capital adequacy. Basel II emphasises the allocation of risk capital for all the three risks-credit risk, market risk, and operational risks and has also suggested a framework on indirect regulation by introducing market discipline. Although Basel II is addressing the capital requirements of all these three risks, the issues associated with the estimation of risk capital for credit risk are complex in nature and need to be addressed cautiously. Basel II suggests two frameworks: the standardised approach and the internal ratings based (IRB) approach for quantification of risk capital for credit risk. Under the standardised approach, different risk weights varying from 0 per cent to 150 per cent are suggested for various categories of assets, which are intimately related with the external ratings of various categories of borrowers.

The applicability of external ratings for estimation of capital requirements especially in the Indian market (also applicable to other emerging markets) suffers from several limitations such as, shopping attitude of borrowers for better rating and the presence of a large quantum of externally unrated borrowers in banks’ portfolios. Therefore, banks are expected to move to the internal ratings based approach for the estimation of capital requirements. Moreover, the thrust of Basel II is that banks have to make their capital requirements more risk sensitive by adopting the IRB approach. The internal rating system of a bank has to produce two essential components, probability of default (PD) and loss given default (LGD); a product of these two will give expected loss. In this context, the objective of this paper is to analyse the current internal credit rating practices of Indian banks and to suggest measures to improve the quality of their internal credit rating models, which ultimately helps in improving the quality of loan portfolios of commercial banks. Section II of this paper focuses on architecture, design, and components of internal rating models; measures to improve the quality of internal rating models are presented in Section III.

This paper is based on information gathered through a survey questionnaire from 19 banks and credit rating documents of six banks. Thus overall 25 banks are covered in this study. The loan portfolios of these banks, comprise 75 per cent of the total loan portfolio of scheduled commercial banks (excluding regional rural banks, cooperative banks and foreign banks) of India (Table 1). The questionnaire is focused on various dimensions of the architecture and design of credit rating systems of banks. I have also interviewed a few senior bankers to know more about the credit decision processes of various banks in rating different types of customers. As the data was collected from the banks assuming confidentiality, the identities of the banks are not disclosed in the analysis.

II Survey of Internal Credit Rating Practices

What Is a Rating System?

As per Basel (2000): An Internal rating refers to a summary indicator of risk inherent in an individual credit. Ratings typically embody an assessment

of the risk of loss due to failure by given borrower to pay as promised, based on consideration of relevant counter party and facility characteristics. A rating system includes the conceptual methodology, management processes, and systems that play a role in the assignment of a rating.

The internal rating model of a bank tries to capture all the risks faced by an entity and attempts to quantify such risks in a scientific manner. The model calibrates and communicates the risk associated with a borrower or a facility. Ideally, rating systems in a bank comprise of rating methodology, rating processes, control, data collection, IT systems, assignment of rating, rating transition matrix, probability of default, and loss in the event of default.

As per the Basel norms [BCBS 2004], an internal credit rating system should produce mainly two important variables, PD and LGD or recovery rates. Out of the 19 banks surveyed it is found that only nine banks have internal rating systems that give the output of the transition matrix, six banks are able to generate probability of default, and four banks are getting the data on recovery rates. In all the other banks, the rating system comprises of only rating methodology and assignment of rating (Table 2). Bank rating models are essentially focused on the rating of borrowers to judge their ability to pay loan interest and instalments. Theoretically, internal credit rating models are an effective instrument in the hands of banks for loan origination, pricing and monitoring. Ratings facilitate comparison among the large number of borrowers being financed by the banks. Banks’ credit rating systems are significantly different from those of credit rating agencies in architecture and design, as well as in the uses to which credit ratings are put.

Who Is Rated?

Fundamentally credit rating should be applicable to all borrowers. Large banks are found to apply rating models only to corporate accounts while small banks are rating all types of borrowers seeking a minimum credit limit. On an average, most banks are assigning credit ratings to the borrowers whose loan requirements are more than Rs 2 lakh. Apart from corporate customers the next important category is borrowers from small and medium level enterprises (SMEs) and the agriculture sector. Large and medium sized banks are rating borrowers whose loan requirements exceed Rs 20 lakh. These discrepancies may help borrowers to take advantage of rating arbitrage. For instance, a borrower may be unrated (rating is not applicable) as per bank X’s norms but the same borrower may be considered a rated borrower as per bank Y’s norms. Some banks have different models for different categories of borrowers. These categories are formed mostly on the basis of loan limit requirement, and size criteria (such as corporates and SMEs).

Seventeen of the surveyed banks are applying rating models to corporate borrowers; out of them five are applying models to borrowers whose loan requirements meet the minimum level criteria. This limit varies from bank to bank (for example Rs 2 lakh for one bank and Rs 5 crore for another bank). Thirteen banks are rating SME borrowers and six banks are concentrating on rating agricultural borrowers also. Although six banks have indicated the applicability of credit rating to retail loans also, discussions with the bankers reveal that certain retail loans such as educational loans and loans against shares are sanctioned by following certain norms instead of applying a rigorous credit rating methodology. Primarily, the rating models are more focused on evaluating the borrower’s capacity to repay the working capital loans. The models applied for term loans are modifications of the rating models applied for working capital limits.

Is the Borrower Rated or the Loan Facility?

A rating structure can have three dimensions. Rating can be on the basis of the characteristics of the borrower or on the basis of specific details of the transaction, or alternatively rating can be a summary indication of risk that comprises both borrower and transaction characteristics. The quality of credit decisions of a bank reflect in the type of rating dimension it has adopted. If banks choose to rate both borrower-wise and transaction-wise rating dimensions, a single exposure receives two types of ratings under these two dimensions.

