Credit Risk management

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A Study on Credit Risk Management

Preface

The history of the banking sector of Bangladesh is fairly short and started with the nationalization of all banks (except the branch of foreign banks) operating in the country immediately after the liberation. As a step towards establishment of the government's socialist leaning economic policy, all banks were nationalized. The banking sector of Bangladesh has grown over the time under the bank branching system. Structurally, the banking system is composed of institutions: the central bank, commercial banks, specialized banks, development financing institutions (non-banking institutions) and cooperative banks. The banking sector of Bangladesh provides an interesting study regarding various effects of macroeconomic variables and portfolio elements on the profitability of the banks because it went through phases of both financial repression and liberalization. The issue of profitability and the banking sector performance in Bangladesh continues to be a perennial source of discussion among academicians, policy makers and the practitioners. Credit risk decision is crucial for a financial institution like bank.

So here we would like to attempt to study on credit risk management and we have selected our field as United Commercial Bank (UCBL).

Basically we would try

· To assess the credit risk managing behavior of our selected bank UCBL· To examine the relationship between Mortgages and default risk premium by bank.

The profitability of banks depends on the operational efficiency of the banks no doubt but some scholars in this fields, economists and policy makers believe that the profitability of banks also depends on some external factors as well as internal. These are general expectation of banks with respect to general economic trends, environmental, seasonal and political situations. However the specific expectations are the changes in money supply, capital market and money market trends, export-import, real and service sector production etc. many economists found that the control of expenditures is the prime determinant of the creditworthiness of client. . Mogen (1971) in his study mentioned that the money market conditions, money supply, population growth rate and individual banking habit have effects on the banking performance i.e. it is effecting the credit risk managing behavior and assessing behavior of the bank. These factors determine the degree of operating risk or the quality of the operating earning flows of the banks.

A panorama of UCBLSponsored by some dynamic and reputed entrepreneurs and eminent industrialists of the country and also participated by the Government, UCBL started its operation in mid 1983 and has since been able to establish the largest network of 80 branches as on 31. 08. 2001 among the first generation banks in the private sector.

With its firm commitment to the economic development of the country, the Bank has already made a distinct mark in the realm of Private Sector Banking through personalized services, innovative practices, dynamic approach and efficient Management. The Bank, aiming to play

a leading role in the economic activities of the country, is firmly engaged in the development of trade, commerce and industry through a creative credit policy.

The Bank closed the year under the recording steady growth. At the end of the year 2001,total assets of the bank stood at T.k1834.82million as against T.k1591.61million registering an increase of 15.26percent.

Total assets included Tk.2416.10 million cash in hand, reserve with Bangladesh Bank and Sonali Bank. Total liquid assets including investment registered an increase of 20.44 percent in the year under review. Total liquid assets including investment stood at Tk.6609.36 million during the year of against Tk.5487.72million in the previous year.

UCBL product and services

Major services

Other services

Management

Mr. Muhammad Sajid-ul-Ha, Managing Director, successfully leads the Management team of the Bank. He is a renowned and dynamic banker with more than three decades of banking

One Stop Service

Time Deposit Scheme

Monthly Savings Scheme

Deposit Insurance Scheme

Inward & Outward Remittances

Travelers Cheques

Import Finance

Working Capital Finance

Loan Syndication Underwriting and Bridge Financing

Trade Finance

Credit Scheme

Locker Service Foreign Currency Deposit A/C

NFCD (Non Resident Foreign Currency Deposit Account)

experience to his credit Prominent and dynamic banker Mr.Hamidul Huq, is the additional Managing Director of the Bank. Mr. Md.Salauddin Gazi and Mr.Bakhtiar HossainChowdhary are the Deputy Managing Directors of the Bank. The Management is ably supported and assisted by qualified executive and officers.

Capital and Reserve

During the year under report authorized capital of the Bank remained unchanged at Tk.1000.00million and the paid-up capital stood at Tk.230.16million.The reserve fund of the Bank increased by 12.82 percent to Tk. 393.50 million as against Tk.348.78 million in the previous year.

Human ResourcesImbibed with the spirit of building a creative work force, UCB puts in utmost endeavor to take over the challenges of modern banking. Since there is no alternative to training for acquiring the required efficiency and professional excellence, Bank’s Training Institute was throughout the year to impart

training on different aspects of Banking. During 2001, five-in-house training courses were arranged in which ninety officers took part. Moreover a number of executive and officers were sent to Bangladesh Institute of Bank Management (BIBM) and other training agencies. Employee’s performances are regularly evaluated and a good number of them have been promoted as reward and recognition of their good performance. At the end of 2001total number of employees stood at 1828comprising 75 executives, 1061offers and 676 staff.

DepositsThe Deposit of the Bank registered an increased Tk. 15.00 percent in the year under review. At the close of 2001,total deposits stood at Tk.14245.87 million as against Tk.12387.47 million in the previous year. The deposit mix comprised Tk.4258.09million as demand and Tk.9987.78 million as time deposit. The ratio between demand and time liability was 29.89:70.11. out of the total deposits, Tk.12424.58 million was mobilized from the private sector while the balance Tk.1821.29 million from the public sector. Average deposit per branch was Tk.180.33 million in 2001.

Credit

The Bank continued its participation in different credit programmers for financing new industrial projects, working capital, trade finance, international trade etc. Consequently net credit rose to Tk.10941.98million in 2001 from Tk.119.54 million of 2000.Average advance per branch increased to Tk.138.51 million from Tk.9443.87 million of 2000.The credit deposit ratio stood at 0.77:1. Sector wise net advances during the year were as follows:

Sector Tk. In Million

1. Continuous Loan 6873.65

2. Demand Loan 749.64

3. Term Loan (unto 5 years) 1890.10

4. Term Loan (over 5 years) 1323.28

5. Staff Loan 105.31

Total amount of loan 10941.98

Investment

At the close of 2001, total investment of the Bank stood at Tk. 2162.92 million in 2001.However, divided amounting to Tk.0.51 million has been received from different companies/institutions against investment in shares during the year under report.

Foreign Trade

During the year 2001, the Bank opened 8761 letters of credit for important worth Tk.13132.90 million compared to 9583 letters of credit worth Tk. 12534.40 million in 2000.The volume of export bill handed by the Bank wasTk.5309.30 million in 2001.

InspectionExperienced officials regularly audit and inspect the activities of the Bank throughout the year. During 2001audit and inspection were carried out .Bangladesh Bank Inspection Team also conducted inspection of 25 branches during the year under review. Moreover, they inspected Bank’s activities relating to foreign exchange at Head office and 17A.D branches authorized to deal directly in foreign exchange transactions.

Some ratio to judge bank’s current condition

Net Interest Margin (NIM)

A number of other profit measures are commonly used in banking, which provides further insight into a bank’s financial performance. One of them the most important is NIM that is Net interest Margin, which measure how effectively a corporation utilizes its earning assets in relation to the interest cost of funding.

