View with images and charts 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 路 路
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 UCBL Sponsored 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
•
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)
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
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. 400 350 300 250 200
Resurve fund
150
Capital
100 50 0 1997 1998 1999 2000 2001
Human Resources Imbibed 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. Deposits The 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
C.loan D loan Term loan Term loan Staff loan
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. 2500 2000 1500
Ser‌
1000 500 0
1
Foreign Trade
2
3
4
5
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.
15000 10000 Import 5000
Export
0
Expor t
1
2
3
4
5
Inspection Experienced 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 income 1998 1999 2000 2001
258523095 468671807 1020392051 1528678923
interest Total expenses 237324232 377744520 691594670 1168952993
interest Average
Earning NIM Assets (%)
3820029159 6665118388 12986669244 17243093906
.55 1.36 2.53 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 Χ 100
YEAR 1999 2000 2001 2002
PROVISION FOR LOANS & LOSSES 24731000 51323000 166854000 298730000
TOTAL LOANS&LEASES
PLR (%)
2283648484 4588087640 8044426040 9391643297
1.08 1.12 2.07 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. Loan ratio (%) = Net Loan / Assets Χ 100
YEAR
NET LOANS
TOTAL ASSETS
1999 2000 2001 2002
2283648484 4588087640 8044426040 9391643297
4000810543 6966336681 13463230033 17865667543
LOAN (%) 57.08 65.86 59.75 52.57
RATIO
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 Gap Ratio (%)
1999 0.69
2000 -0.89
2001 -6.06
2002 -9.41
Dollar gap ratio (%) = {(Interest rate sensitive assets - Interest rate sensitive liabilities)/ Total assets} Χ 100
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.
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.
Credit Risk Models
Qualitative Models
Credit Scoring Model
Borrower’s specific factors • • • •
Reputation Leverage Volatility of earnings Collateral
• •
Market Specific factors
•
The business cycle The level of interest rate
• • •
Linear Probability model Logit model Probit model Linear discriminate model
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.
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 decision Borrower 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
Next we take a brief look at each of these models and their major strengths and weaknesses Linear Probability Model The 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: Zi = Σ βjXij + error Where βj is the estimated importance of the repayment experience. Cumulative probability of default
j i
th variable (leverage) in explaining past
1
E (Zi)
Logistic Function
0 Zi 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
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).
Z = 1.2X1 + 1.4X2 + 3.3X3 + 0.6X4 + 1.0X5 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 (X 5) 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 = 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 threequality 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 y>0, 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 Φ and between k and i. k – i = Φ = (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. Marginal Mortality Rate
0
1
2
3
4
Year since Issue
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.
RAROC Models A popular model to evaluate credit risk based on market data is the RAROC model. RAROCrisk 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= -DL X LX (ΔR/1+R)
ΔL -DL L ΔR
= Dollar capital risk exposure or loss amount = Duration of the loan = Risk amount or loan size = 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.
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) Current exposure Amount To this customer
Organizing Branch/ office
Nature of land Current exposure (total) to this group Taka ………………
Application for New facility
Increase to existing facility
Renewal of Existing facility
Delinquent customer
Why this analysis conducted Risk category Marginable Poor
Good
Acceptable Type Amount
of
facility
sought
Business Security Overall Purpose
Type of facility recommended Type Amount
Loan category Voluntarily given By the bank
Level of approval required
Part of Government
Date customer made request Scheme
…………………………
Date analysis Completed
(Name of scheme) Directed by Individual ………………... ................................................... .... (Name of person directing the loan) Recommendation Date recommendation made Originating officer Accept Decline Amount Recommendation officer(s)
Decision
Date decision made
Approving officer
Accept Decline Amount
Officer authorizing Date disbursement disbursement Authorized
Date loan Disbursed
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 Business Risk Industry Risk Company Risk
Company Position Risk
Risk level Low Average excursive Supplies risk What is the risk of due to description supply of inputs? Sales risk What is the risk of due to description supply of inputs?