The overwhelming majority of banks surveyed have explicitly adopted rating of borrowers and only four banks have ratings on both the dimensions. In the two-dimensional rating system that includes a borrower and transaction grade, transaction grades for different loans to the same borrower could differ. The source of these differences is primarily the collateral attached to the transaction. For example, a borrower may take a working capital loan which is normally secured against the inventory and book

Table 1: Composition of Loan Portfolios of Banks Participating in the Survey

(in per cent)

Name of Advances Proportion Proportion Proportion Proportion
Banks (in of Bills, of Term of Un of Loans
Rs crore) Cash Credit Loans secured to Com
and Over- Loans mercial
draft Loans Sector
Allahabad Bank 12544 53 47 11 43
Andhra Bank 11513 59 41 12 49
Bank of Baroda 35348 62 38 13 40
Bank of India 42633 64 36 22 36
Canara Bank 40472 67 33 14 49
Central Bank
of India 23159 58 42 10 38
Development
Credit Bank 2488 47 53 10 65
Federal Bank 6218 61 39 8 65
Global Trust Bank 3276 46 54 13 73
HDFC Bank 11755 44 56 14 80
ICICI Bank 53279 7 93 3 79
Indian Overseas
Bank 17447 65 35 9 40
Karnataka Bank 3900 71 29 8 58
OBC 15677 55 45 11 52
Punjab National
Bank 40228 59 41 7 42
State Bank
of India 137758 59 41 14 46
State Bank
of Indore 5183 62 38 6 47
State Bank
of Travancore 9171 66 34 13 52
Syndicate Bank 16305 56 44 23 37
The Karur Vyasa
Bank 3344 46 54 8 54
The South Indian
Bank 3613 55 45 17 62
Uco Bank 15923 57 43 10 51
Union Bank
of India 25515 66 34 10 48
UTI 7180 46 54 11 76
Vijaya Bank 7891 55 45 6 45
Total 551821 55 45 12 50

Source: Statistical Exhibits Relating to Banks in India, 2002-03.

Figure: Grading Scales of Indian Banks

Grading Scales

Number of Banks

778 6 4 2 0 6 7 8 910 11

2 2 4 1

Number of Grades

debts, whereas if it is a letter of credit it may not be secured if the margin imposed is less than the value of the credit. The survey finds only one bank assigns ratings purely on transaction alone. Rating on a transaction basis facilitates an estimation of the recovery rate, which is an essential output of an internal rating system.

Interviews with bankers reveal that some banks are practising rating the transaction once the borrower is rated; also rating dimensions actually being used by the banks are not reflected in the rating model. Banks which have systems to rate the borrower may also implicitly rate the loan facilities belonging to that borrower. It is also observed from the credit rating documents of select banks that certain risk parameters are exclusively applied to specific types of loan transactions. For example, debt service coverage ratio, an important risk factor, is implicitly applied to rate the borrowers seeking term loan requirements. The sophistication desired in this direction is more clarity in rating dimensions, and more robust rating models to give an idea about the recovery rates of various facilities.

‘Point in Time’ or ‘Through the Cycle’ Approach?

The banks I have surveyed rate the borrowers on the basis of current conditions. This is called rating on the basis of point in time. Whereas, under “through the cycle” approach, the borrower’s expected condition in a downside event is primarily considered for rating. In this method, long-term conditions and financial strategies adopted by the borrower may change the ratings. Through the cycle approach may be adopted to at least largescale borrowers as this provides an idea on rating in an adverse situation and helps the bank in estimating the additional capital requirements during serious conditions of recession. Through the cycle approach may be suitable to long-term loans exceeding more than three years and the point in time approach may be adequate for working capital loans as these are frequently reviewed.

What Are the Uses of a Credit Rating System?

An internal credit rating system provides many advantages to banks. It guides the loan origination process, portfolio monitoring, analysis of the adequacy of loan loss provisions, profitability analysis, loan pricing, risk capital allocation and incentives for employees. All the surveyed banks are using the credit rating system for loan origination, portfolio monitoring and reporting to senior management. Fifteen banks are pricing loans on the basis of internal rating models (Table 3). None of the banks have linked employee incentives with the risk grading system. Only four banks are using the models for profitability analysis of customers and only one bank is using the model for estimation of risk capital requirements and comparing the regulatory capital requirements with risk capital. In India ratings are applied essentially to price loans, as the banks are yet to explore the advanced uses of credit rating models for the estimation of loan loss reserves, risk capital, profitability, for loan pricing analysis and of ratings as inputs to formal credit portfolio risk management. Different uses place different stresses on the rating system and may have different implications for the internal controls needed to maintain the systems integrity [Treacy and Carey 1998]. For instance, if a bank intends to use credit rating for risk capital requirement it should carefully estimate the capital requirement with proper validation and back testing of the model.

How Many Grades?

A well functioning rating system differentiates risk within a loan portfolio. Grades are an effective way of expressing differentiation of risk categorisation of the entire loan portfolio. Differentiation of risk and pricing of loans are intimately related. Banks with the greatest degree of differentiation seems to be using ratings in loan pricing decisions. Differentiation of risk also facilitates portfolio credit risk management and helps in formulation of exposure norms for each category. The survey investigated the number of grades in the current rating structure, the number of pass grades and grades used in the watch category by banks. Thirty per cent of the banks surveyed have eight grades for the categorisation of borrowers (see the figure). The New Basel Accord [BCBS 2004] suggests that for rating corporates, a bank rating structure should have a minimum of seven borrower grades for non-default borrowers and one for those that have defaulted.

To facilitate easy decision making banks may categorise some grades as pass grades for which the loan facility will be sanctioned at an acceptable risk premium. All the banks have at least two and at most four categories which are not considered for granting of loan facility. A large number of grades on the rating scale is expensive to operate as the costs of additional information for fine grading of credit quality increases sharply [RBI 2002]. The frequency of legitimate disagreements about ratings is likely to be higher when rating systems have a large number of grades. A bank can initiate the risk grading activity on a relatively smaller or narrower scale and introduce new categories as the risk gradation improves.