NIM (%) = (Total interest income – Total interest expense) / Average Earning assets

YEAR Total interest income

Total interest expenses

Average Earning Assets

NIM (%)

1998 258523095 237324232 3820029159 .551999 468671807 377744520 6665118388 1.362000 1020392051 691594670 12986669244 2.532001 1528678923 1168952993 17243093906 2.09

Provision for Loan Losses (PLL) Each bank provides an estimation of future loan losses as an expense on its income statement. This expense can be related to the volume of loan as follows:

PLL (%) = Provision for loan losses /Total loan & Leases 100

Dollar gap ratio (%) = {(Interest rate sensitive assets - Interest rate sensitive liabilities)/ Total assets} 100

YEAR PROVISION FOR LOANS & LOSSES

TOTAL LOANS&LEASES

PLR (%)

1999 24731000 2283648484 1.082000 51323000 4588087640 1.122001 166854000 8044426040 2.072002 298730000 9391643297 3.18

Loan Ratio

The loan ratio indicates the extent to which assets are devoted to loan as opposed to other assets, including cash, securities and plant & equipment.

YEAR NET LOANS TOTAL ASSETS LOAN RATIO (%)

1999 2283648484 4000810543 57.082000 4588087640 6966336681 65.862001 8044426040 13463230033 59.752002 9391643297 17865667543 52.57

INTEREST SENSITIVITY

Interest sensitivity is the responsiveness of liquidity costs and asset returns to changes in the interest rates. The difference between the quantities of interest sensitive assets and liabilities is known as Dollar gap ratio. The gap ratio suggests that bank’s profitability will be affected by the change in the interest rate. Here rate sensitive is defined as short-term assets and liabilities with maturity period of less than one year.

YEAR 1999 2000 2001 2002 Gap Ratio (%) 0.69 -0.89 -6.06 -9.41

Notes: Interest rate sensitive assets are the sum of balances with other banks and financial

institution, Loans & advances, Investment at cost. Interest rate sensitive liabilities are the sum of borrowing from other banks and financial

institutions and deposit and other accounts.

Loan ratio (%) = Net Loan / Assets 100

Credit Risk Management: Theoretical Aspect

Measurement of Credit Risk

To calibrate the default risk exposure of its credit and investment decisions as well as to assess its credit risk exposure in off-balance-sheet contractual arrangements such as loan commitments, a Financial Institutions manager needs to measure the probability of borrower default. The ability to do this largely depends on the amount of information the Financial Institutions has about the borrower. At the retail level, much of the information needs to be collected internally or purchased from external credit agencies such as American Management Systems. At the wholesale level, these information sources are bolstered by publicly available information such as certified accounting statements, stock and bond prices, and analysts’ reports.

Default Risk Models

Economists, bankers, and analysts have employed many different models to assess the default risk on loans and bonds. These very from the relatively qualitative to the highly quantitative. Further, these models are not mutually exclusive, in that a Financial Institutions manager may use more than one to reach a credit pricing or loan quantity rationing decisions. We analyze a number of these models.

Qualitative models

In the absence of publicly available information on the quality of borrowers, the Financial Institutions manager has to assemble information from private sources – such as credit and deposit files – and /or purchase such information from external sources – such as credit rating agencies.

Credit Risk Models

Qualitative Models Credit Scoring Model

Borrower’s specific factors

Market Specific factors

Reputation Leverage Volatility of earnings Collateral

The business cycle The level of interest rate

Linear Probability model

Logit model Probit model Linear discriminate

model

In general, the amount of information assembled varies with the size of the potential debt exposure and the costs of collection. However, a number of key factors enter into the credit decision. These include:

(1) Borrower – specific factors that are idiosyncratic to the individual borrower(2) Market – specific factors that have an impact on all borrowers at the time of the

credit decisionBorrower Specific Factors

Reputation

The borrower’s reputation involves the borrowing – lending history of the credit applicant. If, over time, the borrower has established a reputation for prompt and timely repayment, this enhances the applicant’s attractiveness to the Financial Institutions. A long-term customer relationship between a borrower and lender forms an implicit contract regarding borrowing and repayment that extends the formal explicit legal contract on which borrower – lender relationships based.

Leverage

A borrower’s leverage or capital structure – the ratio of debt to equity – affects the probability of its default. This is because large amounts of debt, such as bonds and loans, increase the borrower’s interest charges and pose a significant claim on its cash flows. As shown in the figure, the relatively low debt – equity ratios may not significantly impact the probability of debt repayment. Yet, beyond some point, the risk of bankruptcy increases, as done the probability of some loss of interest or principal for the lender.

Volatility of Earnings

As with leverage, a highly volatile earnings stream increases the probability that the borrower cannot meet fixed interest and principle charges for any given capital structure. Consequently, newer firms, or firms in high – tech industries with a high earnings variance over time, are less attractive credit risks than those with long and more stable earnings histories. Probability Of default

0 D / E* Leverage(Debt – Equity ratio)Collateral

As discussed earlier, a key future in any lending and long – pricing decision is the degree of collateral or assets backing the security of the loan. Many loans and bonds are backed by specific assets should a borrower default on repayment obligations. Mortgage bonds give the bondholder first claim to some specific piece of property of the borrower, normal machinery or buildings, debentures give a bondholder a more general and more risky claim to the borrower’s assets.

Market Specific Factor

The Business Cycle

The position of the economy in the business cycle phase is enormously important to a Financial Institutions in assessing the probability of borrower default. For example, during recessions, firms in the consumer durable goods sector that produce autos, refrigerators, or houses do relatively badly compared to those in the non-durable goods sector producing tobacco and foods.The Level of Interest Rates

High interest rates indicate restrictive monetary policy actions by the Federal Reserve. Financial Institutions not only find funds to finance their lending decisions scarcer and more expensive but also must recognize that high interest rates are correlated with higher credit risk in general. So far, we have delineated just a few of the qualitative borrower and economy – specific factors an Financial Institutions manager may take into account in deciding on the probability of default on any long or bond. Rather than letting such factors enter into the decision process in a purely subjective fashion, the Financial Institutions manager may weight these factors in a more objective or quantitative manner.

Credit Scoring Models

Credit scoring models use data on observed borrower characteristics either to calculate the probability of default or to sort borrowers into different default risk classes. By selecting and combining different economic and financial borrower characteristics, an FI manager may be able to: 01. Numerically establish factor, which is important explaining default risk. 02. Evaluate the relative degree or importance of these factors. 03. Improve the pricing of default risk. 04. Be better able to screen out bad loan applicants. 05. Be in a better position to calculate any reserves needed to meet expected future loan

losses.

Credit scoring models include these four broad types:

Linear probability models.

Logit model.

Probit models.

Linear discriminant

analysis

Next we take a brief look at each of these models and their major strengths and weaknessesLinear Probability ModelThe linear probability model uses past data, such as accounting ratios, as inputs into a model to explain repayment experience on old loans.Briefly, we divide old loans ( i ) into two observational groups, those that defaulted (Zi = 1) and those that did not default (Zi = 0). We estimate the model by linear regression of this form:

Where j is the estimated importance of the j ith variable (leverage) in explaining past repayment experience.

