Chapter 8 Credit Risk Management – Essentials of Financial Risk Management


Credit Risk Management

What Is Credit Risk Management?

Credit risk management is managing the risk that financial obligations are met, or not met as the case may be. There are two aspects of credit risk management. There is the internal aspect of credit risk management, which is insuring that the organization has the financial wherewithal and financial flexibility to meet its outstanding as well as potential outstanding financial obligations. The second aspect is external credit risk or ensuring that the customers of the organization are able to fulfill their financial obligations and debts to the organization.

Internal credit risk management is important as it firstly affects the solvency and long-term viability of the organization. There are very real costs of bankruptcy or distressed financial health that are both explicit as well as implicit. Bankruptcy is expensive legally and financial stress leads to higher financing costs, loss of customer loyalty, difficulty in keeping and attracting good employees, worsening of relationships with suppliers, a loss of financing flexibility, and a resulting level of underinvestment that prevents the company from remaining competitive in its industry.

External credit risk management is a balance between extending credit to customers in order to enhance or maintain sales and a positive relationship and goodwill against the possibility that payment may be delayed or even not forthcoming. Credit policy is frequently a major component of the marketing package. Consider the financing packages used by automobile manufacturers or furniture dealers and how it plays to their marketing strategy to attract new customers and maintain existing customer relations.

Both the internal credit risk as well as the external credit risk need to be managed. However, in this book, we will focus on the external credit risk management and leave the internal credit risk management to the financial management books. However, the metrics used for external credit risk analysis should of course be used to monitor one’s own credit risk. Having an understanding of how one might be viewed by others is prudent risk management.

Credit risk management is one of the financial risks that the firm often neglects or pays insufficient attention to until it is too late to develop an effective plan. In part, because of this we often see credit risk arise as a systemic event as it was during the 2008 financial crisis. It takes only a small sector of the economy to start defaulting—or even to have an increasing risk of default—for cascading effects to occur that affect large parts of an industry or even an economy.

Like all financial risks, credit risk tends to be dynamic. It is well known that overall in the economy that companies, and indeed sectors of the economy, tend to get weaker financially than they tend to get stronger. This implies that credit risk needs to be reevaluated on a regular basis. It is most certainly not a one-time event, although due to the nature of how personal credit works—for instance, credit cards—the instinct is to assume that once one is considered to be an acceptable credit risk that one will always remain an acceptable credit risk.

There are a couple of ways though in which the nature of credit risk differs significantly from the other financial risks covered in this book. The first is that credit risk has a definite cut-off—namely that the firm suffers a credit event in which it fails to meet a financial obligation; you are either in default or you are not. For all other financial risks, prices can move more or less to any level up or down. With a definitive credit risk, there is basically a zero—one effect. The firm can be meeting its financial obligations or it is not. This is highlighted when a firm goes bankrupt. While a firm can obviously be in better credit health than its peers or in worse credit health than its peers, the reality is that in the eyes of business law, a firm is either meeting its credit obligations or it is not. There is a close analogy with a biological organism; it is either alive, or it is dead. There is no Schrödinger Cat like phenomenon where an entity can be a certain percentage bankrupt, although admittedly there are different levels of financial distress.

A second difference is that credit risk is frequently considered to be a one-way risk; credit risk is for all intents a bad risk with only very limited upside potential. With all of the other financial risks discussed so far, there is a possibility that the risk could be a good risk (prices move in one’s favor), or a bad risk (prices move against one’s favor). With a few minor exceptions, credit risk can only be bad. For example, it is rare to find an organization with financial obligations paying back more than they are legally obligated to.

This leads to the third difference of credit risk which is in regards to the correlation of credit risks. As has already been discussed, financial risks tend to be correlated. This is true for credit risk as well, but only to a certain point. The correlation of credit risks can have some unusual and counter-intuitive outcomes. The first is the difficulty of uncovering when the credit risk of an organization is an idiosyncratic event or a systemic event. An organization could be in financial distress due to systemic factors or due to totally idiosyncratic factors. However, even if financial distress is a function of systemic factors, the correlation can change suddenly for one or more of the correlated firms. Take for instance the case of GM and Ford during the 2008 crisis. The credit health of both firms deteriorated in a highly correlated fashion as the crisis began to spread and endure. However, when GM filed for bankruptcy, the credit risk of Ford counter-intuitively improved. The cause of this was that as one of the major competitors found itself handcuffed (temporarily) by filing for bankruptcy, that in some sense gave Ford more freedom to exploit whatever market opportunities there were at the time and actually improve its probability of not going bankrupt. Thus, while one of the highly correlated companies filed for bankruptcy, the credit correlation reversed course and the two companies for a while became inversely correlated in their respective credit risks.