Table 2: Components of Internal Rating Systems of Banks

Components No of Banks

Rating methodology 18 Rating processes 16 Control 11 Data collection 9 IT systems 8 Assignment of rating 16 Quantification of probability of default 6 Data on recovery rates 4 Rating transition matrix 9

Table 3: Uses of Internal Rating Models

Applications Number of Banks

Guiding the loan origination process 19 Portfolio monitoring 19 Reporting to senior management 19 Analysis of the adequacy of loan loss provisions 3 Profitability analysis 4 Loan pricing 15 Risk capital allocation 1 Employee compensation 0

Grades intended to capture heightened administrative attention are called watch grades. Prompt and systematic tracking is required on credits grouped in watch categories in the assessment of credit risk. Out of the banks surveyed, 13 have watch category grades built into the grading systems and six banks are silent about this. Banks are expected to develop complete rating descriptions and criteria for their assignment. Although most Indian banks have categorised the rating structure into grades they have not described the rating grades, only five out of the surveyed banks have supplemented the rating symbols with descriptions. One such surveyed bank’s rating description is presented in Table 4.

Who Assigns Rating?

The survey reveals that rating is being assigned at the branch level by a credit officer in case of eight banks, whereas for seven banks it is being done by sanctioning authorities including branch managers. In the case of four banks, credit rating is a centralised function. If the credit rating is a decentralised function, the scope for subjectivity in understanding the business, industry and management risk factors would vary and ultimately overall rating may be either under-stated or overstated. Unless continuous training is imparted for credit rating officers working at branches and other administrative units, the consistency of the application of the model would be doubtful.

What Weights Are Assigned for Various Risks?

The survey enquired about various risk factors considered by banks in rating the borrowers. The overwhelming majority of banks consider financial risk as the prime risk factor; the rest of the surveyed banks may also consider financial risk as an important risk factor but they have not clearly indicated this. Banks are assigning around 40 per cent weight for financial risk factors. The other prominent risk factors are management risk and industry risk (Table 5). Internationally, the best practice is that industry risk factors account for 20 to 30 per cent of total score and management risk factors account for 10 to 15 per cent of total score [Scott 2003].

What Are the Risk Factors Considered?

Financial risk: Analysis of financial statements is central to appraising borrowers’ financial risk. Financial risk is expressed by various financial risk parameters which are computed from the financial statements of the obligor. These parameters are expressed as ratios between the two variables of financial statements. A wide range of risk parameters are being used in assessing the financial risk of the borrowers (Table 6). Almost all the surveyed banks are considering current ratio as the prime variable for rating the financial risk of borrowers. Current ratio indicates liquidity of the borrower in meeting all current obligations. The second most prominent ratio is debt-equity ratio, which explains the relationship between total outstanding liabilities and equity. This ratio indicates the solvency position of the borrower in meeting current and long-term liabilities. Among the profitability ratios, net profit margin, operating profit margin, and return on capital employed are the important ratios. The exact definitions of these ratios are found to vary from bank to bank. For example, a bank may consider term loan instalments due within one year as part of the current liability for the purpose of current ratio whereas other banks may not regard this item as current liability.

The standard way of using financial ratio analysis is to compare firm level ratios with those of the same industry. But most credit rating models do not have this feature of comparison at all. Rating is a process involving judgment because the strength of financial ratios may vary with various other characteristics of borrowers. Banks also give importance to the size of borrowers represented by sales or total assets and net worth. Many firms which do not have access to capital market resources often have low assets or net worth. In contrast large firms have several alternative financing avenues, more salable assets in case of a stress scenario and firmly established market presence. For these reasons many banks assign relatively risky grades to small firms although their financial characteristics suggest a more favourable rating. Table 7 shows the financial risk factors considered by a few Asian

Table 4: Risk Description

Grade Description

A++ Indicates an exceptionally high position of strength, very high degree of sustainability

A+ Indicates a high degree of strength on a factor among the peer group, high sustainability

A Indicates a moderate degree of strength with positive outlook

B+ Indicates a moderate degree of strength with suitable or marginally negative outlook

B Indicates weaknesses on a parameter in comparison to peers, unstable outlook

C Indicates a fundamental weakness with regard to the factor, unlikely to improve under normal circumstances.

Source: Credit rating document of a surveyed bank.

Table 5: Weights Assigned to Various Risks (no of Banks)

Weights Financial Business Risk Industry Risk Management (Per Cent) Risk Risk

0-200 4 99 20-4010 9 5 8 40-604 1 01 60-804 0 00 18 14 1418

Table 6: Financial Risk Factors Considered by Internal Credit Rating Models

Financial risk factors No of Banks

Current ratio 16 Debt-equity ratio (total liability to total net worth) 16 Growth rate or trend in sales 10 Growth rate or trend in net profits 11 Net profit margin 14 Gross profit margin 10 Operating profit 8 Operating leverage 5 Interest coverage ratio 13 Debt-service coverage ratio 14 Cash flows 9 Financial leverage 6 Asset turnover ratio 9 Working capital turnover ratio 7 Return on net worth 6 Return on capital employed 13 Return on assets 5 Stock turnover ratio 12 Debtors turnover ratio 11 Asset coverage ratio 6 Bank borrowings to sales 3 Any other (trends in performance, security coverage) 2

banks, which reveals that the ratios considered by the Indian banks are almost similar to many international banks.