Score High 3.3
failure Score 1.5 in the 12
5
4.5 1.53
failure Score 1.5 in the 12
Performance risk What is the risk that the Company’s position is so Score 1.5 weak that it cannot perform 12 well enough to repay the loan, given expected external conditions? Resilience risk What is the risk of failure Score 1.5 due to lack of resilience to 12 unexpected external conditions?
5
4.5
1.2 5
4.5
2.4 5
4.5
Manageme nt Risk
Management competence risks What is the risk of Score 1.5
3.3 5
4.5
failure due to lack of 12 management competence? Management Integrity risks What is the risk of 6.3 failure due to lack of Score 1.5 5 4.5 management Integrity? 12 Total business risk score 18 Security control risk What is the risk that the bank fails 10 to realize the security? Score 1.5 5 4.5 12 Security cover risks What is the risk that the realized 15 security value is less than the Score 1.5 5 4.5 exposure? 12 Total security risk score 20
Securit y Risk
Good risk
Acceptable Risk 20.26
Marginable Risk 27.34
Poor Risk
1
1
1
1
Good risk
Acceptable Risk (.14.0) .0
Marginable Risk 1-10
Poor Risk
Business Risk 13.19
Security
(.201 )
(.15)
Over 34
Over
10
Select Overall Risk from Matrix 1 A B C D
2 A B C D
3 A B C D
4 A B C 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 assessment According 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
Labor Raw materials
Equipment Power
Premises
Other
% Of total costs
What is the disruption? Better than Worse average
risk
of Comments
Average
Number of days production lost is past 12 months due to strikes? …………………. Independent power supply
Dependent power
supply Power 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. Year Estimated turnover
total
industry Strong
weak
no
growth
growth
change
small
large
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 competitors Major competitor I …………………………… Market share. ………………%
(Name) Performance
Year Turnover Profit Less Fast
about the same
faster
This competitor is growing than our customer. What prevents customers from switching to this competitor?
Major competitor II ……………………………… Market share. ………………% (name) Performance Year Turnover Profit Fast
Less about the same
faster
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 entry Difficult
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
What is the risk that changes in regulations will damage sales? Explain your answer.
High
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
No
Are financial spreadsheets attached? Give most recent 3 years performance data Year Sales Capital profits Explain the significance of any important trends you notice in the performance data.
Competitive position What 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) Strategy How does the company differentiate itself from its competitors? Quality Better than Indistinguis Worse than competitors hable from competitors competitors
Price Cheaper than About the More competitors same as expensive than competitors competitors
What strategy will this company adopt to exploit its strengths and overcome its weaknesses?
Biplecontidence strategy
in Average
low confidence in strategy
How confident are you that this strategy will word? Cash flow forecasts Do the cash flow forecasts Significantly more Enough cash indicate that the company will than enough cash generate sufficient cash to repay its loans? How confident are you that the company will High perform as forecast in the cash flows? confidence
Not enough cash
Average
Low confidence
Explain your answer What is the risk that the company’s position Low is so weak that it cannot perform well enough to repay the loan, given expected external conditions?
Average
High
Excessive (tick box)
one
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 Values reported by Bank’s leverage company assessment Assets Liabilities Equity (= Assets – liabilities) Leverage (= Liabilities/ equity)
Exposure to other banks Bank
Exposure
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 Very company in the future if the need arises? readily
will support reluctantly
may not support further
Explain your answer How resilient is the company to Highly resilient bankruptcy?
Average
Not at all resilient
Liquidity Explain the significance of any important trends shown by the ratio analysis. Loans/01/006 June 93 What proportion costs is Very easily Average With difficulty fixed? ..............................................
How easily will this company be able to reduce costs if sales fall? Explain your answer. How resilient is the company to liquidity Highly Average (which may cause repayment failure)? resilient
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 Highly adverse effects of political changes? resilient
Average
Resilience risk W** assessments of resilience to bankruptcy, Highly liquidity the adverse effects of political resilient changes, from above. (low risk)
Not at all resilient
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
Excessive
At 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 Name Share holding (%)
List board members
What is your assessment of the ability Better than Average of these people to ensure that this average company succeeds? Give reasons for your assessment.
