The Bases Of Credit Risk In Banks Finance Essay - Free Essay Example

Sample details Pages: 9 Words: 2771 Downloads: 8 Date added: 2017/06/26 Category Finance Essay Type Essay any type Did you like this example? According to European Central Bank, credit risk is defined as à ¢Ã¢â€š ¬Ã…“the risk that a counterparty will not settle the full value of an obligation à ¢Ã¢â€š ¬Ã¢â‚¬Å" neither when it becomes due, nor at any time thereafterà ¢Ã¢â€š ¬?; similarly, credit risk is the risk that a borrower will not meet its obligations according to agreed terms (Basel, Jul 1999). As Greuning, H.V and Bratanovic, S.B (2003) pointed out, bank failures mostly generated from credit risk due to the fact that more than 80% of the balance sheet of a bank commonly has the relation to this kind of risk. Therefore, a good management of credit risk is vital for the operation of a bank. Don’t waste time! Our writers will create an original "The Bases Of Credit Risk In Banks Finance Essay" essay for you Create order 3.1.2 Credit Risk Exposures in Banks According to Basel (Jul 1999), making loans is still the activity where credit risk rises from mostly. Additionally, along with financial innovation creating new financial instruments like: acceptances, interbank transactions, guarantees and acceptance (Basel, Jul 1999). Hence, this paper will discuss credit exposure of banks existing in these activities. Loan According to Gregoriou and Hoppe (2008), bank loans are categorised as commercial real estate (CRE), commercial and industrial (CI) loans and consumer loans. Frumkin (2005) stated that CI are loans made by commercial banks, representing loans outstanding; moreover, CI can be made from a few weeks to several years and this kind of loans are sources of capital for production. (Saunders and Cornett, 2006). Beside this, CRE are primarily mortgage loans; in terms of size, price and maturity, CRE is different to CI. Moreover, consumer loans made by lenders like banks and other financia l institutions create the only income is interest payment (Gregoriou and Hoppe, 2008). Undoubtedly, when making loans, the risk that banks concern mostly is credit risk. Due to many causes, bank borrowers may fail to repay their debts, possibly leading to bankruptcy (Gregoriou and Hoppe, 2008). Guarantees and Acceptances As the Basel Committee defined (1986), Guarantee is the commitment of a bank to help a third party complete its obligations if the third party cannot do it, while Acceptances is a bankà ¢Ã¢â€š ¬Ã¢â€ž ¢s obligation to pay on maturity the nominal value of a exchangeà ¢Ã¢â€š ¬Ã¢â€ž ¢s bill. Guarantees and Acceptances are considered as loans to ultimate borrowers; hence, they are also considerable sources of credit risk of banks (Basel, 1986). Interbank transaction According to Interbank Liability of US Department of Treasury, interbank transactions like swaps and foreign exchange contracts create exposure to banks that act as counterparties in such tra nsactions. This exposure may include settlement risk possibly coming from transactions related to the government securities or foreign exchange that a counterparty will fail to fulfil a payment as agreed terms. As a result, banks also need to pay attention to this kind of credit risk source. 3.2 PRINCIPLES OF CREDIT RISK MANAGEMENT IN BANKS 3.2.1 Purposes of Credit Risk Management As other businesses, the target of a bank is also maximising its profit; hence, the purpose of credit risk management in each bank is to diminish losses caused by credit risk but reach the maximum profit. This is the optimal combination between risk and profit. In other words, à ¢Ã¢â€š ¬Ã…“the intent of a banks risk management processes is to avoid having an unacceptable number of credits that go into insolvency, workout, restructuring, etc. and then to minimise the actual lossesà ¢Ã¢â€š ¬?  [1]  . According to Basel (Jul 1999), the purpose of credit risk management is to maximise a bankà ¢Ã¢â€š ¬Ã¢â€ž ¢s return by controling credit risk exposure within acceptable levels. 3.2.2 Principles of Credit risk Management Coping with credit risk management, each bank has its own strategies and policies; however, the Basel Committee on Banking Supervision establishes common standards on this issue. This paper will base on these criteria to depict crucial factors needed for a good framework credit management. According to Basel (Jul 1999), principles of credit risk management of banks should satisfy the following five criteria: Establishing an Appropriate Credit Risk Environment This standard requires each bank to set up its own conception, strategies and policies as well as organisations for credit risk management. Firstly, the board of directors should approve the acceptable level of the combination between credit risk and profitability. Then, managers- responsible for