The quality of financial information is also essential in analysing financial ratios. Many banks are giving due importance to the qualifications being made by auditors while analysing the financial statements of a borrower. The survey also reveals that banks assign importance to board structure, family group, and managing director of the company (Table 8) while rating the borrower. Industry risk: Industry ratings are a critical element of any internal rating system and a well designed risk rating system should identify potential future problems with businesses that may appear today to be financially sound with acceptable credit risk. Industry ratings are akin to assessing a healthy individual’s genetic predisposition to contract a medical condition. It is “corporate DNA testing”, an assessment of the family background of an apparently healthy company [Scott 2003]. For setting portfolio limits, industry risk rating is essential. Competitive scenario of the industry, natural and artificial barriers, government policies and the general political environment are factors generally considered while assessing the industry risk (Table 9). Some banks are using business risk and industry risk interchangeably whereas, others have different weights for them. The variables considered for business risk and industry risk are also vary widely (Appendix I and II) across banks. Many banks have not even conceptualised industry risk properly. The concept of business risk is also not clear in the observed credit rating documents. Wide variations are observed in parameters considered for industry risk of select Indian banks. Management risk: Under management risk, banks judge the quality of the borrower’s management and assign a risk weight to this factor. Almost all banks are considering professional experience of management and financial discipline of borrowers as an important factor in assigning better ratings (Table 10). The professional experience of management indicates its ability to achieve a higher level of financial performance throughout the business cycle and its attitude in protecting the interests of lenders. Appendix III demonstrates management risk factors considered by select banks. Like business risk factors, these are broadly worded and it is difficult for the rater to understand their real meaning, especially when a large number of people are involved in the rating process at different branches of a bank. In order to improve the utility of these factors for credit rating, banks have to focus more on continuous training and mentoring. Other risk factors: Most of the banks are considering some factors as negative factors (Table 11) while rating the borrowers. For arriving at the comprehensive rating or fine rating, marks relating

Table 8: Qualitative Factors Considered in Analysing Financial Statements

Factors Considered No of Banks

Board structure 10 Group to which the company belongs 11 Chairman of the company 11 Managing director of the company 10 Statutory auditors of the company 11 Important qualifications being made by the auditors 16 Disclosures according to USGAAP 8 Credit rating assigned by external agencies such as CRISIL, ICRA, CARE, etc 12

Table 9: Industry Risk Factors Considered by Internal Rating Models

Industry Risk Factors No of Banks

Competition 17 Technology 14 Brand 12 Availability of substitutes 13 Environmental risk 13 Export potential 9 Accessibility of inputs 13 Marketing network 15 Product characteristics 11 Barriers to entry for new players 13 Any other (specify) 5

Table 10: Management Risk Factors Considered by Internal Rating Models

Management Risk Factors No of Banks

Professional experience of management 18 Labour relations 12 Professional qualifications of management 14 Transgressions 8 Submission of monthly/quarterly and periodic statements 14 Financial discipline of borrowers 16 Relationship with the bank 15 Corporate governance 13

Table 11: Other Factors (Negative) Considered While Rating the Borrowers

Other Factors No of Banks

External Diversion of Funds 13 Delayed submission of QIS and other Financial Statements 15 Irregularities in Documentation 12 Default on Payment of LC and other Guarantees 16 Dishonour of Commercial Banks 15 Irregularities in Operations of the Account 16 Non-compliance to Terms and Conditions 14 Others 7

Table 7: Benchmarking of Financial Criteria Used by Asian Banks

Criteria US Bank in Asian Market Asian Bank 1 Asian Bank 2 Asian Bank 3 Asian Bank 4
Liquidity Quick ratio Leverage Debt-to-Equity ratio Cash flow Interest cover EBITDA to total debt Profitability Pretax return on average capital Efficiency Growth Size Capitalisation Current ratio Debt-to-equity Cash flow/total debt Cash flow/debt and Payables Cash flow/sales ROI, Net income/assets, Gross profit margin Assets turnover, Inventory/sales, Labour, production, Sales growth rate Equity growth rate Sales growth rate Debt-to-equity EBITDA to interest expense ROAE Net profit margin Inventory/sales Current ratio Debt-to-equity EBITDA to interest expense ROAE Net profit margin Inventory/sales Receivables/sales Current/Quick ratio Equity-to-debt Net working capital to interest EBITDA to interest expense ROE Net income/sales Sales
Source: Scott 2003.
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to these factors are deducted from the total marks computed from all the other risk factors.

How Do Banks Arrive at the Overall Credit Rating of Borrowers?

After evaluating the borrower on various risk parameters a credit rating model produces an overall rating of the borrower by aggregating the scores of various risk parameters. Most of the banks are using simple arithmetic summation of scores arrived at under various risk parameters or a weighted average approach. While aggregating some banks are considering the importance of the size of the company. For example, two different companies may have similar debt-equity ratios but a company larger in size shall certainly have higher shock absorbing capacity than the smaller size company. Once the scores are aggregated banks assign an equivalent rating. For example, one of the surveyed banks’ overall rating methodology is presented in Table 12.

Arriving at overall rating in this method is simple and easy for implementation. However, banks may shift over to other sophisticated multivariate techniques like logit/probit models and discriminant analysis. These techniques will combine the various risk parameters and also produce PD, an essential parameter required under internal rating models approach. Altman’s (1968, 2002) Z score model gained popularity among the multi-variant techniques. Thomas (2000) suggests various approaches to arrive at a single credit score by aggregating multiple risk factors. Though a few banks made an attempt to apply multiple discriminant analysis on select data on an experimental basis, there is no concrete evidence of use of these models in the credit decision process.

How Frequently Ratings Are Reviewed?

Review of rating is an essential component of credit risk management. Reviews are multifold: monitoring by those who assign the initial rating of a transaction, regularly scheduled rating reviews for select exposures, occasional reviews, review at the time of renewal of loan, yearly or half yearly review. Many banks have agreed that they conduct yearly reviews of ratings (Table 12) and the next important review is at the time of renewal of loan limits. A strong review process also aims to identify and discipline managers who produce inaccurate ratings. Such a step provides strong incentives for the individuals most responsible for negotiating with the borrower to assess risk properly and to think seriously about credit issues at each stage of credit decision making. Ratings should be reviewed by an independent credit risk management or loan review office both at the inception of a transaction and periodically over the life of the loan. Such reviewers should have adequate experience and business judgment comparable to that of line managers responsible for assigning initial risk grades. If a bank relies on outside consultants, auditors or other third parties to perform all or part of this review role, such individuals should have a clear understanding of the institution’s credit culture and its rating process, in addition to commensurate experience and competence in making a credit judgment.

Are Internal Ratings Mapped with External Ratings?