Worse than average
Who is the primary decision maker on issues? .......................................................................................................... (Name) Is this person’s biodata attaclied? Yes No What is your assessment of this Better person’s ability to manage the average tenancies of this company?
than Average
Worse than average
Who is the primary decision maker on issues? .......................................................................................................... (Name) Is this person’s biodata attaclied? Yes No What is your assessment of this Better than Average person’s ability to manage the average operations of this company? Give reasons for your assessment.
financial
financial
Worse than average
Comment on strengths and weaknesses of any other key personnel Name Responsibility Strength Weakness
What is the risk that the business fails due to lack of Low management ability? (Tick on box) Loans/01/008 June 93
Average
High
Excessive
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 Company Name
Date of visit
Site visited
Date of last visit
People visited
Bank officers making visit
Total facilities Visit objective and data to be collected
Current outstanding
(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
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 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
Results noted above.
Expected security cover strength Primary security a) Types of security b) Expected realizable value at liquidation c) Expected time taken to liquidated this security d) Discount rate %
Collateral Other Total security
(One year fixed deposit rate) e) Discount factor % = 100 * 1/ (1 + d / 100) ^e f) 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 1 2
ASSETS TYPE DATE CASH ON HAND CASH IN BANK
%
3 4 5 6 7 8 9 1 TO 3 + 6 TO 9 10 11 12 13 14 15 16 17 18 19 13 + 16 TO 20 20 10 + 21 21 22 23 24 25 26 27 28
24 TO 30
32 TO 34 31 + 35
29 30 31 32
37 TO 40
33 34 35 36 37 38 39
36 + 41
40
SECURITIES (MARKETABLE) RECEIVABLES TRADE LESS: BAD DEBT ALLOWANCE NET RECEIVABLES INVENTORIES ADVANCE ALL OTHER CURRENT ASSETS TOTAL CURRENT ASSETS LAND &BUILDINGS LESS: DEPRECIATION NET LAND & BUILDINGS MACHINERY & EQUIPMENT LESS: DEPRECIATION NET MACHINERY & EQUIPMENT INVESTMENTS SUBSIDIARIES INVESTMENTS ASSOCIATED CO. ALL OTHER NON CURRENT ASSETS TOTAL NON CURRENT ASSETS TOTAL ASSETS LIABILITIES OVERDRFT / CASH CREDIT LOANS FROM BANKS (UNDER 1 YEAR) LOANS FROM OTHERS (UNDER 1 YEAR) ACCOUNTS PAYABLE TRADE L.T.DEBT MATURING UNDER 1 YEAR PROVISION FOR TAXES ALL OTHER CURRENT LIABILITIES TOTAL CURRENT LIABILITIES LONG TERM DEBT ALL OTHER NON CURRENT LIABS TOTAL NON CURRENT LIAILITIES TOTAL LIABILITIES CAPITAL + PAID IN SURPLUS RESERVES RETAINED EARNINGS LESS: INTANGIBLES NET WORTH TOTAL LIABILITIES & NET WORTH
43 44 45 46 47 48 14 TO 48 49 43 - 49 50 51 52 53 54 51 TO 54 55 50 - 55 56 57 58 (56 + 57) - 58 59 60 59 - 60 61
10 - 31
101 102 103
61 47 + 54 103
104 105 106 107
Current year
108
Minus prior
109 110
104+105+106 111 107 TO 110 112 113 114