credit risk management should base on the approved strategies to carry out policies and implem ents for all activities and products of the bank. Operating under a Sound Credit Granting Process Having deep knowledge about their borrowers or counterparties as well as the structure of the credit and the ability of repayments is crucial for banks in determining the credit limit of each individual borrower or groups of counterparties. Thus in order to do that, banks need to build appropriate credit granting processes. The determining of the credit limit must been available for both circumstances of granting credit for new credit and extensions of existing credit. Maintaining an Appropriate Credit Administration, Measurement and Monitoring Process These processes must be applied for credit- bearing portfolios, monitoring the overall component of these portfolios. Additionally, banks should develop internal credit rating systems which need to fit the size, structure, activities of them. An internal credit rating system is an indicator of the risk in an individual credit in indentified by banks (Frenkel, Hommel, Dufey and Rudoff, 2005). This system should be applied at the beginning of the lending and updated regularly (Monetary Authority of Singapore, 2006). However, the Basel Committee make a suggestion that the framework of administration, measurement and monitoring of credit risk should estimate credit risk exposures in possible changes and stressful conditions. Ensuring Adequate Controls over Credit risk Banks need to establish a credit review system that board of directors need to be informed about reports and assessments of such credit review system regularly and directly. Banks must make sure that the credit risk exposures are within the approved level. Moreover, once weaknesses or problem credits appeared, bank should be ready to manage them. 3.3 CREDIT RISK MEASUREMENT Jickling (2010) argued that one of the causes resulting to the current financial crisis is the weakness of risk management systems including credit risk measurem ent. As Colquitt (2007) pointed out, credit risk measurement plays a vital role in the framework of credit risk management, becoming a major agenda at financial institutions over the past few years. There may be two main reasons leading to this role of credit risk measurement. Firstly, the increasingly complex financial risks cause large losses; hence, they need to be managed by quantifying and measuring the potential risk exposures. The second reason is that credit risk is intimately related to other risks like market and operational risks; as a result, to manage properly these integrated risks need a systematic process that can measure the loss exposures in all activities. The dissertation will analyse three methods for credit risk measurement of banks, including: credit risk rating, credit risk scoring and credit risk modelling. 3.3.1 Credit Risk Rating Credit rating systems are tools to assess creditworthiness, estimate default probability according to rating categories an d they are à ¢Ã¢â€š ¬Ã…“at the heart of credit risk management in that they provide a road map to entire credit processà ¢Ã¢â€š ¬? (Colquitt, 2007, p 318). Moreover, according to OCC (2001), credit risk rating systems may enhance safety and soundness, monitoring changes and trends in credit risk levels, helping banks reach optimal returns. Chen (2003) argued that there are three types of credit rating systems helping lenders rate creditworthiness of borrowers or counterparties, such as: bank internal rating systems, external rating agencies and external credit agencies. Bank Internal Rating Systems It is mentioned by Basel (Jan 2000) that internal ratings, based on quantitative and qualitative information, show an evaluation of the risk of loss due to the counterpartyà ¢Ã¢â€š ¬Ã¢â€ž ¢s default. Internal credit rating systems are used for many purposes like determining problem loans, analysing to support loan loss reserving, being an element of credit portfolio monitoring and management, capital allocation, etc (Federal Reserve Board, Division of Banking Supervision and Regulation, 1998). In other words, a robust internal credit rating system is crucial in credit risk management processes, contributing to banksà ¢Ã¢â€š ¬Ã¢â€ž ¢ safety, soundness and success. External Rating Agencies External rating agencies are provided by public credit rating companies like Moodys Investors Service, Standard Poors and Fitch. Like bank internal rating systems, these rating agencies offer consistent credit scores, information and credit risk indicators to banks about the prospective creditworthiness of borrowers or obligors. Along with bank internal ratings, lenders rely on assessments of rating agencies in the hope of avoiding bias estimations existing in internal credit rating