E (Zi)

0

While this technique is straight forward as long as current information on the X ij is available for the borrower, its major weakness is that the estimated probabilities of default can often lie outside the interval 0 to 1.

The Logit Model

The logit model constrains the cumulative probability of default on a loan to lie between 0 and 1 and assumes the probability of default to be logistically distributed according to the functional form: 1 F(Zi) = 1 + e-z

Cumulative probability of default

1

Zi

Logistic Function

Zi = jXij + error

Where e stands for exponential, F(Zi) is the cumulative probability of default on the loan, and Zi is estimated by regression in a similar fashion to the linear probability model. Basically, we can estimate a projected value for Zi for a prospective borrower from a regression model I the same fashion as the linear probability model.

The Probit Model

The Probit model also constrains the projected probability of default to lie between 0 and 1, but differs from the logit model in assuming that the probability of default has a (cumulative) normal distribution rather than the logistic function.

Linear Discriminant Models

While linear probability, logit models, and probit models all estimate or project a value for the expected probability of default, should a loan be made, discriminant models divide borrowers into high or low default risk classes contingent on their observed characteristics (Xj).

Altman’s discriminant function takes the form: Where, X1 = Working capital / total asset ratio

X2 = Retained earnings / total asset ratio X3 = Earnings before interest and tax / total asset ratio X4 = Market value of equity / book value of long-term debt ratio X5 = Sales / total assets ratio

The higher the value of Z, the lower the default risk classification of the borrower. Thus, low r negative values of Z may be evidence of the borrower being a member of a relatively high default risk class.Suppose that the financial ratios of a potential borrowing firm took the following values

X1 = .2

X2 = 0 X3 = -.20 X4 = .10 X5 = 2.0

The ratio X2 is zero and X3 is negative, indicating that the firm has had negative earnings or losses in recent periods. Also, X4 indicates the borrower is highly leveraged. However, the working capital ratio (X1) and the sales by asset ratio (X5) indicate the firm is reasonably liquid and is maintaining its sales volume. The Z score provide an overall score and indicator of the borrower’s credit risk since it combines and weights these five factors accordingly to their past importance in explaining borrower default. For the borrower in question: Z = 1.2(.2) + 1.4(0) + 3.3(-.20) + .06(.10) + 1.0(2.0)

Z = 1.2X1 + 1.4X2 + 3.3X3 + 0.6X4 + 1.0X5

Z = 0.24 + 0 - .66 + 0.06 + 2.0 Z = 1.64

According to Altman’s credit scoring model, any firm with a Z score of less than 1.81 should be placed in the high default risk region. Thus the FI should not make a loan to this borrower until it improves its earnings.

Term Structure derivation of Credit Risk

One market – based method of assessing credit risk exposure and default probability is to analyze the risk premiums inherent in the current structure of yields on corporate debt or loans to similar risk – rated borrowers. Rating agencies categorize corporate bond issuers into seven major classes according to perceived credit quality. The first four quality ratings is AAA, AA, A and BBB. Which is indicating investment quality borrowers. The rest three-quality rating is BB, B and CCC. These three classes are known as high – yield or junk bonds. Different quality ratings are reflected in the degree to which corporate bond yields exceed those implied by the Treasury (credit risk – free) yield curve.

Treasury Strips and Zero – coupon Corporate Bonds

Bonds that are created or issued bearing no coupons and only a face value to be paid on maturity. Treasury strips and zero – coupon corporate are single – payment discount bonds, it may be possible to extract required credit risk premium and implied probabilities of default from actual market data on interest rates. That is, the spreads between risk – free deep – discount bonds issued by the Treasury and deep – discount bonds issued by corporate borrowers of differing quality may reflect perceived credit risk exposure of corporate borrowers for single payments at different times in the future.

Probability of Default on a One – Period Debt Instrument

Assume that the FI requires an expected return on a one – year corporate debt security at least equal to the risk – free return on Treasury bonds of one year’s maturity.

Let p be the probability that the corporate debt, both principal and interest will be repaid in full, therefore 1 – p is the probability of default. By denoting the promised return on the one – year corporate security as 1 + k and on the credit risk – free Treasury security as 1 + i, the FI manager would just be indifferent between corporate and Treasury security when:

p (1 + k) = 1 + i

The FI manager would set the expected return on the loan to equal the risk – free rate in the following manner:

y (1 + k) (1 – p) + p (1 + k) = 1 + i

The new term here is y (1 + k) (1 – p) this is the payoff the FI expects to get if the borrower defaults.As might be expected, if the loan has collateral backing such that y0, the required risk premium on the loan would be less for any given default risk probability (1 – p). Collateral requirements are a method of controlling default risk, they act as a direct substitute for risk

premiums is setting required loan rates. To see this solve for the risk premium and between k and i.

k – i = = (1 + i) / (y + p – py) – (1 + i)

Probability of Default on a Multi period Debt Instrument

In this analysis to derive the credit risk or default probabilities occurring in the market for longer – term loans or bonds. For the simple one – period loan or bond, the probability of default (1 – p) was,

1 – p = 1 - 1 + i / 1 + k

Suppose that the FI managers wanted to find out the probability of default on a two – year bond. To do this, the manager must estimate the probability that the bond would default in the second year conditional on the probability that it does not default in the first year. The probability that a bond would default in any one year is clearly conditional on the fact that the default hasn’t occurred earlier.

Managerial Default Probability

The probability that a borrower will default in any given year. The probability that a bond would default in any one year is marginal default probability for that year.

Cumulative Default Probability

The probability that a borrower will default over a specific multiyear period. Yield curves are rising for both Treasury issues and corporate issues. We want to extract from these yield curves the market’s expectations of the multi period default rates for corporate borrowers classified in the grade B rating class.

No Arbitrage and Forward Rate

The condition of no arbitrage by investors requires that the return on buying and holding the two – year Treasury discount bond to maturity should just equal the expected return from investing in the current one – year discount T – bonds at the end of the first year at the expected one – year forward rate.

(1 + i2)² = (1 + i ) (1 + f )

Mortality Rate Models:

Financial Institutions managers analyze the historic or past default risk experience, the mortality rates, of bonds and loans of a similar quality.

If p1 is the probability of a grade B bond or loan surviving the first year of its issue; thus 1- p 1

is the marginal mortality rate or the probability of the bond or loan dying or defaulting in the first year of the issue.

If p2 is the probability of a grade B bond or loan surviving the first year of its issue; thus 1- p 2

is the marginal mortality rate or the probability of the bond of loan dying or defaulting in the second year of the issue.

Thus, for each grade of corporate borrower quality, a marginal mortality rate (MMR) curve can show the historical default rate experience of bond sin any specific quality class in each year after issue on the bond or loan.

The above figure shows that as grade B bonds age, their probability of dying in each successive year increases. In reality, any shape to the mortality curve is possible. It is possible that MMRs can be flat, decline over time, or show a more complex functional form. These marginal mortality rates can be estimated from actual data on bond and loan defaults. Specially, for grade B quality bonds.

