The Financial Accounting Standards Board (FASB) recently issued two new statements that materially change the financial accounting for merger and acquisition (M&A) transactions. FASB Statement No. 141 is titled "Business Combinations." Statement 142 is titled "Goodwill and Other Intangible Assets."

Statement 141 was issued to improve the generally accepted accounting principles (GAAP) financial reporting for business combinations. Under Statement 141, the pooling-of-interests method of accounting for acquisitions is no longer acceptable. All corporate M&A business combinations will now have to be accounted for under the purchase method of accounting. Statement 141 is effective for business combinations initiated after June 30, 2001.

Statement 142 requires that goodwill acquired in a business combination can no longer be periodically amortized to earnings; rather, the value of acquired goodwill must be periodically reviewed for possible impairment charges. The FASB believes that this GAAP change will allow investors to better understand the true economics of a company's acquired goodwill. The amortization of acquired goodwill will no longer be allowed after a company's adoption of this statement. Statement 142 must be adopted for fiscal years beginning after Dec. 31, 2001. However, Statement 142 does allow for the periodic amortization of a significant number of discrete intangible assets acquired in an M&A business combination. Discrete intangible assets are those that may be (1) identified separately and (2) valued separately from acquired general goodwill. While Statement 142 identifies many categories of discrete intangible assets, one category of such a discrete intangible is acquired customer lists and customer relationships.

Customer/client relationships represent a valuable intangible asset to many industrial and commercial companies. Customer/client relationships may represent the most valuable asset-tangible or intangible to many service-oriented companies. The expectation of periodic business from recurring customers/clients can be a substantial component of the value of service organizations, such as communications, transportation, pipeline, utilities and cable TV companies. Accordingly, under the provisions of Statement 141, customer-related intangible assets will now be recorded on the GAAP balance sheets of acquisitive companies. However, there are numerous other reasons to value a company's customer-related intangible assets. For example, a liquidating company may sell its customer relationships to a competitor. A debtor-in-possession (DIP)may license its customer lists to generate cash. In addition, a debtor company may pledge its customer relationship as collateral for financing or refinancing.

This article discusses the approaches and methods with respect to the identification, valuation and remaining-useful-life analysis of customer relationship intangible assets in the bankruptcy and reorganization process. In particular, we will discuss the importance of—and analytical methods related to—the remaining useful life of customer relationships. Finally, we will also present a simple illustrative example of the valuation of customer/client relationships within a bankruptcy context.

Identification of Discrete Intangible Assets

There are various definitions of the term "intangible asset." In a purchase-price allocation, the analyst may have to perform research to determine if a particular definition is appropriate to the subject analysis, given the purpose and objective of the valuation. Obviously, relevant judicial precedent and statutory authority should be consulted in this research. For purposes of this discussion, we will focus on the economic (and not the accounting) questions that are relevant to the valuation of discrete intangible assets. From this economic perspective, there are two fundamental questions that the analyst should consider:

1. What economic phenomena qualify as discrete intangible assets?
2. What economic phenomena manifest—or are indicative of—value in discrete intangible assets?

For a discrete intangible asset to exist from an economic perspective, it should typically possess certain attributes. Some of the more common attributes include:

1. It should be subject to specific identification and recognizable description.
2. It should be subject to legal existence and protection.
3. It should be subject to the right of private ownership, and this private ownership should be legally transferable.
4. There should be some tangible evidence or manifestation of the existence of the intangible asset (e.g., a contract, a license, a set of patient files, a set of client workpapers, a listing of customers, a set of financial statements, etc.).
5. It should have been created or have come into existence at an identifiable time or as the result of an identifiable event.
6. It should be subject to being destroyed or to a termination of existence at an identifiable time or as the result of an identifiable event.

In other words, there should be a specific bundle of legal rights associated with the existence of discrete intangible assets. For a discrete intangible asset to have economic value, it should possess certain additional attributes. Some of these additional attributes include:

1. It should generate some measurable amount of economic benefit to its owner; this economic benefit could be in the form of an income increment or of a cost decrement; this economic benefit is sometimes measured by comparison to the amount of income otherwise available to the intangible asset owner (e.g., the company) if the subject intangible did not exist.
2. This economic benefit may be measured in any of several ways, including net income, net operating income, net cash flow and so on.
3. It should be able to enhance the value of the other assets with which it is associated; the other assets may encompass all other assets of the company such as tangible personal property, real estate or other intangible assets.

