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CREDIT ANALYSISSubmitted By:

Aman Nogia (2806)Repali Durga Babu (2820)Prerna Aggarwal (2842)Himanshu Khurana (2855)Sweta Suman (2864)Kinshuk Bansal (2871)

Credit AnalysisCredit analysis is the evaluation of a firm from the perspective of holder or potential holder of its dept , including trade payables , loan and public dept securities.

Credit analysis is the quantitative and qualitative analysis of a company, which help to determine the companys debt service capacity, or how capable it is to pay back its principal payments to the bank or other creditors.

Credit analysis involves the examination of the link between management performance or capacity and the working relationship of a companys assets, liabilities and equity as shown on its balance sheet.

Basic ConceptsThe "five C's" the basic components of a credit analysis:Character is the general impression the customer makes on the prospective lender or investor. Capacity to repay is the most critical of the five factors; it is the primary source of repayment cash inflows and cash generated by the company. Capital is the money personally invested in the business by the shareholder borrower and is an indicator of how much the shareholder has at risk should the business fail.Collateral (or guarantees) are additional forms of security the customer can provide the lender. Giving a lender collateral means that an own asset is mortgaged, such as a propertyConditions describe the intended purpose of the loan and the conditions under which the credit is being grantedDefault RiskThe event in which companies or individuals will be unable to make the required payments on their debt obligations. Lenders and investors are exposed to default risk in virtually all forms of credit extensions.

The risk that a partner in a business transaction will not live up to its obligations; for example, that a financial institution such as a bank or savings and loan may collapse and not be able to return the investors principal, or may not continue paying interestThe Market for CreditCommercial banks : commercial banks are very important player in the market for credit . Since banks tend to the provide a range of services to a client, they have a comparative advantages in extending credit in setting.Non-bank financial institutions: financial companies compete with the banks in the market for the asset based lending.Public debt markets: Requires that a firm have the size, financial strength, and credibility to bypass the banking sector and seek financing directly from investors.Sellers who provide financing: Suppliers typically extend very short term financing to buyers, but may occasionally grant a loan

The Credit Analysis Process in Private Debt MarketsStep 1:Consider the nature and purpose of the loan: The purpose of the loan is important not just for deciding whether it should be granted but also for structuring the loan.The size of the loan must be set. In the case of small and medium sized companies, a banker would prefer to be sole financial businessStep 2:Consider the type of loan and available security:Type of the loan consider is a function of not only its purpose , but also the financial strength of the borrower.The type and amount of security needed to collateralize a loan must be established

The Credit Analysis Process in Private Debt Markets(Cont..)Step 3:Potential borrower financial status: the portion of the analysis involves all the steps likes business strategy analysis, accounting analysis, financial analysis. Ratio analysis is useful, particularly ratios addressing the ability to make loan payments.

Step 4:Assemble the detailed loan covenants: Loan covenant specify mutual expectation of the borrower and lender by specifying action the borrower will and will not take. loan covenant must strike a balance between protecting the interest of the lender and providing the flexibility management

Loan Covenants/PricingLoan covenants: loan covenants specify mutual expectation of the borrower and lender by specifying action the borrower will and will not take. Loan covenants must strike a balance between protecting the interest s of the lender and providing flexibility management needs to business.

Loan pricing : the essence of pricing is to assume that the yield on the loan in sufficient to cover- (a) the lender cost of borrower funds (b) the lender cost of administering loan (c) a premium for exposure to default risk (d)a normal return on the equity capital necessary to lending operation Credit RatingA credit rating estimates the credit worthiness of an individual, corporation or even a country. It is an evaluation made by credit bureaus of a borrowers overall credit history.

Credit rating are based on financial history and current assets and liabilities.

Typically, a credit rating tells a lender or investor the probability of the subject being able to pay back a loan.

Commercial credit risk is the largest and most elementary risk faced by many banks and it is a major risk for many other kinds of financial institution and corporation as well.

Rating symbols for debenturesHigh investment grade:

AAA-(Triple A) high security- offer the highest safety against payment of interest and principle.

AA(Double A)high safety-offer high safety against payment of interest and principal.

A-Adequate safety- offer adequate safety against payment of interest and principal. In adverse condition might affect such issues.