Marginal Mortality Rates:

MMR1 = (Value Grade B default in year 1) (Value Grade B outstanding in year 1)

MMR2 = (Value Grade B default in year 2) (Value Grade B outstanding in year 2)

Cumulative Mortality Rate

The probability of a bond or loan dying (defaulting) over a given multiyear period.

Limitations of the Mortality Model:

It produces historic or backward looking measures. Future default probabilities ten to be highly sensitive to the period over which the FI

managers calculate the MMRs. The estimates tend to be sensitive to the number of issues and the relative size of

issues in each investment grade.

MarginalMortality Rate

0 1 2 3 4 Year since Issue

RAROC Models

A popular model to evaluate credit risk based on market data is the RAROC model. RAROC- risk adjusted return on capital- was pioneered by Bankers Trust and has now been adopted by virtually all the large banks.

Under the RAROC model, the actual or promised annual cash flow on a loan (such as net interest and fees) is compared with the loan’s risk.

RAROC = one-year income on loan Loan (asset) risk or Risk capital (ΔL)

A loan is approved only if sufficiently high relative to a benchmark cost of capital for the bank. Alternatively, if the RAROC on an existing loan falls below a bank’s RAROC benchmark, the lending officer should seek to adjust the loan’s terms to make it profitable.

ΔL = Dollar capital risk exposure or loss amount -DL = Duration of the loanL = Risk amount or loan sizeΔR = is an estimate of the worst change in credit risk premiums for the loan class over the past year.

The ΔR in RAROC equation equals:

ΔR= Max. [Δ (Ri – RG) > O]

Where, Δ (Ri – RG) is the change in the yield spread between corporate bonds of credit rating class i (Ri) and matched duration treasury bonds (RG) over the last year.

In order to consider only the worst-case scenario, the maximum change in yield spread in chosen, as opposed to the average change.

Option Models

Employ option-pricing methods to evaluate the option to default. Used by many of the largest banks to monitor credit risk. KMV Corporation markets this model quite widely.

Theoretical Framework:

Following the pioneering work of Merton, Black and Scholes an others, it is now recognized that firms, which raise funds either by issuing bonds or increasing its bank loans, hold a very valuable default or repayment option.

ΔL= -DL X LX (ΔR/1+R)

That is, if a borrower’s investment projects fail, it has the option of defaulting on its debt repayment and turning any remaining assets over to the debt holder.

On the other hand, if things go well, the borrower can keep most of the upside returns on asset investments after the promised principal and interest on the debt have been paid.

Applying Option Valuation Model

Merton has shown that in the context of the preceding options framework, it is quite straightforward to express the marker value of a risky loan made by a lender to a borrower.

Theoretically, this model is an elegant tool for extracting premiums and default probabilities; it also had important conceptual implications regarding which variables to focus on in credit risk evaluation.

Limitations:

The assumption- continuously traded claim on the assets of the borrower- is difficult to accept in many cases.

The value of option-based premiums is extremely sensitive to errors made in measuring.

Lending Risk Analysis - UCBL

The credit quality of many Financial Institutions’ (FI’s) lending and investment decisions is always a great deal of attention. In the 1980s, there were tremendous problems with bank loans to less developed countries as well as thrift and bank residential and farm mortgage loans. Many banks as well as financial institutions in our country also suffer from this credit quality problem. Basically this type of problems would be faced by the financial organizations if they failed to measure the credit risk of the customers accurately. Its natural all banks and FI would use a standard format of performence evaluation of the customers for their loan screening process. But inspite of this, the planning, timing, decision making and application procedure might bring different result.

Our main target of this report is to evaluate the credit risk as well as lending risk analysis of a publicly owned financial institution. As mentioned earlier, in this regard we have selected UCBL (United Commercial Bank Limited) to evaluate their lending risk analysis so that we might get a practical dilemma from theoretical point of view.

Basically this chapter will contain the details procedure of lending risk analysis of UCBL. To make it understandable and clear the standard format, which is frequently used to measure and to assess the risk for different perspective, are attached here. Then its explanation and practical courses of actions have also been mentioned. It would help us to sketch the real condition of credit risk measurement of financial institutions.

Lending risk analysis form Company name:Address:

Industry name:

Code:

Group name (if company is a part of group) Organizing Branch/ office

Current exposure Nature of land Amount To this customer

Current exposure (total) to this group

Taka ………………

Application for Increase to New facility existing facility

Why this analysis conducted

Renewal of DelinquentExisting facility customer

Risk category Good Acceptable Marginable Poor

Business

Security

Overall

Type of facility sought Amount

Purpose Type of facility recommended Type Amount

Loan category Voluntarily given By the bank

Part of Government Scheme ………………………… (Name of scheme) Directed by Individual ………………... ....................................................... (Name of person directing the loan)

Level of approval required

Date customer made request

Date analysisCompleted

Originating officerRecommendationAccept Decline Amount

Date recommendation made

Recommendation officer(s)

Decision Date decision made

Approving officer Accept Decline Amount

Officer authorizing disbursement

Date disbursementAuthorized

Date loanDisbursed

According to LRA form we find that at first it is mandatory to mention the customer’s (company’s) name, address, belonging industry, current exposure of land as well as fixed assets. Then we have to select the risk category of business and security. It shows a preliminary screening of the customer’s risk class. Loan category and level of requirement is also consistent here. Loan approving and originating officer has a great responsibility and commitment here. So it is also mentioned here with the disbursement date and recommendation. No doubt this form carries a great important for credit quality evaluation, subjective judgments be exercised cautiously to make it more accurate and qualitative one.

Lending risk When you have completed pages 3 to 15 of the loan analysis form, copy your answers to the questions into the grid below. Then write the score corresponding to the answers in the rightmost column and total all the scores.

Lending Risk Risk level Low Average High excursive

Score

Business Risk

Supplies riskWhat is the risk of failure due to description in the supply of inputs?

Score 1.5 5 4.5 12

3.3

Industry Risk

Sales riskWhat is the risk of failure due to description in the supply of inputs?

Score 1.5 5 4.5 12

1.53

Company Risk Performance risk

What is the risk that the Company’s position is so weak that it cannot perform well enough to repay the loan, given expected external conditions?

Score 1.5 5 4.5 12

1.2

Company Position Resilience risk 2.4

Risk What is the risk of failure due to lack of resilience to unexpected external conditions?

Score 1.5 5 4.5 12

Management Risk

Management competence risks What is the risk of failure due to lack of management competence?

Score 1.5 5 4.5 12

3.3

Management Integrity risks What is the risk of failure due to lack of management Integrity?

Score 1.5 5 4.5 12

6.3

Total business risk score 18Security control risk What is the risk that the bank fails to realize the security?

Score 1.5 5 4.5 12

10

Security Risk

Security cover risks What is the risk that the realized security value is less than the exposure?