systems (Colquitt, 2007). On the other hand, users of analyses from external rating agencies should consider some negative features of them. Firstly, there is a conflict of interest as a result of the fact that external rating agencies are paid by organisations or companies they assess rather than by the user of ratings information. Secondly, external rating agencies have been criticised because of being too slow to adjust ratings when breakdowns happen  [2]  . The case of Thai Bahtà ¢Ã¢â€š ¬Ã¢â€ž ¢s downgrade can serve a stark example of this argument. In July 1997, Thai baht plunged in value as the result of the Asian financial crisis; however, both Moodyà ¢Ã¢â€š ¬Ã¢â€ž ¢s and Standard Poorà ¢Ã¢â€š ¬Ã¢â€ž ¢s did not downgrade Thailandà ¢Ã¢â€š ¬Ã¢â€ž ¢s long- term until October 1997. External Credit Agencies According to Chen (2003), the third type of rating systems, external credit agencies is less well- known, providing information of borrowers in the score value form rather than rating information. In terms of the availability of borrowers- evaluating information, this type of rating system possibly outperform both of the bank internal ratin g systems and the external rating agencies because a large range of firms in different industries an regions are covered by external credit agencies (Chen, 2003). 3.3.3 Credit Scoring Systems Another tool for enhancing lenders in making decisions related to risk management is the credit scoring system. Banks use credit scoring as a method of estimating credit risk of loan applications. Analysing historical data related to borrowers and loan applicants such as the applicantà ¢Ã¢â€š ¬Ã¢â€ž ¢s monthly income, debt, financial assets, whether the applicant has defaulted or been delinquent on a loan, the credit scoring system creates a result used to classify loan applicants or borrowers (Mester, 1997) . Mester (1997, p2) also argued that à ¢Ã¢â€š ¬Ã…“a well-designed model should give a higher percentage of high scores to borrowers whose loans will perform well and a higher percentage of low scores to borrowers whose loans will not perform wellà ¢Ã¢â€š ¬?. As Thomas, Edelman and Crook (2002) pointed out, the main role of credit scoring system is to decide who will get credit and how much credit they should get; however, one of the long- term limitations of the credit scoring system is that there exist borrowers who can get credit from all lenders and those who cannot get from at least one lender. 3.3.4 Credit Risk Models As Basel (Apr 1999) mentioned, credit risk models play an increasingly vital role in many banksà ¢Ã¢â€š ¬Ã¢â€ž ¢ activities, including risk management and performance measurement. There are two main roles of credit risk models. The first role is to analyse single counterparty or transaction in the portfolio, estimating the creditworthiness of the counterparty related to the structure of the transaction. Another one is to assess the entire transactions and counterparties to decide whether the portfolio fits into the risk profile of the bank (Frenkeel, M., Hommel, U., Dufey, G., Rudoff, M., 2005). Moreover, these models offer bank s a mechanism for evaluating credit risk, contributing to banksà ¢Ã¢â€š ¬Ã¢â€ž ¢ credit risk management (Basel, Apr 1999). This paper will examine types of credit risk models according to the classification of Smithson (2003) as these models are commonly used and possibly well- known. Structural Models As Smithson (2003) stated that structural models originated from in the Merton model which analyses the volatility between assets and liabilities. In 1974, Merton suggested a model evaluating a company in default if its assetà ¢Ã¢â€š ¬Ã¢â€ž ¢s value is below that of its liabilities (Jackson, Nickell and Perraudin, 1999). In other words, à ¢Ã¢â€š ¬Ã…“ the probability of a firm going bankrupt depends crucially on the beginning period market of that firmà ¢Ã¢â€š ¬Ã¢â€ž ¢s assets relative to its outside debt, as well as the volatility of the market value of a firmà ¢Ã¢â€š ¬Ã¢â€ž ¢s assetsà ¢Ã¢â€š ¬? (Altman and Saunders, 1998, p5). Among structural models, there are tw o models used commonly by financial institutions including: Moodyà ¢Ã¢â€š ¬Ã¢â€ž ¢s KMV Portfolio Manager and JP Morganà ¢Ã¢â€š ¬Ã¢â€ž ¢s CreditMetrics (Smithson, 2003). KMV Portfolio Manager considers the value of the firmà ¢Ã¢â€š ¬Ã¢â€ž ¢s asset as the stochastic variable while the Expected Default Frequency (EDFs) of each individual borrower that this model employs collected from Moodyà ¢Ã¢â€š ¬Ã¢â€ž ¢s KMV Credit Monitor or KMVà ¢Ã¢â€š ¬Ã¢â€ž ¢s Private Firm Model; then, basing on historical data, this model produces loss distribution (Smithson, 2003). Figure 3.1: Sources of Probability of Default for Portfolio Manager KMVà ¢Ã¢â€š ¬Ã¢â€ž ¢s Credit Monitor KMVà ¢Ã¢â€š ¬Ã¢â€ž ¢s Portfolio Manger KMVà ¢Ã¢â€š ¬Ã¢â€ž ¢s