Banks may compare and map the internal ratings assigned by them with the ratings of credit rating agencies. This may lead to the problem of circularity [Treacy and Carey 1998] as raters of internal ratings already know the agency grade for a given borrower and have an idea of a borrower’s likely position on the internal scale. Obviously, if the agency rating is the sole criterion used in assigning internal grades to agency rated borrowers, rated and unrated borrowers within a given internal grade might differ substantially in risk. In such circumstances the mapping is circular because borrowers are assigned internal grades based on the agency rating, and the agency rating corresponding to each internal grade is inferred only from such rating assignments [Treacy and Carey 1998]. The banks I surveyed show that 10 out of 19 banks compare internal grading with that of external rating agencies. The portion of rated advances in the total loan portfolio and amount of loans under each risk grade is not available in the public domain. Therefore a view about the size of rated advances and composition of advances with different risk grades is difficult to analyse. Hence, it is difficult to judge the correctness of mappings at this stage.

III Improving the Quality of Internal Rating Systems

Credit risk ratings are designed to reflect the quality of a credit exposure and explicitly or implicitly the loss characteristics of that exposure. A consistent and meaningful internal risk rating system is a useful source of differentiating the degree of credit risk in loans and other credit exposures. This consistency and meaning is rooted in the design of the risk rating system itself. Considering the importance of a robust credit rating system, this section outlines certain measures to improve the quality of credit rating system. The section is heavily dependent on the minimum requirements of an internal rating based approach stipulated by Basel Accord [BCBS 2004] and the guidance notes issued by Federal Reserve (2003).

Definition of Default

The generally acceptable accounting definition of default is when the interest or principal installment on any credit exposure is due for more than 90 days. Banks which are in the process of implementing advanced credit rating models are recognising that downgrading is also a default event. Harmonisation of default definition would facilitate creation of data pool across banks. Consistency in identification of default is fundamental to any IRB system. In the Indian context, only from the year 2004 onwards has the delinquency norm of 90 days been introduced. “The greening of assets” may be avoided, which would dilute the importance of a rating system in a bank. In defining the default rating systems must also capture so-called “silent defaults” or defaults when the loss on a facility was avoided by liquidating

Table 12: Computation of Overall Credit Rating of a Borrower

Scores Gradation Risk Nature
More than 90 1 Very Low
More than 80 2 Low
More than 70 3 Moderately low
More than 60 4 Fair
More than 50 5 Mode rate
More than 40 6 High
More than 30 7 Very high
Less than 30 8 Critical

Source: Credit rating document of one of the surveyed banks.

underlying collaterals [Federal Reserve 2003]. The rating definitions and criteria must be both plausible and intuitive and must result in a meaningful differentiation of risk [BCBS 2004]. Rating systems should be flexible enough to cope with all foreseeable types of risks. Similarly, rating systems should be able to handle all types of borrowers belonging to various businesses of different industries [Krahnen and Weber 2001]. Useful output from a credit rating system may be expected provided default definition and time horizon are consistent.

Rating Philosophy

Bank managements should clearly articulate whether their internal rating system is “point in time” or “through the cycle”. If the bank adopts a point in time rating system, obligors are grouped by probability of default frequency over the next year. Alternatively, borrowers may be rated on the basis of over a wide range of possible stress outcomes, which is called through the cycle rating system. Choosing between these two systems forms a rating philosophy. Point in time ratings change from year to year as the borrower’s circumstances change, including changes due to economic possibilities. Since the economic circumstances of many borrowers reflect the common impact of the general economic environment, the transitions in point in time ratings will reflect that systematic influence. Merton’s (1974) probability of default prediction is in line with the point in time approach of rating. Through the cycle rating systems do not estimate PD over the next year; instead, they assign obligors to multiple groups that would be expected to share a common default frequency if the borrowers in them were to experience distress, regardless of whether that distress is in the next year. This rating philosophy abstracts from near-term economic possibilities and considers a richer assessment of the possibilities. Normally external rating agencies follow the philosophy of through the cycle rating approach whereas banks’ internal rating models are point in time. Regardless of rating philosophy, the bank management must articulate the implications of the bank’s ratings philosophy for its capital planning process. Capital management policy should be articulated according to rating philosophy to avoid capital shortfalls on times of systematic economic stress.

Obligor Rating Granularity

A bank must justify the number of obligor grades used in its rating system and the distribution of borrowers across those grades. The grade definition must include both a description of the degree of default risk typical for borrowers assigned the grade and the criteria used to distinguish that level of credit risk. The modifiers used or numeric grades (+ or – to alpha or A1, A2) will only qualify as distinct grades if the bank has developed complete rating descriptions and criteria for their assignment and separately quantified PDs for these modified grades (Basel 2004). If modifiers (such as plus or minus) are attached with ratings, banks should clarify whether these constitute a separate grade or not. Bank should develop a distinct rating definition and criteria for the modified grade. If a bank has diverse credit quality they may have a greater number of borrower grades (Basel 2004). Each obligor grade in turn must be associated with a single PD. The rating of obligors must result in a ranking of obligors by PD. The borrower rating should be distinct from the loss severity rating which is assigned to the facility and collateral as well as other characteristics should not influence the obligor rating. In the Indian system some banks are combining these two. For example in a 1 to 10 rating system where risk increases with the number grade, a defaulted borrower with a fully cash secured transaction should be rated as 10 (lowest), regardless of remote expectation of loss. Similarly, a borrower whose financial condition warrants the highest investment grade rating should be rated as one, even if the bank’s transactions are subordinate to other creditors and unsecured. Since a rating is assigned to the obligor and not to the facility, separate exposures to the same obligor must be assigned to the single obligor rating grade.