Score 1.5 5 4.5 12

15

Total security risk score 20

Good risk Acceptable Risk

Marginable Risk

Poor Risk

Business Risk 13.19 20.26

27.34 Over 34

1 1 1 1

Good risk Acceptable Risk

Marginable Risk

Poor Risk

Security (.201)

(.15) (.14.0) .0 1-10 Over 10

Select Overall Risk from Matrix

1 2 3 4A A A AB B B BC C C CD D D D

GOOD ACCEPTABLE MARGINAL POOR

Loans/01/14

After getting the preliminary information based on the lending risk analysis form, it is needed to evaluate risks in specific sector. Business risk is very much important here. It includes industry risk as well as company risk. While analyzing industry risk, supplier’s risk is considered as the risk of failure due to disruption in the supply of inputs. The risk of failure due to disruption to sales is also an important factor. Company risk includes company position risk and management risk. Under company risk performance evaluation covers mostly positioning the company whether it is so weak that it cannot perform well enough to repay the loan, given expected external conditions. The risk of failure due to lack of resilience to unexpected condition should also be considered. While evaluating management risk, management compensation risk and management integrity risk is determined on subjective judgments.Security control risk and security cover risk would be faced when the bank fails to realize the security. After analyzing these factors, scoring is done to get a complete figure of risk assessmentAccording to our hypothetical analysis we found that total business risk score is 18, total security risk score is 20. Lastly the overall risk from matrix shows marginal position of the customer.

Supplies risk Cost item %

Of total costs

What is the risk of disruption?Better than Average Worse average

Comments

Labor

Raw materials

Equipment

Power

Premises

Other

Number of days production lost is past 12 months due to strikes? ………………….

Independent power supply Dependent power supplyPower supply

Explain any significant risks of disruption to production

Low Average High Excessive What is the risk of failure due to disruption in the Supply of input?

The risk from supplier’s point of view is a very important factor in case of lending risk analysis. Suppliers risk means the risk of failure due to disruption in the supply of inputs. These inputs include raw materials, equipment power, premises and others. What is the contribution of these items in total cost i.e. the percentage of total cost? Then risk measurement is ranked in any of three categories consisting of better than average, average and worse than average. Then the comments on these ranking fulfils the risk assessment in this regard.

Sales risk

Industry growth

Give industry size figures for the latest 3 years that are available.

YearEstimated total industry turnover

Strong weak no small large growth growth change decline decline

Over the next few years, what is the most likely trend in industry turnover?

Support your answer:

Competitive pressure: Obtain performance data for two major competitorsMajor competitor I …………………………… Market share. ………………% (Name)Performance Year

TurnoverProfit

Less about the faster Fast same

This competitor is growing than our customer.What prevents customers from switching to this competitor?

Major competitor II ……………………………… Market share. ………………% (name)Performance Year

TurnoverProfit

Less about the faster

Fast same

This competitor is growing than our customer.What prevents customers from switching to this competitor?

Sales are the main earning generating power of a company. Not only as the main source of cash generation but also as an important factor for customer screening process sales risk must be measured. So sales risk measurement is the most crucial part of lending risk analysis.

Sales risk (continued)

Barriers to entryDifficult Average Easy

How easy is it for new competitors to enter this industry?

What barriers prevent new competitors from entering this industry?

Regulatory changes Low Average High

What is the risk that changes in regulations will damage sales?

Explain your answer.

Customer concentration: List 5 largest customers

Customer name % of total sales

What is the risk that a single customer representing a significant proportion of sales, switches to a competitor?

Low Average High

Explain your answer.

What is the risk of failure due to disruption to sales?

Low Average High Excessive

Sales risk in some extent depends on industry growth. If the industry is in the initial stage then the growth of sales will continue to grow. But if the industry is in a mature position then the growth might be in a stable position but not grow at an increasing rate. On the other hand at the declining stage of the industry sales growth will be obviously low. So to analyze the customer firm for giving any loan, it is required to compare the firm with the position of the industry. Here only historical analysis of the industry is not enough, as we also have to focus the future trend of the industry’s growth. Then logical and descriptive support of our assumption will strengthen our analysis.

Firm’s risk assessment also depends on the competitive pressure of the industry. So to sketch its competitive pressure we have to select two major competitors with our target firm. In this

type of competitive analysis we have to keep in mind about their market share, turn over, year to year profit as well as growth. Is there any barrier to entry in this industry or to what extent the regulatory body would adversely affect the sales are also crucial aspect to analyze sales risk. Then customer concentration portion of the firm’s largest customer will show the percentage or dependency of the firm on specific customer. Lastly after evaluating all these factors about sales risk we have to rank the risk of failure due to disruption to sales in any of four categories: low, average, high and excessive.

Performance risk

Recent performance history Yes NoAre financial spreadsheets attached?

Give most recent 3 years performance data

YearSalesCapitalprofits

Explain the significance of any important trends you notice in the performance data.

Competitive positionWhat is the company’s returns (in terms of turnover)? …………………

Compare figures with other companies in the industry (and/or with industry averages, and explain the significance of any important differences you notice.

What are the strengths and weaknesses of this company, in comparison to its competitors?Strengths Weaknesses

Performance risk (continued)

StrategyHow does the company differentiate itself from its competitors?

Quality Price

Better than competitors

Indistinguishable from competitors

Worse than competitors

Cheaper than competitors

About the same as competitors

More expensive than competitors

What strategy will this company adopt to exploit its strengths and overcome its weaknesses?

Biplecontidence in strategy

Average low confidence in strategy

How confident are you that this strategy will word?

Cash flow forecasts

Do the cash flow forecasts indicate that the company will generate sufficient cash to repay its loans?

Significantly more than enough cash

Enough cash Not enough cash

How confident are you that the company will perform as forecast in the cash flows?

High confidence

Average Low confidence

Explain your answer

What is the risk that the company’s position is so weak that it cannot perform well enough to repay the loan, given expected external conditions?


(tick one box)

Loans/01/004 June 93

Performance risk analysis contains recent performance history of the customer firm and the financial condition of the firm in terms of sales, capital and profit. Then it allows the assessment a brief description of the competitive analysis. Basically is shows the main strengths and weakness of the customer in comparison with its main competitors. Then performance risk analysis continues to describe the strategy and the cash flow forecast of the firm. We have to find out the specialty and uniqueness of the firm in contrast with the competitions. That means we have to judge the quality of the production or services, pricing policy of the firm. Then the degree of confidence is also mentioned here to support our answer.Then cash flow analysis basically depends on the cash flow forecasts of the firm and we have to evaluate whether the firm is quite able or would generate enough cash funds to repay the loan. If the firm is quite competent and efficient to generate enough cash flow to repay the loan then the confidence of our judgments would also be mentioned with explanation. Lastly we have to comment about the risk that the company’s position is so weak that it cannot perform well

enough to repay the loan, given expected external conditions. That means we would analyze not only the good situation but also the worst case scenario.

Resilience risk

Leverage Company leverage

Values reported by company

Bank’s assessment

Exposure to other banks

Assets Bank ExposureLiabilitiesEquity (= Assets – liabilities)Leverage (= Liabilities/ equity)

Total exposure to other banks

Is the current balance on any account above sanctioned limits? No Yes

Are any interest or principal payments more that 30 days late? No Yes

If you answered yes to either question, give details.

Does the credit burcan report indicate any problems? No Yes

If you answered yes to the previous question, explain.