Economic phenomena that do not demonstrate these attributes typically do not qualify as discrete intangible assets. Some economic phenomena are merely descriptive or expository in nature. They may describe conditions that contribute to the existence and value of identified, discrete intangible assets. But these phenomena do not themselves possess the requisite elements to qualify as discrete intangible assets.

Examples of such "descriptive" economic phenomena that do not qualify as identifiable intangible assets include the following:

1. high market share of the firm,
2. high profitability of the firm,
3. general positive reputation of the firm,
4. monopoly position of the firm,
5. market potential of the firm, and
6. other economic phenomena.

However, while these "descriptive" conditions do not qualify as discrete intangible assets themselves, they may indicate that the actual intangible assets do have substantial economic value. For example, while these "descriptive" conditions do not qualify as discrete intangible assets, they may indicate the existence of—and greatly contribute to the value of—recurring customer/client relationships.

Valuation of Customer-related Intangible Assets

There are several procedures and techniques that may be appropriate when used in the valuation of discrete intangible assets, such as customer/client relationships. However, all of these methods can logically be sorted into the three general categories of analyses: the cost approach, market approach and income approach.

Each of these three approaches (or groups of related methods) has the same objective: to arrive at a reasonable indication of a defined value for the customer-related intangible asset. Accordingly, methods that are premised on the same fundamental economic principles are grouped together into general approaches. Collectively, the three intangible asset valuation approaches encompass a broad spectrum of economic theory and property investment concepts.

The cost approach is based on the economic principle of substitution. This economic principle asserts that an investor will pay no more for an asset than the cost to obtain—by either purchasing or constructing—an asset of equal utility. For purposes of this economic principle, utility can be measured in many ways, including functionality, desirability and so on. The availability of—and the cost of—substitute assets are directly affected by shifts in supply and demand within the universe of substitute assets. Unlike fungible tangible assets, there may be no reasonable substitutes for discrete intangible assets. Accordingly, the cost approach often has limited application in the valuation of customer/client relationships.

The market approach is based on the related economic principles of competition and equilibrium. These economic principles conclude that, in a free and unrestricted market, supply and demand factors will drive the price of an asset to a point of equilibrium. The principle of substitution also directly influences the market approach. This is because the identification and analysis of equilibrium prices for substitute assets will provide market-derived evidence with regard to the value of the subject discrete intangible asset. Due to a paucity of transactional data, the market approach often has limited application in the valuation of customer/client relationships.

The income approach is based on the economic principle of anticipation (sometimes called the principle of expectation). In this approach, the value of the discrete intangible asset is the present value of the expected economic income to be earned from the ownership of that intangible. As the name of this principle implies, the investor anticipates the expected economic income to be earned from the intangible. This expectation of prospective economic income is converted to a present worth—that is, the indicated value of the discrete intangible asset. The income approach is commonly used in the valuation of the customer/client relationships.

There are numerous alternative definitions of economic income that may be used in the valuation of customer/client relationships. Using this valuation approach, the analyst estimates the intangible asset owner's required rate of return on the investment that generates the prospective economic income. This required rate of return is a function of many economic variables, including the risk—or uncertainty—of the expected economic income.

Identification of Customer-related Intangible Assets

The first step in any valuation process is to identify the subject property. In order for customer/client relationships to have economic value, there should be an active recurring relationship between the company and the customer (or patient, client, etc.). First, analysts exclude any "one-time" customers. Such customers may be merely shopping around for the lowest price, friendliest practitioner, etc. In any event, they have not established a recurring relationship with the company.

Second, analysts exclude any "retired" customer. "Retired" customers have a recurring relationship with the company, and the company would not expect to generate future income from such customers. There is no specific definition as to when a customer has "retired." The practical definition relates to the type of company (i.e., banking, insurance, publishing, etc.). In some cases, a customer has "retired" (and the customer relationship has no intangible value) if the customer has done business with the company in a year or two. In some cases, it may be a much longer period of customer inactivity before the customer is considered to be "retired."