Private Firm Model EDFS EDFs Source: Smithson, 2003. Another model based on the Merton approach is JP Morganà ¢Ã¢â€š ¬Ã¢â€ž ¢s CreditMetrics which is a system for analysing credit risk in portfolios. According to JP Morgan (1997), this model use Monte Carlo simulation to measure VAR to estimate a portfolio loss. The measurement mechanism of CreditMetrics is showed at Figure 3.2. The probability of rating migration is determined by a transition matrix. Both CredtiMetrics and Portfolio Manager assume that firmà ¢Ã¢â€š ¬Ã¢â€ž ¢s asset returns are produced by a set of common risk factors with factors related to the features of firms, industries and countries (Jackson, Nickell and Perraudin, 1999) Figure 3.2: CreditMetrics framework source: JP Morgan, 1997. Macrofactor Models According to Jackson, Nickell and Perraudin (1999), CreditPortfolioView is the most commonly used of macrofactor models, measuring only default risk and taking into account the relationship between macroeconomic conditions and default probabilities by using Monte Carlo simulation to assess default probabilities. Moreover, the time series of default rates per sector are the most crucial data input in using Mente Carlo simulation macroeconomics climates (Kern and Rudolph, 2001). This argument is illustrated in table 3.1. Table 3.1: CreditPortfolioView-data input source: Kern and Rudolph, 2001 Actuarial Models According to Smithson (2003), actuarial models indentify default rates and loss events and among this kind of model, Credit Risk+, proposed by Credit Suisse First Boston, is perhaps best known. In Credit Risk+, only credit risk from defaults is analysed and default rates are considered to be stochastic, not constant over time but possible fluctuate over the credit cycle. The data input of Credit Risk+ include default rates per country- industry segment and those for the individual credit exposures (Kern and Rudolph, 2001). à ¢Ã¢â€š ¬Ã…“Recovery rates are taken as constants or alternatively only exposures net of collateral are used for the calculation of losses. Then à ¢Ã¢â€š ¬Ã¢â‚¬Å" for a big portfolio of homogenous and independent loans with the same exposure and the same default rates à ¢Ã¢â€š ¬Ã¢â‚¬Å" the probability that exactly defaults will happen in the portfolio approximately follows the Poisson distributionà ¢ â‚ ¬? (Kern and Rudolph, 2001, p10). The measurement framework of Credit Risk+ is demonstrated in the Figure 3.3. Figure 3.3: Credit Risk+ framework source: Credit Suisse, 1997 3.4 CREDIT RISK MITIGATION TECHNIQUES In the credit risk management framework, credit risk mitigation techniques play a crucial role, applied throughout the risk management with the aim of avoiding and minimising losses. Along with the development of financial instruments, there are a handful of such techniques that are applied dependent on the size, business strategies of banks or national characteristics (Basel, Jan 2000a). This section will examine commonly- used credit risk mitigation approaches such as: collateral, credit limits, netting agreements and credit derivatives. Collateral It may be one of the most popular and basis methods of banks and financial institutions for reducing credit risk. When appearing the event of default, the ownership of properties of borrowers used as collateral in lending agreements will be given to banks; thanks to this, losses are offset partly through the sale of properties (OCC, 2001). However, as Horcher (2005) argued, in the circumstance of devalued collateral assets, counterparties would be required to provide additional collateral. Credit limits According to Horche (2005), credit limits are a useful mitigation approach in minimising exposure to sectors, regions or sovereign governments by granting maximum contract size or maximum term limit to these categories. As the result, banks need to have deep knowledge and understanding about their customers in order to increase the effectiveness of this method. Netting agreements Netting agreements are used to net exchanged amounts between two counterparties. This method, specially applied commonly for interbank transactions when banks are borrowers and lenders of each other, reduces interbank credit exposure by shifting credit risk to bank creditors who do not claim in the netting agreements (Emmons, 1995). Credit derivatives As Horcher (2005) defined, Credit derivatives are contractual agreements based on credit perfo rmance related to predetermined events such as default, insolvency or bankruptcy and non fulfilment of loan obligations. This approach is used through the transfer agreed loanà ¢Ã¢â€š ¬Ã¢â€ž ¢s credit risk from the protection purchaser- the creditor bank to the protection seller, as a result they have the ability to support participants to offset risk arising from their core businesses (Horcher, 2005).