BBB(Triple B)- moderate safety offer sufficient safety against payment of interest and principal. Circumstances may lead to weakened capacity to pay interest and principal. Speculative grades:BB(Double B)- inadequate safety- these instruments carry inadequate safety of timely Payment of interest and principle.

B(High risk)-instrument rated B have greater risk of default.

C(Substantial risk)-risk of default. Repayment can only be expected are extremely speculative and default risk is highest.

D(Default) such instruments are extremely speculative and default risk is higher.

Factors that drive debt ratingDebt rating agencies rely heavily on quantitative models and such models are commonly used by insurance companies , banks and other to assist in the evaluation of the riskiness of dept issues for which a public rating is not available.

Firm sizeSubordination status of debt ProfitabilityUnsystematic riskRiskiness of profit streamInterest coverageLeverageSystematic risk

Prediction of distress and turnaroundThe key task in credit analysis the probability that a firm will face financial distress and fail to repay a loan.

The prediction of either distress or turnaround is a complex, difficult and subjective task that involves all of the step of analysis discussed. There are several distress prediction models- 1.Profitability = [Net income/Net worth] 2. Volatility=[Standard deviation of (Net income/Net worth)Prediction of distress and turnaround(cont..)3. Financial leverage= [Market value of equity/(Market value of equity +Book value of debt)

The evidence indicate that the key to whether a firm will face distress is its level of profitability, the volatility of that profitability and how much leverage it faces Ratio analysis for credit evaluation Financial analysis using financial ratios provides a mean of assessing a company's strengths and weaknesses.

Using data from the balance sheet and income statement, various ratios can be computed which can then be compared directly to those of competing companies of varying sizes.

Generally, financial ratios are calculated for the purpose of evaluating aspects of a company's operations. They are grouped into following types 1) Short term liquidity ratios 2) Long term solvency ratios Short term liquidity ratios

Long term solvency ratios

Forecasting and credit analysis Prelude to Forecasting: The Interpretive Background Understand the business strategy and understand the drivers of value in the strategy. Appreciate the moral hazard problem of debt. Understanding the financing strategy. understanding the current financing arrangements. Understand the quality of firms accounting. Understand the auditors opinion, particularly any qualification to the opinion.

Ratio Analysis and Credit-scoring

Consequences arise in getting default from accounting ratios Many ratios to be considered. A low interest coverage but a high current ratio may have different implications than a low interest coverage and a high current ratio. Errors in predicting default and the cost of prediction errors have to be considered.

The first issue calls for a method of combining ratios into one composite score that indicates the overall creditworthiness of the firm. The second issue calls for a method of trading off the two types of errors that can be made. We deal with each in turn. Credit Scoring ModelsCredit Score = W1 x Ratio1 + W2 x Ratio2 + + Wn x Ratio NCredit scoring models combine a set of ratios that pertain to default into a credit score.

A variety of statistical techniques can be used to determine the weights, but two common ones are multiple discriminant analysis and logit analysis.

Multiple Discriminant Analysis:Altmans Z-score models:

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Logit analysis Its based on different statistical analysis assumptions from discriminant analysis.

It gives a score between 0 and 1 that indicates the probability of default.

Prediction Error Analysis

Classifying a firm as not likely to default when it actually does default is called a Type I error. Classifying a firm as likely to default when it does not default is called a Type II error. Both errors have costs. In a Type 1 error, the bank or bond holder loses in the default.In a Type II error, the bank or bond investor misses out on a good investment. Many considered a type I error more costly than a type II error

Full-Information Forecasting

The full information about the firms is captured by the pro forma analysis along with value at risk analysis.Pro Forma Analysis and Default PredictionPro forma analysis for equity evaluation focuses on forecasting operating income and net operating assets for the residuals income calculation.The forecasts underlying these pro formas were a sales growth of 5 percent per year, a profit margin (PM) of 7.85 percent, an asset turnover (ATO) of 1.762, and a dividend payout of 40 percent of net income.Scenario 2 gives a different picture. Here sales are expected to decline by5percent each year and the profit margins are expected to be only 1 percent Net operating assets decline with sales but they are not perfectly flexible, so asset turnover decreases.