There is a final element that distinguishes credit risk. It is a difference that is frequently overlooked, in part due to its subtleness. Credit risk is frequently caused by an unforeseeable event or a series of unforeseeable events. For instance, with the exception of the issuance of credit cards (which are analyzed and assessed in an entirely different manner), financial institutions almost never extend credit to a counterparty that they expect to fail. Financial institutions understand that in the aggregate that they will experience credit losses, but for each individual credit they extend credit to they do so only if they are highly confident that the credit will be repaid. Thus, when a credit event does occur, it is almost always because of an unexpected event or a series of events. We expect financial prices to go up or down; we do not expect creditors to fail, yet of course we know that they do.

This subtle difference has major implications for analyzing credit risk. Since credit events tend to be unique and specific to the context, we have to be very careful in applying traditional probability-based techniques. It is related to the frequency bias that was discussed in Chapter 4. The mathematics of determining who will go bankrupt is different and the mathematical nature of the losses is also different from the other financial risks. The losses from credit risk are sudden and large; they are not a matter of degrees like they are with other financial risks. For instance, a small interest rate move may imply a small change in financial position while a large interest rate move will likely imply a larger change in financial position. With credit risks it is either no loss, or a loss. Furthermore, if it is a loss, then it generally is a significant loss. It is a subtle difference but one that has profound effects for how one measures credit risk effects, and makes the task of pricing credit risk far more difficult.

In terms of financial risks, credit risk may be one of the simplest to comprehend, perhaps because it is the one that almost everyone deals with in their day-to-day personal lives. However, the fact that it is considered simple to understand does not mean that it is easy to master. Credit risk may be one of the subtlest of the financial risks, and this in turn makes it one of the trickiest to manage well.

Credit Derivatives

In the mid-1990s, a new type of derivative called the credit default swap was developed. Credit default swaps dramatically changed the world of credit analysis and gave traders a way to trade, and thus price pure credit risk. When trading a bond, you are in essence trading the underlying interest rate of the bond, plus the associated credit risk, or credit spread on the bond. The reason that bond price changes are thus not always a good way to assess credit risk is that the change in the interest rate component inherent in the price of the bond was generally of much greater magnitude than the change in the level of credit risk. The rise of credit derivatives changed all of that and provided an instrument whose value depends solely on credit risk.

The credit default swap is the basic building block of credit derivatives. In a credit default swap, the credit protection buyer pays a periodic fee, generally semi-annually, to the credit protection seller. The credit protection seller in return makes a payment to the protection buyer if, and only if an underlying reference credit, generally linked to a corporate bond, suffers a credit event such as a default or a bankruptcy. The size of the payment is based on a notional amount multiplied by 1 minus the recovery rate on the reference asset. Figure 8.1 illustrates this.

Figure 8.1 Credit default swap

So for illustration, assume that the credit default swap was based on a notional amount of $10MM. Also assume that 3 years into the 5-year swap that ABC went bankrupt and the resultant price of their bonds that were trading at 37 percent of face value, which would indicate that investors expected to recover $0.37 for every dollar that they were owed. In this case, the protection seller would make a payment to the protection buyer of $6.3MM ($10MM multiplied by 1 minus the recovery rate of 37 percent). In this way, the protection buyer has protected themselves from a default of ABC company.

Credit default swaps provide a very simple and straightforward way to hedge credit risk. A side benefit of this market is that market forces are setting the credit default swap price. As a company’s credit health deteriorates, the price for buying protection through a credit default swap will increase. Likewise, as a company’s credit health improves, the price of a credit default swap referenced to it will decrease. Thus, the credit default swap price on a company is a very timely and relatively accurate way to assess the credit health of a company.

Credit Risk Metrics

Besides credit default swaps, there are a wide variety of credit risk metrics that can be used to assess the financial health of an organization, or even a person. The first concept to understand about credit risk is the difference between credit exposure and expected loss due to a credit event. Exposure is the size of the outstanding credit. It is the size of the loss one would experience if there was a credit event and nothing was recovered in terms of payment from the counterparty. For credit obligations such as a loan, calculation of the exposure is simply the size of the loan outstanding. However, with other credit-related obligations such as derivative contracts with counterparties, the potential exposure is uncertain, as the size of the future net derivatives payments is generally unknown. In such cases, the exposure is generally taken to be the maximum expected size of the credit obligation.

