Counterparty Risk Intermediation
After completing this reading, you should be able to: Identify counterparty risk intermediaries,... Read More
After completing this reading you should be able to:
The word “credit” is derived from the ancient Latin word credere, which means “to believe” or “to entrust.” In the world of finance and investment, credit refers to a contractual agreement in which a borrower receives something of value now and agrees to repay the lender at a later date – generally with interest. Credit is built upon a foundation of trust. The borrower can meet obligations as set out in the contract or fail to so, a situation that can lead to loss for the lender. As such, the lender must assess the likelihood that the borrower will pay back the loan in accordance with the terms of the agreement.
Credit risk is the probability that a borrower will not pay back a loan in accordance with the terms of the agreement. It is the risk of loss caused by consumer default on credit products, including amortized loans, credit cards, revolving credits, and residential mortgages. Credit risk can arise in different ways. For example, it can emerge when:
For retail banks, credit risk is simply unavoidable. Banks receive deposits from customers and then lend the money to individuals and firms. In this process, every borrower is associated with some level of credit risk. However, the incremental risk of any single risk exposure is small. A single obligor is not big enough to threaten the operations of the bank.
To manage credit risk, banks invest heavily in credit analysis models that estimate future default rates and related losses. They also use a range of risk mitigants such as loan guarantees and collateral.
The variables most directly affecting relative credit risk include:
The four primary components of credit risk evaluation are as follows:
Risk mitigants make it easier for the obligee to decide whether to grant the obligor a facility. The obligee will often determine the market value of collateral so as to determine whether it is sufficient to cover potential losses. To do this, they might engage the services of a professional asset valuer. Key questions under this component are therefore as follows:
Qualitative credit risk analysis uses subjective judgment based on non-quantifiable information, such as management expertise, industry cycles, and the amount (and strength) of research and development. Qualitative analysis is used to gauge the obligor’s willingness to pay, which is a subjective attribute.
Qualitative analysis can be described by the acronym 6Cs derived from the first letters of the areas taken into account in the analysis:
Some of the qualitative techniques often used include:
In general, qualitative credit risk analysis looks at three key things about a company:
Quantitative credit risk analysis involves primarily an insight into past, current, and forecasted financial statements of the prospective obligor. These include the balance sheet, income statement, and cash flow statement. Qualitative analysis is used to gauge the obligor’s ability to pay.
While scrutinizing financial statements, the obligee assesses the obligor’s liquidity, revenue streams, receivables, existing assets, liabilities, and all outstanding obligations to various stakeholders such as suppliers.
Quantitative analysis, however, has several limitations:
Bottom line: The best credit analysis must combine quantitative techniques and qualitative judgments. Financial statements have their shortcomings and credit analysis must, therefore, be a synthesis of quantitative tools and sound qualitative judgments.
There are four main categories of borrowers, which gives rise to four types of credit analysis:
Consumer credit analysis is the evaluation of the creditworthiness of individual consumers.
The most basic measure of an individual’s ability to honor their obligations involves assessing their net worth. The other important indicator of ability to pay is the borrower’s cash flow stream – both inflows and outflows such as rent and salaries receivable, respectively. Since for most individuals, earnings and cash flow are generally equivalent, income and net worth provide the fundamental criteria for measuring their capacity to meet financial obligations.
Consumer credit analysis is a fairly simple process and it is not uncommon to find lenders using statistical tools to correlate risk to a fairly limited number of variables. Furthermore, extensive credit analysis often does not make economic sense because the amounts advanced are comparatively small.
Here, the analyst evaluates the creditworthiness of nonfinancial firms. Businesses are typically more difficult to analyze than individuals, although the process is similar. The income streams, asset, and liability values of businesses are more volatile.
The credit analysis process is usually detailed because the amounts advanced are relatively large. While evaluating the creditworthiness of a nonfinancial obligor, the lender is particularly concerned with the company’s liquidity, cash flows, near-term earnings capacity and profitability, and solvency position. Each of these attributes is relevant also to the analysis of financial companies.
Financial institution credit analysis is the evaluation of financial companies including banks and nonbank financial institutions (NBFIs), such as insurance companies and investment funds. As with corporate credit analysis, liquidity, solvency, earnings capacity, the quality of management, the state of the economy, and the industry environment are vital factors in evaluating financial company creditworthiness. However, financial institution credit analysis differs from corporate credit analysis in two main ways:
An institution’s earnings capacity over time is a more relevant indicator of creditworthiness than cash flow.
