Credit Risk Management in Canara Bank Essay

In the past few years, on that point pose been some(prenominal) developments in the field of modeling the trust run a jeopardy in banks moneymaking(prenominal) bestow portfolios. realisation risk is essenti in ally the possibility that a banks lend portfolio result lose value if its borrowers reach unable to afford back their debts. Arguably, reference book risk is the largest risk faced by moneymaking(prenominal) banks, since imparts and a nonher(prenominal) debt instruments constitute the bulk of their assets. In the U. S. , contributes made up everyplace 60% of total banking assets at year-end 2000, and meliorate-income securities made up an supernumerary 14%.These book of facts risk models be becoming widely received by banks for various purposes in fact, bank supervisors, including the Federal Reserve, score lately proposed new risk-based capital waitments based partly on much(prenominal) models. This scotch Letter provides a brief survey of how the se models argon constructed and used for identification risk measurement and management. General modeling procedure Commercial banks have been using ascribe risk models for their mortgage and consumer impart for decades.These course credit risk models, typically kn sustain as credit scoring models, were first unquestionable for consumer lending because of the large number of borrowers and their detailed credit histories. In contrast, there are m each fewer commercial borrowers, and it is only within the net few years that credit risk models for commercial loans have been success amply created, securities attentioned, and integrated into banks risk management procedures. Although a reasonable variety of such models exists, all of them are constructed broadly on three standard adjectival steps.The first step is to choose the type of credit risk to be modeled. Default models simply estimate the probability that a borrower testament slackness on that is, the borrower will non make any much payments under the received lending agreement. In contrast, multi- accede (or mark-to-market) models estimate the probability that the borrowers credit smell will change, including a change to default status. For example, a multi-state model forecasts the probabilities of whether a B-rated borrower will remain B-rated, will become n A-rated or a C-rated borrower, or will default. Obviously, default models are a special character reference of multi-state models and are being used less frequently by banks. An authorised element of this choice is the horizon over which credit handoutes are measured. For example, a borrowers credit quality may change several times before a default, and a default model would non be able to capture these changes. Many options are available to the user, besides common practice has settled on a one-year horizon, which is shorter than the maturity date of many commercial loans.This relatively short horizon is out-of-pocket partl y to modeling convenience and partly to the increasing liquidity of the secondary loan market and the credit derivatives market. Both of these markets permit banks to hedge (i. e. , decrease) their credit characterization to a particular borrower or class of borrowers. The second step is to deposit the probability of each credit state occurring and the value of a given loan in each of them. In default models, there are two credit states the credit is simply paid off totally, or it is worth a recovery value in case of default.In multi-state models, the loans value in each possible credit state is frequently assessed by referencing credit spreads derived from the merged bond market. The state probabilities fecal matter be calculated in several ways, such as from simple historical experience in the corporate bond market or from models using data from the public debt and equity markets. The combination of the estimated determine of a loan in the different states and the estimated probabilities of the states determine the credit departure diffusion for that loan.A central element of these spillage calculations is the credit rank initially assigned to a loan and its corresponding borrower. Corporate credit ratings for large borrowers that issue publicly traded debt are available from financial selective information vendors, such as Moodys and Standard & Poors. For other borrowers, which, in fact, typically make up the bulk of banks commercial loan portfolios, banks must rely on their own internal ratings systems, based on both public information and their own credit experience put on Treacy and Carey (1998) for a survey of banks internal ratings systems.The third step combines the credit loss distribution for each loan into an aggregate portfolio loss distribution. This aggregation depends this instant on the default correlations between individual credits, that is, the degree to which probable changes in credit status and losings are interrelated. T here are generally two ways to model these correlations. In reduced form (or occur down) models, correlations are essentially a by-product of the models portfolio loss distribution.In structural (or bottom up) models, the default correlations are modeled as functions of several variables, such as a borrowers industrial categorization and country of origin. In addition, macroeconomic factors can be incorporated into these correlations. Once specified, the correlations are used to combine individual credit losses in different states into a loss distribution for the built-in portfolio based on the credit risk models implicit in(p) assumptions. Credit risk models as a risk management dig A portfolios credit loss distribution is a account analytical tool for credit risk management.Once determined, this loss distribution gives a banker a complete forecast of possible portfolio credit losses over the coming year. For example, the mean of the distribution is the expected value of auth orization credit losses and could be used directly to determine the train of loan loss provisions that should be held for the loan portfolio. Furtherto a greater extent, the high gearer percentiles of the portfolio loss distribution can be used to determine the economic capital necessary for the portfolio. Economic capital is the buffer of reserves banks hold to safeguard against unexpected loan losses.Economic capital is typically set high enough that unexpected credit losses are very unbelievable to exhaust it. For example, a banker could determine the amount of capital necessary to cover up the solvency of the portfolio with a 99. 