PROFIT & LOSS SALES (NET) MATERIALS USED/GOODS PURCHASED LABOUR MANUFACTURING EXPENSES DEPRECIATION COST OF GOODS SOLD GROSS PROFIT SELLING EXPENSES GENERAL & ADMIN. EXPENSES INTEREST DEPRECIATION TOTAL OPERATING EXPENSES OPERATING PROFIT OTHER INCOME OTHER EXPENSES PROFIT BEFORE TAX INCOME TAX NET PROFIT AFTER TAX ANALYSIS DATE CONTENGENT LIABILITIES WORKING CAPITAL DIVIDEND PAID CASH FLOW FROM OPERATING ACTIVITIES NET EARNINGS PLUS DEPRECIATION MINUS DIVIDEND PAID /OTHER NON CASH ADJUSTMENT INCREASE/DECREASE IN INVENTORY INCREASE/DECREASE IN RECEIVABLES INCREASE/DECREASE IN PAYABLES INTERNALLY GENERATED CASH INCREASES (DECREASES) IN WORKING CAPITAL CASH & CASH EQUIVALENTS RECEIVABLES INVENTORY
115 116 117 118 119 120 121
122 123 124 125 126 127 128 129 130 131 10/31 (10-7)/31
132 133
365/(43/6) 365/(49/7)
134 135
365/(43/27) 43/102 36/41
136 137 138
PAYABLES SHORT TERM LOANS AND LONG TERM LOANS DUE WITHIN 12 MONTHS NET TAXES PAID OTHER CURRENT ASSETS OTHER CURRENT LIABILITIES NET CHANGES IN WORKING CAPITAL WORKING CAPITAL PROVIDED BY (USED FOR) NET CHANGES IN CAPITAL NET CHANGES IN P&L AND RESERVES NET CHANGE IN LONG TERM LOAN ACQUISITION/SALE OF PROPERTY ACQUISITION/SALE OF FIXED ASSETS INV IN SUBS & ASSOCS OTHER INVESTING ACTIVITIES OTHER NON CURRENT ASSETS OTHER NON CURRENT LIABILITIES OTHER SOURCES AND USES OF FUND RATIOS CURRENT QUICK RECEIVABLES TURNOVER IN DAYS INVENTORY TURNOVER IN DAYS ACCS. PAYABLE TURNOVER IN DAYS SALES TO WORKING CAPITAL DEBT TO EQUITY
An Example of Default Risk Analysis (using Altman Z score) Name of the firm: Address:
XYZ Manufacturing Corporation. .....................................................
Selected Items of Balance Sheet At the Year Ended 31 December, 2002 (Tk in crore)
Net sales Operating cost and Exp. Other income Net income EPS Dividend per share Share Outstanding
2962.70 2291.80 13.30 411.80 2.71 1.30 155.00
Cash and M securities Current asset Current liabilities Property and Equipment Total asset Long term obligation Share holder equity
303.80 1680.50 873.60 1135.60 3155.10 49.40 2055.50
Selected Ratio of XYZ Manufacturing Corporation Return on avg.asset (%) Return on Equity (%) WC/ Total asset ratio Retained earning/Total Asset EBIT/Total asset MV Equity/BV debt Sales / Total asset
13.6 20.9 25.57% 6.93% 16.31% 4.61 0.939
Calculation of Z score
WC/ Total asset ratio (X1) Ret. earning/Total Asset (X2) EBIT/Total asset (X3) MV Equity/BV debt (X4) Sales / Total asset (X5)
Value or Ratio 0.256 0.069 0.163 4.61 0.939
Weight 1.2 1.4 3.3 0.6 1.0 Total
Ratio*Weigh t 0.307 0.097 0.538 2.77 0.939 4.647
Z Score = 1.2 X1 + 1.4 X2 + 3.3 X3 + 0.6 X4 + 1.0 X5 = 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 Large & medium level industry Export Other commercial loan Small and cottage industry Brick Financing Fertilizer dealer
10 % 14 % 7% 13.5 % 12 % 14 % 14 %
Spot rate and Forward rate (assumption) 1year 2year 3year 4year 5year
Treasury bill Spot rate = i 0.060 0.065 0.067 0.067 0.070
1+ i 1.060 1.065 1.067 1.067 1.070