Sovereign/municipal credit analysis is the evaluation of the credit risk associated with the financial obligations of sovereign states and subnational governments. The creditworthiness of a state has implications for the creditworthiness of non-state entities operating in specific jurisdictions.
There are several measures used to assess the creditworthiness of a firm:
The probability of default measures the likelihood of the obligor defaulting on the terms of a contract.
While highly relevant to what constitutes “good credit” and “bad credit”, probability of default is often not the creditor’s central concern. That’s because a borrower may briefly default and then quickly correct the situation by making a payment, going as far as to pay up interest charges or penalties for missed payments. Non-payment for a limited period of time can cause the lender some financial strain particularly if the lender happens to be relying on the cash flows to meet their own obligations, but otherwise, the tangible harm would be negligible. As a result, creditors tend to rely on other measures of risk in addition to PD.
PD is expressed as a percentage.
Loss given default (LGD): LGD represents the likely percentage loss if the borrower defaults. The severity of a default is equally as important to the creditor as the probability of default itself.
A default event can be brief such that the borrower immediately makes the required payments resulting in a negligible loss for the lender. In such a scenario, the creditor would not be too alarmed. On the other hand, if payment ceases and no further revenue is ever received by the creditor, a substantial loss is incurred.
The probability of default and the severity of the loss as indicated by the loss given default are crucial in determining the tangible expected loss to the creditor.
Like the PD, LGD is expressed as a percentage.
Exposure at default is the total value the creditor is exposed to when a default event occurs. EAD may be expressed either as a dollar amount (i.e., outstanding loan balance) or as a percentage of the nominal amount.
Expected loss for a given time horizon is calculated as the product of the PD, LGD, and EAD \(\left( \text{i.e.,}\text{PD}\times \text{LGD}\times \text{EAD} \right) \).
The longer the time horizon (i.e., tenor of the loan), the more likely it is that a default will occur. Both the EAD and LGD change with time, where the former increases as the borrower draws on a credit line loan is fully drawn and decreases as it is gradually repaid. LGD can change over time, where the nature of the change is contingent on the specific terms and structure of the loan.
Prime Bank has examined its loan portfolio over the past 1 year and concluded the following:
Calculate the expected loss given a one-year time horizon
Solution
$$ \text{EL}=\text{PD}\times \text{LGD}\times \text{EAD}=\text{5}\%\times \text{70}\%\times \text{60}\%=\text{2.1}\% $$
Bank insolvency can be defined as a bank’s inability to pay its debts. This can happen in two ways:
Bank failure is the closure/collapse of a bank plagued by insolvency by a federal or state regulator. It results in significant losses to depositors and creditors.
In the 21st century, banks regularly run into solvency issues but very few fail. The main reason behind this is that the failure of a bank often has huge implications on the economy as a whole and regulators/governments do everything possible to prevent this from happening. As a result, regulators find it more convenient and less expensive to simply fold an insolvent bank through a merger or acquisition, resulting in a stronger bank. This is especially true for systematically important banks (SIBs) that are considered too big to fail.
Statistics seem to back up the claim that banks rarely fail. In the United States, for example, only 50 banks failed between 2001 and 2008, half of which failed in 2008 at the height of the financial crisis. This equates to a rate of approximately 0.1% per year during the period. In the aftermath of the crisis, approximately 2% of banks failed in both 2009 and 2010. An additional 1.2% of banks failed in 2011. Furthermore, research has shown that nonfinancial institutions fail more often compared to banks.
In a bid to avoid financial stress and possible failure, banking regulators around the globe have come up with a range of preventative measures. For example, the Financial Stability Board has crafted additional capital requirements to improve the loss absorption capacity of some 29 systematically important financial institutions. This is informed by the fact that the failure of a SIB has a spillover effect that causes severe financial strain to other financial institutions.
Apart from mergers and acquisitions, banks are often bailed out by governments. The Federal Reserve, for example, acts a lender of last resort and often injects capital into banks under financial strain to forestall impending failure.
Although bank failures are rare, continuous credit analysis is important:
Practice Question
According to the type of borrower, credit analysis can be categorized into which of the following four areas?
A. Character, reputation, credit record, creditor’s right and legal system
B. Consumers, government and government-related entities, financial companies, and non-financial companies.
C. Character, capacity, capital, and collateral
D. Probability of default, loss given default, exposure at default, expected loss.
The correct answer is B.
According to the type of borrower, credit analysis can be categorized into 4 areas: consumers, government and government-related entities, financial and non-financial (corporate) companies.
Option C is the 4’Cs of Credit, which is to know the creditworthiness of a business/individual.