97% probability, which roughly corresponds to the annual 0. 03% default probability of AA-rated corporate bonds. Furthermore, the loss distribution provides the banker with a diagnostic tool for examining the impact of changes in credit concentrations on the entire portfolios potential losses.This approach to credit risk management has now been exp licitly incorporated into the risk-based capital requirements certain by the Basel Committee on Banking Supervision (2001), an inter issue forum for commercial bank regulation. Under the Committees recently proposed revisions to the 1988 Basel Capital Accord, national bank supervisors would permit banks that have met certain supervisory criteria to use their own internal models to determine certain inputs to their regulatory capital requirements.However, the new guidelines will not permit banks to set their capital requirements solely on the creation of their own credit risk models. Looking ahead The field of credit risk modeling for commercial loans is still developing, but its core principles have been readily accepted by banks and their supervisors. The next few years of industry practice will be crucial in developing key aspects of the estimation and calibration of the model parameters. (For a thorough survey of the issues, live Hirtle, et al. (2001). ) Resolution of these is sues is needed before supervisors and model users can be completely confident with the models outcomes.However, as banks gain additional modeling experience and more observations on changes in corporate credit quality, credit risk models should become an integral element of all banks risk measurement and management systems. Credit risk refers to the risk that a borrower will default on any type of debt by failing to make payments which it is obligated to do. 1 The risk is to begin with that of the lender and include lost principal and interest, disruption to cash flows, and change magnitude collection costs. The loss may be complete or overtone and can arise in a number of circumstances. 2For example * A consumer may fail to make a payment due on a mortgage loan, credit card, line of credit, or other loan * A company is unable to repay amounts secured by a fixed or floating charge over the assets of the company * A cable or consumer does not pay a trade invoice when due * A busi ness does not pay an employees earned final payment when due * A business or government bond issuer does not make a payment on a coupon or principal payment when due * An insolvent insurance company does not pay a policy obligation * An insolvent bank wont return funds to a depositor A government grants failure protection to an insolvent consumer or business To reduce the lenders credit risk, the lender may perform a credit civilise on the prospective borrower, may require the borrower to take out tolerate insurance, such as mortgage insurance or seek pledge or guarantees of third parties, besides other possible strategies. In general, the high the risk, the higher will be the interest rate that the debtor will be asked to pay onTypes of credit risk Credit risk can be classified in the following way3Credit default risk The risk of loss arising from a debtor being incredible to pay its loan obligations in full or the debtor is more than 90 days past due on any temporal credit obligation default risk may impact all credit-sensitive transactions, including loans, securities and derivatives. * Concentration risk The risk associated with any single exposure or group of exposures with the potential to produce large enough losses to peril a banks core operations. It may arise in the form of single name concentration or industry concentration. awkward risk The risk of loss arising from a sovereign state freeze foreign currency payments (transfer/conversion risk) or when it defaults on its obligations (sovereign risk).Assessing credit risk Main articles Credit analysis and Consumer credit risk Significant resources and school programs are used to analyze and manage risk. 4 Some companies run a credit risk department whose job is to assess the financial health of their customers, and extend credit (or not) accordingly. They may use in house programs to give the sack on avoiding, reducing and transferring risk. They likewise use third party provided inte lligence.Companies uniform Standard & Poors, Moodys, Fitch Ratings, and Dun and Bradstreet provide such information for a fee. Most lenders employ their own models (credit score card) to rank potential and existing customers according to risk, and then apply appropriate strategies. 5 With products such as unsecured personal loans or mortgages, lenders charge a higher price for higher risk customers and vice versa. 67 With revolving products such as credit cards and overdrafts, risk is controlled through the setting of credit limits. Some products also require security, most commonly in the form of property.Credit scoring models also form part of the framework used by banks or lending institutions grant credit to clients. For corporate and commercial borrowers, these models generally have qualitative and quantitative sections outlining various aspects of the risk including, but not limited to, direct experience, management expertise, asset quality, and leverage and liquidity ratio s, respectively. Once this information has been fully reviewed by credit officers and credit committees, the lender provides the funds subject to the price and conditions presented within the contract (as outlined above).