How reality do you expect shareholders to support this company in the future if the need arises?

Very readily

will support reluctantly

may not support further

Explain your answer

How resilient is the company to bankruptcy?

Highly resilient Average Not at all resilient

Liquidity

Explain the significance of any important trends shown by the ratio analysis.Loans/01/006 June 93What proportion costs is fixed? ..............................................

Very easily Average With difficulty

How easily will this company be able to reduce costs if sales fall?Explain your answer.How resilient is the company to liquidity (which may cause repayment failure)?

Highly resilient

Average Not at all resilient

Connections

Do the owners or managers have any connections/ affiliations, which may benefit or damage the company?

How resilient is the company to the adverse effects of political changes?

Highly resilient

Average Not at all resilient

Resilience riskW** assessments of resilience to bankruptcy, liquidity the adverse effects of political changes, from above.

Highly resilient (low risk)

Average Not at all resilient (high risk)

Resilient is the company to bankruptcy? Resilient is the company to liquidity? Resilient is the company to the adverse test political changes?

** Assessment of resilience to bankruptcy, liquidity and the effects of political changes, to answer the following question:

Low Average High ExcessiveAt is the risk of failure due to lack of resilience unexpected external conditions?

(Tick on box) Loans/01/008 June 93

Resilience risks basically cover the riskiness of the company’s leverage. We know higher the leverage i.e. higher the portion of the debt in the capital structure, higher the risk. It’s natural that if a firm possesses a higher leverage portion then the financial risk will be high and in a high financial risky position the firm’s ability to pay debt obligation decreases. So bank or financial institution must have to consider the debt portion of the financial structure.

Here, at one side bank has to exercise its own assessment about the customer firm’s assets, liability and leverage portion, so also at the same time other banks exposure is also important here. Credit Rating Company frequently gives this type of assessments about firms. So bank should also use this credit bureau’s rating. If there is any problem in rating this should be explained. Then financial institutions must have to consider from the shareholder’s point of view.Liquidity is also a very important factor while analyzing resilience risk. Because accurate liquidity position determination is too much difficult. If a firm has excess liquidity it might decreases the profitability. On the other hand, less liquid firm will not be able to satisfy its obligation. Quick ratio as well as current ratio is to be considered here. A company should have the ability to reduce its costs if sales fall. Because if sales fall then it will obviously decrease profit margin. So here firm must have to cut cost. While analyzing credit quality, bank also has to consider it.

Management ability

List all owners holding more than 20% of equity List board membersName Share holding (%)

What is your assessment of the ability of these people to ensure that this company succeeds?

Better than average

Average Worse than average

Give reasons for your assessment.

Who is the primary decision maker on financial issues? ..........................................................................................................(Name)Is this person’s biodata attaclied? Yes No

What is your assessment of this person’s ability to manage the tenancies of this company?

Better than average


Who is the primary decision maker on financial issues? ..........................................................................................................(Name)Is this person’s biodata attaclied? Yes No

What is your assessment of this person’s ability to manage the operations of this company? Give reasons for your assessment.

Better than average


Comment on strengths and weaknesses of any other key personnelName Responsibility Strength Weakness

What is the risk that the business fails due to lack of management ability?


(Tick on box)Loans/01/008 June 93

Management efficiency plays a very important role in credit rating measurements. Basically here board member’s list and the portion of equity holding s crucially analyzed. Then on the basis of collecting information and subjective judgments the assessment of the liability of these people to ensure that company’s success should be mentioned with the logical support and argument. Ranking would male thing easier and appropriate to manage the management risk. Not only the board members but also the executives, decisions makers and the responsible managements would be evaluated on the basis of their activities, performance and attached biodata. Then comment is required about the ability of the person to manage the core activities of the firm. Financial institutions also have to evaluate the key personnel’s of the loan taking firm when it attempts to measure its credit risk. Here all the strengths, responsibility as well as weakness of these key personnel are to be examined. It would obviously reflect the contribution of the managements of the firm.

Customer site visit report form

Basically bank collects creditors information in many ways. It could collects information from their internal sources as well as from the credit rating institutions. But collecting information in this way is not enough to evaluate the measurement of risk, as all these sources are secondary as well. So here bank has to visit the customer-firm directly to gather

Company Name Date of visit

Site visited Date of last visit

People visited Bank officers making visit

Total facilities Current outstandingVisit objective and data to be collected

(To be completed before visit)

Result

Follow up and notion steps

Any risk components rated high or excessive should be addressed with management and the

Results noted above.

information and to observe the actual condition of the firm. Visit date and detailed are to be explained by the institutions. Total facilities and outstanding conditions also observed here. From the report of the credit rating firm, if there is any risk component that is abnormally high or excessive must be addressed with management and the result is noted here.Security covered risk

Expected security cover strength

Primary security

Collateral Other security

Total

a) Types of securityb) Expected realizable value at liquidationc) Expected time taken to liquidated this securityd) Discount rate % (One year fixed deposit rate)e) Discount factor % = 100 * 1/ (1 + d / 100) ^ef) Present value of security (= b * e/100)g) Current exposure (Principal + Interest)h) Security cover % (= 100 * f/g)

Loan taking firm must have to set some security or collateral against the loan. It is the security of the firm, if the customer fails to repay the loan. Here the probability of default is depends on the credit risk management and also on the collateral valuation. Here bank has to analyze how liquid the security is and whether it would loss any of its value when it would be liquidated. Basically securities are of various types. But whatever the nature of the security i.e. primary security, collateral or other security, it is required to examine the expected security cover strength.

Default Risk Analysis

As mentioned earlier there are various models to measure default risk. These models are not mutually exclusive. A bank or any financial institution can apply any of these default risk model or more than one model. But whatever be the number of application of the model, the main point is that how efficiently they are applying and measuring the variable used in these models.

Here, our target bank UCBL is basically applying “Z score” and “Y score” while analyzing default risk of customers. Already we have analyzed the implication of Z score to measure the credit risk in the previous chapter. In spite of it we will again focus on this scoring as for our analysis. To sketch a picture of this measurement, we would attempt to use an example of a customer. But for secrecy the name of the firm is not mentioned here. We know Z score is a credit rating as well as default risk rating measurement on the basis of some financial ratios of the loan taking firm. But giving specific weights Altman has averaged the ratios and now it is worldwide used to measure credit risk.

“Y Score “ is another used model by banks. Mainly in case of analyzing Y score, the basic ratios such as current ratio, quick ratio, liquidity ratio, asset ratio and ROI, are frequently used. As Z score indicates further investigation of the customer if the score is below 3, so also Y score suggests unusual degree of risk and security against loan if the Y score is under 12. Now before analyzing the Z Score, we will at first show the common size proforma of financial statement of the loan-taking firm used by the bank

Spreadsheet NAME TAKA ASSETS TYPE % DATE 1 CASH ON HAND 2 CASH IN BANK 3 SECURITIES (MARKETABLE) 4 RECEIVABLES TRADE 5 LESS: BAD DEBT ALLOWANCE 6 NET RECEIVABLES 7 INVENTORIES 8 ADVANCE 9 ALL OTHER CURRENT ASSETS 1 TO 3 + 6 TO 9 10 TOTAL CURRENT ASSETS 11 LAND &BUILDINGS 12 LESS: DEPRECIATION 13 NET LAND & BUILDINGS 14 MACHINERY & EQUIPMENT 15 LESS: DEPRECIATION 16 NET MACHINERY & EQUIPMENT 17 INVESTMENTS SUBSIDIARIES 18 INVESTMENTS ASSOCIATED CO.