Value-at-Risk Profiles and the Probability of Default

Scenario 2 is a default scenario, but it is just one default scenario: It forecasts a particular sales growth, profit margin, and so on.Other operating and financing scenarios are possible and the analyst is interested in the full set of default scenarios.

The debt analysis profiles the possible variation in cash available for debt service. Follow these steps:Generate profiles of cash available for debt service for a full set of scenarios from pro forma analysis. Establish the debt service requirement Identify the default point where cash available for debt service is below the debt service requirement, and so identify the default scenarios. Assess the probability of the set of default scenarios occurringProbability of default = Pr {Cash available for debt service < Debt service requirement}

Liquidity planning and financial strategyPro forma analysis here be used to formulate financial strategy.Objective is to ensure debt and equity financing is in place to support firms operational strategyPlanning for pessimistic scenarios sets a default strategy. Other scenarios to deal with default are Modify operations to reduce operational risk that generates default riskIssue equity Issue or roll over debt Establish an open line of credit Sell off assets Sell of whole firm ( in an acquisition )Hedge risks

FINANCIAL RATIOS, DISCRIMINANTANALYSIS AND THE PREDICTION OFCORPORATE BANKRUPTCYAltman, E. I. (1968), The Journal of FinanceResearch PaperPurpose: To assess the quality of ratio analysis as an analytical technique.

The prediction of corporate bankruptcy is used as an illustrative case.

Financial and economic ratios are investigated in bankruptcy prediction wherein a multiple discriminant statistical methodology is employed.

It has been divided into the five sections:Traditional ratio analysisMultiple discrimination analysisDevelopment of the model Empirical resultApplications

Traditional Ratio AnalysisIn earlier times, agencies used to supply qualitative information to assess the creditworthiness of particular merchants.

A study at that time concluded that failing firms exhibit significantly different ratio measurements than continuing entities.

A later work compared a list of ratios individually for failed firms and non failed firms. It was observed that ratio analysis can be useful in the prediction of failure.

Ratios measuring profitability, liquidity, and solvency prevailed as the most significant indicators.Multiple Discriminant AnalysisMDA is a statistical technique used to classify an observation into one of several a priori groupings dependent upon the observation's individual characteristics.

It is used primarily to make predictions in problems where the dependent variable is in qualitative form, e.g., male or female, bankrupt or non-bankrupt.

In our case we have 2 groups: Bankrupt & Non-Bankrupt and data is collected for the objects in the groups.

MDA then attempts to derive a linear combination of these characteristics which best discriminates between the groups.

MDA approach to traditional ratio analysis has the potential to reformulate the problem correctly. Combinations of ratios can be analyzed together in order to remove possible ambiguities and misclassifications observed in traditional studies.Development Of The ModelThe Initial sample has 66 corporations with 33 firms in each of the two groups

The data collected are from the same years as those compiled for the bankrupt firms

Data is derived from financial statements one reporting period prior to bankruptcy.

From the original list of 22 variables, five variables are selected as doing the best overall job together in the prediction of corporate bankruptcyThe final discriminant function is as follows:

The lower the discriminant score, greater a firm's bankruptcy potential.Variable Means and Test of SignificanceTo test the individual discriminating ability of the variables, an F test is performedThis test relates the difference between the average values of the ratios in each group to the variability (or spread) of values of the ratios within each group.

Relative Contribution Of Each Variable

The profitability ratio contributes the most, which is not surprising if one considers that the incidence of bankruptcy in a firm that is earning a profit is almost nil.

X3 i.e profitability ratio contributes the most43Empirical Results

The H's stand for correct classifications (Hits) and the M's stand for misclassifications (Misses). M1 represents a Type I error and M2 a Type II error.

% of firms correctly classified = Total Hits i.e. H + H Total number of firms classifiedyields the measure of success of the MDA

44The final criterion used to establish the best model was to observe its accuracy in predicting bankruptcy.

The model is extremely accurate in classifying 95 per cent of the total sample correctly.

Type I error - 6 percent, while the Type II error was 3 percent.ApplicationAll firms having a Z score of greater than 2.99 clearly fall into the non-bankrupt category, while firms having a Z score below 1.81 are all bankrupt.

The area between 1.81 and 2.99 is defined as the zone of ignorance or gray area.