Forward rate = f 0.060 0.070 0.071 0.067 0.082
1+fi 1.060 1.070 1.071 1.067 1.082
Calculation of Cumulative Probability ( Cp ) of Default on Agriculture Sector Year 1 year 2 year
Interest rate 0.14 0.14
1+k 1.14 1.14
Ci 0.1 0.14
1+Ci 1.1 1.14
Pi 0.964 0.939
Cp = 1 – ( P1 * P2 ) = 9.48 % Calculation of Cumulative Probability ( Cp ) of Default on Large and Medium level industry Year 1 year 2 year
Interest rate 0.10 0.10
1+k 1.10 1.10
Ci 0.1 0.14
1+Ci 1.1 1.17
Pi 0.906 0.973
Cp = 1 – ( P1 * P2 ) = 11.85 % Calculation of Cumulative Probability ( Cp ) of Default on Export Sector Year 1 year 2 year
Interest rate 0.07 0.07
1+k 1.07 1.07
Ci 0.1 0.14
1+Ci 1.1 1.135
Pi 0.964 0.943
Cp = 1 – ( P1 * P2 ) = 9.12 % Calculation of Cumulative Probability ( Cp ) of Default on Small & Cottage industry Year
Interest rate
1+k
Ci
1+Ci
Pi
1 year 2 year
0.12 0.12
1.12 1.12
0.1 0.12
1.1 1.12
0.964 0.955
Cp = 1 – ( P1 * P2 ) = 7.94 % Credit Risk Measurement on the basis of RAROC model RAROC 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 years Interest rate: 10 % Installment Payment is done monthly Duration 2.99* [Calculation of Duration is shown in Appendix} Suppose,
R = 10 % ∆ R = .011 L = Tk 150 million D = 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. Appendix Last 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. 3. 4. 5. 6. 7.
223.83 183.76 8,497.68 4,798.99 1,207.87 847.45
230.16 265.69 9,187.16 5,152.56 1,191.10 887.19
230.16 301.59 10,899.90 5,554.16 1,958.85 984.36
230.16 334.78 10,059.85 8,557.91 1,555.14 1,098.76
230.16 348.78 12,387.47 9,443.87 2,162.92 1,401.87
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
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
Paid-up Capital Reserve Fund Deposits Advances Investments Gross Income
230.16 393.50 14,245.87 10,941.98 1,961.58 1,727.06
175.03
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
79
79
79
79
79
2,095
2,128
3,086
3,200
3,539
78
15 Number of Shareholders 1,915
Calculation of Duration Period 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46
Payment 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902
PV of cash flow 3.456 3.421 3.388 3.354 3.321 3.288 3.255 3.223 3.191 3.160 3.128 3.097 3.067 3.036 3.006 2.977 2.947 2.918 2.889 2.860 2.832 2.804 2.776 2.749 2.722 2.695 2.668 2.642 2.615 2.589 2.564 2.538 2.513 2.488 2.464 2.439 2.415 2.391 2.368 2.344 2.321 2.298 2.275 2.253 2.230 2.208
PV * t 12.061 11.941 11.823 11.706 11.590 11.476 11.362 11.249 11.138 11.028 10.919 10.810 10.703 10.597 10.493 10.389 10.286 10.184 10.083 9.983 9.884 9.787 9.690 9.594 9.499 9.405 9.312 9.219 9.128 9.038 8.948 8.860 8.772 8.685 8.599 8.514 8.430 8.346 8.264 8.182 8.101 8.021 7.941 7.862 7.785 7.708
47 48 49 50 51 52 53 54 55 56 57 58 59 60
3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902 3.4902
2.186 2.165 2.143 2.122 2.101 2.080 2.060 2.039 2.019 1.999 1.979 1.960 1.940 1.921 ∑ = 313.741
7.631 7.556 7.481 7.407 7.333 7.261 7.189 7.118 7.047 6.978 6.908 6.840 6.772 6.705 ∑ = 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