19ALL OTHER NON CURRENT ASSETS

13 + 16 TO 20 20 TOTAL NON CURRENT ASSETS 10 + 21 21 TOTAL ASSETS 22 LIABILITIES 23 OVERDRFT / CASH CREDIT

24LOANS FROM BANKS (UNDER 1 YEAR)

25LOANS FROM OTHERS (UNDER 1 YEAR)

26 ACCOUNTS PAYABLE TRADE

27L.T.DEBT MATURING UNDER 1 YEAR

28 PROVISION FOR TAXES 29 ALL OTHER CURRENT

LIABILITIES24 TO 30 30 TOTAL CURRENT LIABILITIES 31 LONG TERM DEBT 32 ALL OTHER NON CURRENT LIABS

32 TO 34 33TOTAL NON CURRENT LIAILITIES

31 + 35 34 TOTAL LIABILITIES 35 CAPITAL + PAID IN SURPLUS 36 RESERVES 37 RETAINED EARNINGS 38 LESS: INTANGIBLES 37 TO 40 39 NET WORTH

36 + 41 40TOTAL LIABILITIES & NET WORTH

PROFIT & LOSS 43 SALES (NET)

44MATERIALS USED/GOODS PURCHASED

45 LABOUR 46 MANUFACTURING EXPENSES 47 DEPRECIATION 48 14 TO 48 49 COST OF GOODS SOLD 43 - 49 50 GROSS PROFIT 51 SELLING EXPENSES 52 GENERAL & ADMIN. EXPENSES 53 INTEREST 54 DEPRECIATION 51 TO 54 55 TOTAL OPERATING EXPENSES 50 - 55 56 OPERATING PROFIT 57 OTHER INCOME 58 OTHER EXPENSES (56 + 57) - 58 59 PROFIT BEFORE TAX 60 INCOME TAX 59 - 60 61 NET PROFIT AFTER TAX ANALYSIS DATE 101 CONTENGENT LIABILITIES 10 - 31 102 WORKING CAPITAL 103 DIVIDEND PAID CASH FLOW FROM OPERATING ACTIVITIES 61 104 NET EARNINGS 47 + 54 105 PLUS DEPRECIATION 103 106 MINUS DIVIDEND PAID

107 /- OTHER NON CASH ADJUSTMENT

Current year 108INCREASE/DECREASE IN INVENTORY

Minus prior 109INCREASE/DECREASE IN RECEIVABLES

110INCREASE/DECREASE IN PAYABLES

104+105+106 111INTERNALLY GENERATED CASH

107 TO 110 INCREASES (DECREASES) IN WORKING CAPITAL 112 CASH & CASH EQUIVALENTS 113 RECEIVABLES 114 INVENTORY 115 PAYABLES

116SHORT TERM LOANS AND LONG TERM

117 LOANS DUE WITHIN 12 MONTHS 118 NET TAXES PAID 119 OTHER CURRENT ASSETS 120 OTHER CURRENT LIABILITIES

121NET CHANGES IN WORKING CAPITAL

WORKING CAPITAL PROVIDED BY

(USED FOR) 122 NET CHANGES IN CAPITAL

123NET CHANGES IN P&L AND RESERVES

124NET CHANGE IN LONG TERM LOAN

125ACQUISITION/SALE OF PROPERTY

126ACQUISITION/SALE OF FIXED ASSETS

127 INV IN SUBS & ASSOCS 128 OTHER INVESTING ACTIVITIES 129 OTHER NON CURRENT ASSETS

130OTHER NON CURRENT LIABILITIES

131OTHER SOURCES AND USES OF FUND

RATIOS 10/31 132 CURRENT(10-7)/31 133 QUICK

365/(43/6) 134RECEIVABLES TURNOVER IN DAYS

365/(49/7) 135 INVENTORY TURNOVER IN DAYS

365/(43/27) 136ACCS. PAYABLE TURNOVER IN DAYS

43/102 137 SALES TO WORKING CAPITAL36/41 138 DEBT TO EQUITY

An Example of Default Risk Analysis (using Altman Z score)

Name of the firm: XYZ Manufacturing Corporation.Address: .....................................................

Selected Items of Balance SheetAt the Year Ended 31 December, 2002 (Tk in crore)

Net sales 2962.70Operating cost and Exp. 2291.80Other income 13.30Net income 411.80EPS 2.71Dividend per share 1.30Share Outstanding 155.00

Cash and M securities 303.80Current asset 1680.50Current liabilities 873.60Property and Equipment 1135.60Total asset 3155.10Long term obligation 49.40Share holder equity 2055.50

Selected Ratio of XYZ Manufacturing Corporation

Return on avg.asset (%) 13.6Return on Equity (%) 20.9WC/ Total asset ratio 25.57%Retained earning/Total Asset 6.93%EBIT/Total asset 16.31%MV Equity/BV debt 4.61Sales / Total asset 0.939

Calculation of Z score

Value or Ratio Weight Ratio*Weight

WC/ Total asset ratio (X1) 0.256 1.2 0.307

Ret. earning/Total Asset (X2) 0.069 1.4 0.097EBIT/Total asset (X3) 0.163 3.3 0.538MV Equity/BV debt (X4) 4.61 0.6 2.77Sales / Total asset (X5) 0.939 1.0 0.939

Total 4.647

As the Z Score is greater than 2.90, so the loan taking firm has no probability of default.Specific Sector wise Default Probability

UCBL sanctions loan in various sectors. Basically in this chapter, we will show the specific sector wise default probability. For this at first, we have to mention the interest rate on different sector. Mainly UCBL gives loan in agriculture sector, large and medium level industry, commercial sector, export, small and cottage industry etc. Here probability of default has been calculated on the basis of multi period model. Here, one thing is assumed for this calculation and that is the theoretical spot rate on treasury security. On the basis of this theoretical spot rate of treasury security forward rate has also been calculated. Thus we have calculated the cumulative probability of default on multi period model.