The expected loss on a loan is the multiple of two components: the expected loss given a credit event and the probability of a credit event occurring. The expected loss given that a credit event has occurred can be a function of many different factors. The primary factor though is the value of the collateral. That is why it is relatively easier to get credit to buy a house. A house acts as very good collateral, so if there is a default, the lender can seize property that will have significant value and thus the expected loss given a default will be low. Conversely, this is also why you generally cannot get consumer credit on perishable goods.

To assess credit, one of the first variables to look at is a company’s credit rating, or a person’s credit score. The credit rating of a company gives an overall view from an independent source (the credit rating agency) of how likely it is that a creditor will receive full payment on their credit extension. Generally, credit ratings of BBB or better are considered to be “investment grade” or relatively safe, with a BBB-rated company having less than a 0.2 percent probability of defaulting within a year.1

There is a major caveat with corporate credit ratings; ratings tend to be relatively sticky. Rating agencies for a variety of reasons tend to be loath to change ratings. To avoid having to change ratings every time economic conditions change, rating companies examine a company over an assumed business cycle. This evens out possible fluctuations due to changing business conditions, but it also implies that ratings may be misleading if economic conditions are poorer than usual.

One interesting side fact about credit ratings is that the rating agencies take into account the strength of a company’s risk management systems as part of their ratings analysis, which gives corporations yet another reason to practice good risk management.

Altman Z-Scores

A second method to assess the credit quality of a company is to examine what is known as their Altman Z-score. The Altman Z-score was developed by the academic Edward Altman. In his analysis, he looked at a variety of factors and developed the following equation and set of factors:

Z-score = 1.2 × F1 + 1.4 × F2 + 3.3 × F3 + 0.6 × F4 + 0.999 × F5


If the calculated Z-score is below 1.80, then there is a high probability of the company encountering financial distress. If the Z-score is above 2.99, then the company is considered to be a safe credit risk. Values of the Z-score between 1.80 and 2.99 are considered to be indeterminate in terms of credit quality.2

Related to the Altman Z-score which is used for corporate credits are credit scoring techniques for individuals. Like the Altman Z-score, these proprietary credit scores take into account a wide variety of different factors including past payment history, level of education, length of time in a given residence, and a host of other factors. Credit scores are based on statistical techniques and do not necessarily take into account the specific situation of a given individual.

The Five (Six) Cs of Credit Analysis

One credit analysis technique that examines the specifics of a company is what is known as the five Cs of credit analysis, which was heavily used by bankers in the past. To this list, many financial institutions have added a sixth factor. These factors are: (1) Character, (2) Capital, (3) Capacity, (4) Collateral, (5) Conditions, and more recently, (6) Compliance.

Character can simply be stated as the willingness of the counterparty to pay. Certain companies, and indeed certain individuals, develop a reputation for being slow to pay or finding reasons to not pay or dispute the size and terms of the payment. Experienced credit officers will tell you that character is by far the most important of the analysis of credit risk that they perform. Bankers in particular will tell you that they would rather deal with a borrower with good character and poor capacity to pay, than one with a perfect capacity to pay but poor character. When dealing with large organizations, character is often less of a factor unless it is a tightly controlled firm with a dominant personality in control. Character becomes more of an issue with smaller firms, where there is more likely to be such a dominant individual who sets the tone for the firm in dealings with counterparties. Ironically, as credit analysis has come more under the auspices of big data, the role of character has regrettably taken a diminished role. Character is assessed through personal relationships or more likely through the credit and payment history of the organization. The one caveat of relying on history to assess credit character is that true character can only be truly assessed in times of stress. It is generally quite easy to have good credit character if one has never had financial stress.

Capital involves the analysis of the existing financial reserves of an organization. Obviously, the larger the financial reserves, the smaller the credit risk of an organization is likely to be. Capital is related to the old joke of the bank being more than willing to lend you money when you don’t need it, but loath to lend when you most need the money.

Capacity is the ability of the firm to pay. Although many financial ratios are used to assess capacity to pay, the most important metric for measuring capacity is perhaps the coverage ratio, or the ratio of cash inflows to the firm divided by the required cash outflows required to keep the organization in good credit standing. The debt-to-equity ratio is also a key component. In particular, the debt-to-equity ratio relative to industry peers. Common wisdom tells us that companies in the same industry should face similar growth opportunities and similar levels of risk and thus should have similar debt-to-equity ratios. It is considered a red flag if a company has a much higher debt-to-equity ratio than its industry peer group.