Loss Severity Ratings

The two dimensions of a qualifying IRB system are quantification of default risk of borrower and risk of specific transaction. The orientation of first dimension is that the rating of the borrower is same irrespective of his exposure to bank transactions. For example, he may take a partly secured working capital loan and a fully secured term loan from a bank. Regardless of the nature of the transaction under the first dimension, the rating would be same. Under the second dimension, the adjustment of security should reflect on the borrower’s grade. The LGD estimate is the loss the bank is likely to incur in the event that the obligor defaults, and is expressed as a percentage of exposure at the time of default. LGD estimates can be assigned either through the use of a loss severity rating system or they can be directly assigned to each facility. A bank must estimate a long-run average LGD for each facility. Since defaults are likely to be clustered during times of economic distress and LGDs may be correlated with default rates, a time weight may materially understate loss severity per occurrence. Moreover, for exposures for which LGD estimates are volatile over the economic cycle, the bank must use LGD estimates that are appropriate for an economic downturn if those are more conservative than the long run-average. LGD estimates must be grounded in historical recovery rates and, where applicable, must not be based solely on the collateral’s estimated market value. Estimates of LGD must be based on a minimum data observation period that should ideally cover at least one complete economic cycle but must, in any case, be not shorter than a period of seven years from at least one source [BCBS 2004].

Regarding retail exposures, rating systems must be oriented to both borrower and transaction risk and must capture all relevant borrower and transaction characteristics. Banks must assign each exposure that falls within the definition of retail for IRB purposes into a particular pool. Banks must demonstrate that this process provides for a meaningful differentiation of risk. For each pool bank must estimate PD, LGD, and EAD [BCBS 2004].

Multiple Ratings Systems

A bank’s size of the loan portfolio and complexity in product range will affect the types and numbers of rating systems employed. Banks may develop one risk rating system that can be used across the entire commercial loan portfolio. Alternatively, a bank can choose different rating systems for different types of portfolios. A bank may have as many different rating systems as necessary and as few as possible. The reasons for choosing the number of rating systems should be made transparent. For example, two different rating systems are required to evaluate real estate companies and companies in manufacturing activity. Similarly the bank should not divide the set of companies into too many subsets and construct too many different rating systems. Certain companies may fall into more than one rating system and create a difficulty in back testing due to the relatively smaller number of data points [Krahnen and Weber 2001]. Banks may combine rating models for some loans and expert judgment systems for others. The bank must document the rationale for assigning a borrower to a rating system. However the aim of use of multiple rating systems should not be to minimise capital requirements inappropriately [BCBS 2004].

Informational Efficiency

A rating system should accommodate all the available information and such information should be modelled correctly in the rating. The current credit rating of a borrower should be the best basis for predicting tomorrow’s rating. The rating system should cope with splitting bias. Splitting bias suggests that presenting an attribute more in detail may increase the weight it receives. Credit officers may have the tendency to rate qualitative criteria of a rating system better than quantitative ones and they tend to change qualitative variables less than quantitative [Krahnen and Weber 2001].

Documentation of Rating Systems

Banks must document in writing their rating systems design and operational details. The documentation is an evidence of the bank’s compliance with the minimum standards and must address topics such as portfolio differentiation, rating criteria, responsibilities of parties that rate borrowers and facilities, definition of rating exceptions, parties that have authority to approve exceptions, frequency of rating reviews, and management oversight of the rating process. Rating criteria and procedures must be periodically reviewed to determine whether they remain fully applicable to the current portfolio and to external conditions. If the bank employs statistical models in the rating process the bank must document their methodologies [BCBS 2004].

Minimise the Error of Human Judgment

Undoubtedly the rating process involves the exercise of human judgment while considering the assignment of rating and weight given to each factor. Among the surveyed banks almost all of them are using judgmental rating methods for rating the borrowers on management and industry risk parameters. Different individuals in the same bank may understand certain risk parameters differently. This is more pertinent while rating the borrowers on industry risk and management risk. For example, almost all the banks are assigning weights to the competition while assessing the business risk. For the credit officer at the branch level it is difficult to comprehend the concept of competition. He may consider purely local factors of a specific geographical area while the firm may face competition from non local units and ultimately the borrower may encounter competition risk substantially. Unless the bank provides rigorous training to all users of the model, the degree of objectivity will be very low in evaluating business and industry risk factors. The rating system should be identical regardless of the person who rates. It should stand for the test of stationarity property1 [Krahnen and Weber 2001].

Data Maintenance

Indian banks have not paid much attention to storing of default data on each type of loan by risk grade. Even if they have done so, the data is available on regulatory categorisation loans but not on the basis of risk grades. Under regulatory categorisation also the norms for categorisation of bad loans is not uniform for the last six or seven years. Therefore, banks have to make a beginning in collection and maintenance of different loans as per loan performance and grading. A bank must collect and store data on key borrower and facility characteristics to provide effective support to its internal credit risk measurement and management processes. Banks must maintain rating histories on borrowers and recognised guarantors, the dates the ratings were assigned, the methodology and key data used to derive the rating and the person or model responsible for rating. The identity of defaulted borrowers and facilities, the timing of default and circumstances of such defaults must be retained.

Validation Process

Banks must implement a process to ensure the accuracy of their rating systems. Banks must have a robust system in place to validate the accuracy and consistency of rating systems, processes and the estimation of all relevant risk components [BCBS 2004]. Rating system accuracy is a combination of two things – the actual long-run average default frequency for each rating grade is not significantly greater than the PD assigned to that grade and the actual stress condition loss rates experienced on defaulted facilities are not significantly greater than the LGD estimates assigned to those facilities. A bank must demonstrate to its supervisor that the internal validation process enables it to assess the performance of internal rating and risk estimation systems concisely and meaningfully. While doing validation, estimates of PDs, LGDs and EADs are likely to involve unpredictable errors. In order to avoid over optimism, a bank must add to its estimates a margin of conservatism that is related to the likely range of errors. Where methods and data are less satisfactory and the likely range of errors is larger, the margin of conservatism must be larger [BCBS 2004].

Back Testing

Banks must establish internal tolerance limits for differences between expected and actual outcomes. The ex-ante default should not be significantly different from the ex post default frequency. Back testing in credit risk management is difficult because of non-availability of market prices for loans. The historical data on credit defaults is also limited. Therefore, pooling of resources across different banks may create a better data base which facilitates improved back testing. Back testing is a focal point for validating rating, the need for it yields some important implications for the design and use of ratings.