Interest Rate on different Sectors

Agriculture 10 %Large & medium level industry 14 %Export 7 %Other commercial loan 13.5 %Small and cottage industry 12 %Brick Financing 14 %Fertilizer dealer 14 %

Spot rate and Forward rate (assumption)

Treasury bill Spot rate = i 1 + i Forward rate = f 1+fi1year 0.060 1.060 0.060 1.0602year 0.065 1.065 0.070 1.0703year 0.067 1.067 0.071 1.0714year 0.067 1.067 0.067 1.0675year 0.070 1.070 0.082 1.082

Calculation of Cumulative Probability ( Cp ) of Default on Agriculture Sector

Year Interest rate 1 + k Ci 1+Ci Pi1 year 0.14 1.14 0.1 1.1 0.9642 year 0.14 1.14 0.14 1.14 0.939 Cp = 1 – ( P1 * P2 ) = 9.48 %

Calculation of Cumulative Probability ( Cp ) of Default on Large and Medium level industry

Z Score = 1.2 X1 + 1.4 X2 + 3.3 X3 + 0.6 X4 + 1.0 X5 = 4.647


Calculation of Cumulative Probability ( Cp ) of Default on Export Sector


Calculation of Cumulative Probability ( Cp ) of Default on Small & Cottage industry

Year Interest rate 1 + k Ci 1+Ci Pi1 year 0.12 1.12 0.1 1.1 0.9642 year 0.12 1.12 0.12 1.12 0.955 Cp = 1 – ( P1 * P2 ) = 7.94 %Credit Risk Measurement on the basis of RAROC modelRAROC model is one of the popular models to evaluate credit risk. Though our target bank does not use this model, we have shown a hypothetical credit risk analysis on the basis of this model for our assessment.To find out the RAROC rate we have to find out the duration of a loan.

Name of the Firm: ABC Enterprise.Location: ........................................Date: ......................................

Total Loan Amount: Tk 150 million. Year to Maturity: 5 yearsInterest rate: 10 %Installment Payment is done monthly

Duration 2.99*[Calculation of Duration is shown in Appendix}

Suppose, R = 10 %∆ R = .011L = Tk 150 millionD = 2.99

∆ L = D * L * ∆ R / 1 + R = - 2.99 * 150 * .011 / 1.10 = - 4.49

Now, again assume that, Spread = 0.2 % and Fees = 0.1 %

Spared = 0.2 % * 150 million = 0.3 million

Fees = 0.1 % * 150 million = 0.15 million

Total one year income on loan = 0.45 million

RAROC = 0.45 / 4.49 = 10.02 %Now, if 10.02 % exceeds the bank’s own RAROC benchmark, then loan will be approved, otherwise not.

Conclusion

As mentioned at the very outset, the main objective of this report is to analyze the credit risk management of United Commercial Bank Limited (UCBL) we take attempts only to explain lending risk and default risk assessment. It should be mentioned that because of data limitation we failed to sketch a real picture. However, we tried our best for the greatest output. However, as the Central Bank has prescribed the common format for lending risk analysis, commercial bank has limitations to rearrange it anymore. So in most of the cases financial institutions and banks have to analyze the crucial factors on the basis of their subjective judgments.

Another important point is to be noted that, UCBL as well as other banks usually follow only the traditional evaluation process. Most of the theoretical and latest credit rating approaches, described in our text are not followed at all. So it is difficult to draw any comment about the Bank’s efficiency for credit risk measurement.

However, bank should keenly examine the effective and crucial factors, related to credit quality problem of the loan taking firms or individual borrowers. In this regard, financial institutions have to show their highest responsibility, commitment, potentiality as well as ethics and accountability to the loan screening process. Otherwise, bank would extremely suffer from credit quality problem and incur a great loss in the long run.

AppendixLast Five Years Position at a Glance

Taka in Million

1996 1997 1998 1999 2000 2001

1. Authorized Capital 1,000.00 1,000.00 1,000.00 1,000.00 1,000.00 1,000.00

2. Paid-up Capital 223.83 230.16 230.16 230.16 230.16 230.163. Reserve Fund 183.76 265.69 301.59 334.78 348.78 393.504. Deposits 8,497.68 9,187.16 10,899.90 10,059.85 12,387.47 14,245.875. Advances 4,798.99 5,152.56 5,554.16 8,557.91 9,443.87 10,941.986. Investments 1,207.87 1,191.10 1,958.85 1,555.14 2,162.92 1,961.587. Gross Income 847.45 887.19 984.36 1,098.76 1,401.87 1,727.06

8. Gross Expenditure 644.02 766.99 863.96 987.74 1,095.68 1,223.77

9. Net Profit (Pre-tax) 203.43 120.20 120.40 111.02 22.89 175.03

10. Import Business 8,377.50 10,176.70 13,049.90 14,150.90 12,534.40 13,132.90

11. Export Business 3,467.40 4,529.20 5,192.40 5,616.50 7,178.90 5,309.30

12 Foreign Correspondents 102 102 110 110 110 110

13. Number of Employees 1,938 1,948 1,947 1,878 1,842 1,812

14. Number of Branches 78 79 79 79 79 79

15 Number of Shareholders 1,915 2,095 2,128 3,086 3,200 3,539

Calculation of Duration

Period Payment PV of cash flow PV * t1 3.4902 3.456 12.0612 3.4902 3.421 11.9413 3.4902 3.388 11.8234 3.4902 3.354 11.7065 3.4902 3.321 11.5906 3.4902 3.288 11.4767 3.4902 3.255 11.3628 3.4902 3.223 11.2499 3.4902 3.191 11.13810 3.4902 3.160 11.02811 3.4902 3.128 10.91912 3.4902 3.097 10.81013 3.4902 3.067 10.70314 3.4902 3.036 10.59715 3.4902 3.006 10.49316 3.4902 2.977 10.38917 3.4902 2.947 10.28618 3.4902 2.918 10.18419 3.4902 2.889 10.08320 3.4902 2.860 9.98321 3.4902 2.832 9.88422 3.4902 2.804 9.78723 3.4902 2.776 9.69024 3.4902 2.749 9.59425 3.4902 2.722 9.49926 3.4902 2.695 9.40527 3.4902 2.668 9.31228 3.4902 2.642 9.21929 3.4902 2.615 9.12830 3.4902 2.589 9.03831 3.4902 2.564 8.94832 3.4902 2.538 8.86033 3.4902 2.513 8.77234 3.4902 2.488 8.68535 3.4902 2.464 8.59936 3.4902 2.439 8.51437 3.4902 2.415 8.43038 3.4902 2.391 8.34639 3.4902 2.368 8.26440 3.4902 2.344 8.18241 3.4902 2.321 8.10142 3.4902 2.298 8.02143 3.4902 2.275 7.94144 3.4902 2.253 7.86245 3.4902 2.230 7.78546 3.4902 2.208 7.708

47 3.4902 2.186 7.63148 3.4902 2.165 7.55649 3.4902 2.143 7.48150 3.4902 2.122 7.40751 3.4902 2.101 7.33352 3.4902 2.080 7.26153 3.4902 2.060 7.18954 3.4902 2.039 7.11855 3.4902 2.019 7.04756 3.4902 1.999 6.97857 3.4902 1.979 6.90858 3.4902 1.960 6.84059 3.4902 1.940 6.77260 3.4902 1.921 6.705

∑ = 313.741 ∑ = 937.798 Duration = ∑ PV * t / ∑ PV

= 937.798 / 313.741= 2.99

Bibliography www.ucbl.com Annual Report 2001-2002, United Commercial Bank Ltd. Financial Institutions Management: A Modern Perspective

By Anthony Saunders

http://www.ucbl.com/

Documents

Credit Risk management