Collateral is what can be recovered if the counterparty cannot pay. The presence of collateral makes the granting of credit for certain purposes much easier. For instance, household mortgages are quite easy to secure as there is readily available collateral. A liquor store, however, is far less likely to be extended credit as the assets are far less collectible after they have been used.

Conditions are the state of the economy or the industry at the time that the credit question is being posed. As with many financial variables, there are cycles to credit; namely, there are times when the economic conditions are prime for credit and during such times credit is readily available at attractive prices. Conversely, there are periods where the economic conditions in general, or the conditions for a specific industry are far from ideal and during such times credit is much more expensive to obtain, or perhaps unobtainable at any reasonable cost. During the height of the financial crisis this was certainly the case, when even the most financially secure of companies had difficulty obtaining credit financing as investors preferred to hold cash given the level of economic uncertainty.

To these traditional five components of credit analysis, many lenders, and in particular financial institutions, have added the sixth metric of compliance. In large part, this is a reaction to regulatory concerns placed on financial institutions in the wake of the events of 2008. However, it also makes sense as it relates to not only regulatory compliance but also issues such as reputation, cyber security, and even strategic risk. For instance, no one wants to be accused of extending favorable credit terms to a criminal organization or a terrorist organization.

Together, the five/six Cs of credit risk determine to whom one might extend credit and the extent of that credit. Once the decision has been made to extend credit, the next step is to develop a credit policy.

Developing a Credit Policy

The credit policy of a firm is the conditions under which the firm will extend credit to its customers. Components of a credit policy include; (1) whom to extend credit to, (2) how much credit to extend, (3) the terms under which the credit will be extended, (4) how the credit will be monitored, and (5) what will be done if the credit terms are not fulfilled.

The terms of credit are not only a credit risk decision but also a financial cost decision. Extending credit has an explicit cost as the organization that is extending the credit has to; (a) source the financing for the credit, (b) pay for that source of financing, and (c) pay for the additional monitoring costs of monitoring the credit. Obviously, the terms of the credit risk need to take into account the sales effect versus the need to offset the cost of financing the credit extension.

In determining whom to extend credit to, a company will generally establish a minimum level of credit quality. This could be based on credit rating, credit score, maximum credit default swap price, or an internal credit analysis based on the five Cs of credit. It is also likely at this step the company will have tiers of credit quality that they will extend credit to, with better tiers of credit quality being granted larger amounts of credit and at better credit terms.

Once the decision has been made to extend credit, the next step is to determine how much credit to extend. The extension of credit, and the amount of credit extended can have a major impact on sales. Generally, the amount of credit to extend is a function of the credit analysis, the size of the customer and their ability to service the credit, and how much sales activity the customer is likely to have. Generally, the better the credit rating, the greater the extent of credit will be.

The terms of the credit are essentially what implied interest rate on the credit will be. Again, this could be a function of the credit rating of the customer, the extent of credit granted, or a function of both factors. One does not want to act as a major competitor to the bank for the customer, and also one needs to keep in mind the costs of financing the credit. Ultimately, the terms of the credit may come down to a marketing decision, with the implied costs of extending the credit implicitly charged to the cost of sales or embedded in the sales price.

The one key aspect of extending credit to clients is in monitoring the credit. This is generally done by monitoring the days receivable, and acting on any credit payments that are past due.

A final component of the credit policy is what to do when a customer cannot, or will not, make payment. This is an often neglected part of credit policy, but one that it is much better to plan for in advance, rather than when it is necessary to put such plan into action. The usual strategy is to have a series of escalating notices and then warnings. However, when that does not work, other action may be taken including taking legal action or hiring a collection agency. Each of these actions has different ramifications that may reflect badly on the organization that puts them into practice.

In total, credit risk management involves a lot of moving parts, yet is often critical to sales success.

Concluding Thoughts

Credit is one of the most visible financial risks, yet one of the ones that we still have the most trouble accurately assessing and establishing accepted best practices for managing. Credit management, both one’s own credit as perceived by the external stakeholders, as well as the credit granted to customers, is a key component of the day-to-day managing of a business.

The development of the credit derivative market has revolutionized the assessment of credit and how credit risk is managed by financial institutions. It is likely that some of these techniques will be filtering to the general-use market in the next few years.

Meanwhile, consumer credit is likely to be affected by big data techniques, in part based on social media activity, so new developments in consumer credit can also be expected in the near future as well. It is an exciting time to be working as a credit risk analyst!


1S&P Ratings.

2E. Altman. September, 1968. “Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy,” Journal of Finance 23, no. 4, pp. 189-209.