Credit Risk Control

Banks must have independent credit risk control units that are responsible for the design, implementation and performance of their internal rating systems. The unit must be functionally independent from the personnel and management functions responsible for originating exposures. Areas of responsibility must include: (a) Testing and monitoring internal grade.

  • (b) Production and analysis of summary reports from the bank’s rating system to include historical default data stored by rating at the time of default and one year prior to default, rating migration analysis and monitoring of trends in key rating criteria.
  • (c) Implementing procedures to verify that rating definitions are consistently applied across departments and geographic areas.
  • (d) Reviewing and documenting any rating changes to the rating process, including the reasons for the changes. (e) Reviewing the rating criteria to evaluate if they remain predictive of risk. Changes to the rating process, criteria or individual rating parameters must be documented and retained for supervisors to review. A credit risk control unit must actively participate in the development, selection, implementation and validation of rating models.
  • Corporate Governance

    All material aspects of the rating and estimating processes must be approved by the bank’s board of directors. These parties must process a general understanding of the bank’s risk rating system and detailed comprehension of its associated management reports. Senior management must also have a good understanding of the rating system’s design and operation and must approve material differences between established procedure and actual practice. Management must also ensure on an ongoing basis, that the rating system is being operated properly. Management and staff in the credit control function must meet regularly to discuss the performance of the rating process, areas needing improvement and the status of efforts to improve previously identified deficiencies. Internal ratings must be an essential part of the reporting to these parties. Reporting must include risk profile by grade, migration across grades, estimation of the relevant parameters per grade, and comparison of realised default rates against expectations. Reporting frequencies may vary with the significance and type of information and the level of the recipient. Senior management must provide notice to the board of directors for any material changes or exceptions from established policies that will impact the operations of the bank’s rating system.

    Internal and External Audit

    Market testing is possible for external ratings but for internal ratings there is no external check. Testing for neutrality of internal ratings is a serious test of rating methodology and rating performance. Internal audit or an equally independent function must review at least annually the bank’s rating system and its operations, including the operations of the credit function and the estimation of PDs, and LGDs. Internal audit must document its findings.

    Conclusion

    The components of internal rating systems, their architecture and operation differ substantially across the surveyed banks. The range of grades and risks associated with each grade vary across the banks analysed. This implies that lending decisions may vary across the banks. There are differences among the rating systems of various banks. No single rating system is best for all banks. Building an internal rating system and implementing it successfully to get the desired result is a complex task in a banking entity.

    Appendix I: Business Risk Factors

    Bank X

    1 Past commitments with respect to net sales. 2 Past commitment with respect to net profit. 3 Conduct of the account 4 Compliance of terms and conditions 5 Income value of the Bank (Interest, commission, exchange, etc, from the

    account as percentage of total fund based limit) 6 Repayment of installment (for term loan) 7 Security coverage (collateral) 8 Trend analysis

  • (a) Trend analysis-variation in net current assets
  • (b) Trend analysis-variation in tangible net worth
  • (c) Trend analysis-profitability (net profit/net sales or receipt)
  • Bank Y

    1 Market position/Current market share 2 Operating efficiency 3 Growth 1 Market position/Current market share

    Products

  • Product range (single product dependence or wide range of products)
  • Consistency of quality (approach toward quality assurance)
  • Support service facilities (ability to provide service after sales)
  • Customisation of product (ability to provide customised products)
  • Shelf life of product.
  • Prices

  • Pricing flexibility (flexibility to increase prices in line with costs) _ Brand equity
  • Bargaining power with suppliers (to control cost of input effectively)
  • Bargaining power with buyers (whether monopolistic, etc)
  • Place (Selling/Marketing)

  • Distribution set-up
  • Geographical diversity of markets (both domestic and international)
  • Long-term contracts/assured off take
  • Promotion (based on needs/competition)

    – Advertising expenditure (required as well as ability to sustain)

    – Other promotional ventures (whether undertaken and whether beneficial) 2 Operating efficiency

    Raw material

  • Related risk and mitigation
  • Availability of raw materials
  • Import content substitution (degree of indigenisation)
  • Management of product price volatility
  • Manufacturing and selling

  • Overall cost structure advantage/disadvantage form
  • Capacity utilisation
  • Management of operative cost (employee/energy/technology)
  • Management of selling costs.
  • Technology adoption
  • Location advantage.
  • Others

  • Availability of utilities (power/water, etc)
  • Adherence to environmental/domestic/international regulation
  • Foreign exchange earnings
  • – Working capital management 3 Growth

  • Increase of net sales over last year (per cent)
  • Increase of operating profit margin over last year (per cent)
  • Debtor’s velocity (months)
  • Bank Z

    1 Competition

  • There is no competition in the nearly area
  • Competition is existing but not a threat
  • Company has to exist among stiff competition/faces difficulty in sustaining growth
  • Heavy competition leading to insipid growth 2 Locational advantage
  • Located in an area with huge demand
  • Located among competitors but standing is long (> 10 years)
  • Located among competitors but with a standing of 5 to 10 years.
  • No locational advantage 3 Commodities traded
  • Traded commodities have consistent demand with no seasonal fluctuation
  • Demand fluctuation would not impact the growth
  • Demand fluctuation results in constant revision according to market trend
  • High fluctuation on demand leading to poor growth 4 Market perception
  • Cash and carry business leading to constant cash flow
  • Available credit from supplier matches extension of credit to customers.
  • Largely dependent on credit sales with satisfactory realisation
  • Largely dependent on credit sales but realisation is poor
  • Appendix II: Industry Risk Parameters

    Bank X 1 Present industry/activity scenario dealt by is favourable. 2 Technology/activity is proven for medium-term. 3 Demand of the product is increasing. 4 Availability of raw material/ products (traders) is adequate. 5 Industry/activity does not depend on the vagaries of nature. 6 The products have established markets. 7 Quality of product is satisfactory. 8 Product range/mix is satisfactory. 9 Threat of substitute/competitors to the product/s is not there.

    10 Firm is not assembler or trader of unbranded items.

    Bank Y

    1 Industry characteristics

  • Importance to economy (in terms of industry size/contribution to production/exports/employment generation/forward and backward linkages)
  • Cyclicality (impact of cyclical fluctuations on industry performance)
  • Sensitivity of the industry to government policies (duties/price controls and licensing or environmental norms)
  • Growth potential/outlook of the industry (best estimate of next five
  • years’ average annual growth per cent) 2 Competitive forces

  • Extent of competition among domestic/international players
  • Threats of imports/substitute/unorganised sector
  • Technology risk(does industry require constantly changing technology or R&D/rate of obsolescence of technology)
  • Barriers to entry for new players (interims of technology, high cost, long gestation period)
  • Bargaining power of buyer industries
  • Bargaining power of supplier industry
  • International competitiveness
  • – Fluctuation and demand-supply gap 3 Industry financials

  • Return on capital employed – ROCE (three years industry average per cent)
  • Operating margins (three years industry average per cent)
  • Earning stability
  • Appendix III: Management Risk Factors

    Bank X 1 Management is an established player for more than five years. 2 Have good reputation and track record. 3 Have satisfactory relations with the bank for more than three years. 4 Business is not managed by one or two persons. 5 Management is financially able to withstand competition. 6 Borrowers not dealing in perishable goods. 7 Future growth potential is high. 8 Borrowers are not dependent on limited suppliers. 9 Business is not cyclical or there are no cyclical earnings.

    10 Borrowers not dependent on limited customers.

    11 Market share is satisfactory and acceptable.

    12 Distribution set-up is satisfactory.

    Bank Y Compulsory parameters/track records

    1 No of years of experience in industry 2 Quality of management personnel 3 Percentage of actual sales achieved to projections made last year. 4 Percentage of net profit achieved to projections made last years. 5 Percentage of actual net working capital to projections made last year. 6 Payment record to bankers/institutions

    Other relevant parameters

    1 Group support 2 Management succession 3 Corporate governance 4 Credibility

    Bank Z

    Management quality: 1 Management experience

  • The promoters have been in the trade for more than a decade and are well experienced
  • The promoters are in the trade for over five years, but less than 10 years
  • Promoters are in the trade for less than five years
  • – Management is totally new in venture 2 Succession planning

  • Family business and no cause for concern
  • Promoters are young and have family back up
  • Promoters are old but succession by family members is expected
  • Promoters are old and no back up for succession
  • In this process human judgment plays central role and a variety of possible uses of ratings can influence the rating decisions. Thus banks have to design carefully controls and internal review procedures for the effective implementation of internal rating systems. Internal rating systems promote a credit culture in the organisation. It should hold managers accountable for credit quality. The banks should consider critically the culture factor in designing rating systems.

    Internal rating systems are expected to operate dynamically. As ratings are assigned, quantified and used, estimates will be compared with actual results, data will be maintained and updated to support oversight and validation efforts and for better future estimates. Rating systems with appropriate data and oversight feedback mechanisms foster a learning environment that promotes integrity in the rating system as well as continuing refinement. Internal rating systems need the support and oversight of the board and senior management to ensure that the various components fit together seamlessly and those incentives to make the system rigorous extend across line, risk management and other control groups. In the absence of strong support and involvement of board and senior management, rating systems are unlikely to provide accurate and consistent risk estimates during both good and bad times.

    m

    Email: jayadev@iiml.ac.in

    Note

    [This paper is part of the research report entitled ‘Basel-II and Credit Risk’ submitted to the Indian Institute of Banking and Finance, Mumbai. Author wishes to express gratitude to the anonymous referee and to Joshy Jacob for their useful comments on this paper.]

    1 A PD is based on an ex-ante point of view. It states that a company within PD 0.7 per cent has a 7 in a 1,000 chance to be default within a given time period. We know from research on capital markets that testing expectations is always tricky. In order to relate (ex-ante) expectations of (ex-post) observed data, we have to assume that the structure of the problem under consideration remains constant from the date where expectations are formed to the date where observations are taken. This assumption is called the stationarity assumption.

    References

    Altman, I Edward (1968): ‘Financial Ratios, Discriminant Analysis and Prediction of Corporate Bankruptcy’, Journal of Finance, 23, pp189-209.

    – (2002): Bankruptcy, Credit Risk and High Yield Junk Bonds, Blackwell

    Publishers. Basel (2000): Range of Practice in Banks’ Internal Ratings Systems, January. BCBS (2004): International Convergence of Capital Measurement and Capital

    Standards, Basel Committee on Banking Supervision, June. Federal Reserve (2003): ‘Draft Supervisory Guidance on Internal Ratings Based Systems for Corporate Credit’, July 1.

    Krahnen Jan Peiter, Martin Weber (2001): ‘Generally Accepted Rating Principles: A Primer’, Journal of Banking and Finance, 25, pp 3-23.

    Merton, R C (1974): ‘On the Pricing of Corporate Debt: The Risk Structure of Interest Rates’, Journal of Finance, 29, pp 449-70. RBI (2002): ‘Guidance Note on Credit Risk Management’, Reserve Bank of India, October.

    Scott, Roman (2003): ‘Credit Risk Management for Emerging Markets: Lessons from the Asian Crisis’, in Gordian Gaeta (ed), Frontiers in Credit Risk, John Wiley and Sons (Asia), Singapore.

    Thomas, Lyn C (2000): ‘A Survey of Credit and Behavioural Scoring: Forecasting Financial Risk of Lending to Customers’,International Journal of Forecasting, No 16, pp 149-72.

    Treacy, William F, Mark S Carey (1998): ‘Credit Risk Rating at Large US Banks’, Federal Reserve Bulletin, November, pp 897-921.

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