Third, there should be some form of personal relationship between the customer and the company. While this factor is difficult to quantitatively measure, analysts expect the customer to identify with the company. Because of the recurring relationship, we would expect the customer, if asked, to be able to specifically identify "his" or "her" service provider.

Fourth, and likewise, there should be some form of personal relationship between the service provider and the customer. Just as the customer should be able to identify the provider, the provider should be able to identify the customer. In other words, the provider should know something about the customer, such as his/her name, address, telephone number, customer account number, purchase history, payment history, etc.

To illustrate this point, a McDonald's restaurant and a Kmart store have customers, and they probably have recurring (i.e., repeat) customers. But they don't have customer relationships, because they don't collect data regarding individual customers. Without such a relationship, general retailers cannot directly influence a customer the way a service organization can. For example, McDonald's generally cannot send a card to an individual customer to remind him that it is time for his next Big Mac. However, a data-processing firm or a commercial bank can send marketing notices to their individual customers.

Fifth, the company should possess or create some form of a file or other tangible documentation regarding the relationship with the customer. Typically, this file documents the services provided by the company for the customer. For example, these documents may include purchase records, service records, credit/payment files, etc. This factor is important because the customer is more likely to continue a professional relationship with the company that has his/her records.

Sixth, customer relationships may generally be sold or otherwise transferred. This does not mean that the actual customers themselves are sold from one company to another. Rather, the expectation of continued customer loyalty—and recurring customer income—may be sold from one company to another. Of course, the sale or other transfer of customer relationships is not an everyday occurrence. Clearly, most companies would rather maintain their customer relationships than sell their customer relationships. Nonetheless, customer relationships are bought and sold on occasion—and they may be bought and sold separately from any other tangible or intangible assets of the company.

Remaining Useful Life Analysis for Customer-related Intangible Assets

The next step in the customer relationships valuation is an analysis of remaining useful life (RUL). As explained below, the estimation of RUL is an integral part of each valuation approach.

• Income Approach—RUL analysis should be performed to estimate the projection period for economic income subject to either yield capitalization or direct capitalization.
• Cost Approach—RUL analysis should be performed to estimate the total amount of obsolescence, if any, from the estimated measure of "cost."
• Market Approach—RUL analysis should be performed in order to select/reject/adjust "comparable" or "guideline" sale/license transactional data.

The customer relationships RUL analysis will typically have a direct and predictable influence on intangible asset value. The expected influence on value is summarized below.

• Expected Influence on an Income Approach Valuation—Normally, a longer RUL would indicate a higher value. The customer relationship value is particularly sensitive when the RUL is less than 10 years. The customer relationship value is not very sensitive when the RUL is greater than 20 years.
• Expected Influence on a Cost-approach Valuation—Normally, a longer RUL means a higher value. Normally, a shorter RUL means a lower value.
• Expected Influence on a Market Approach Valuation—The "market" should indicate an acceptance for the customer relationships RUL. If the subject RUL is different from guideline sale/license transactions, then adjustments to the transactional multiples may be required. If the subject RUL is substantially different from guideline sale/license transactions, then this may indicate a lack of marketability of the subject.

The following list presents the common determinants, or factors, that influence intangible asset RUL:

• legal
• contractual
• functional
• technological
• economic
• analytical

Each of these RUL determinants should be considered in the analysis of customer/client relationships. Typically, for customer/client relationships, the determinant that indicates the shortest RUL deserves primary consideration.

The Analytical RUL Method

With regard to customer/client relationships, the analytical method often provides the best indication of RUL. There are two procedures related to the application of the analytical method to customer/client relationships RUL estimation:

1. estimation of a historical customer/client attrition rate, and
2. development of survivor curves based on historical attrition rates.

In the analytical method, "survivor curves" are used to estimate the mortality or the decay rate of a group of similar assets (e.g., customer/client/subscriber relationships) as those assets age. The analytical method—and the survivor curve theory—is similar to the mortality theory used by insurance company actuaries in order to estimate the human life span. RUL analysis is the process of estimating the behavior of a group of assets (e.g., customers) by fitting a "test group" of the assets (e.g., customers) to various survivor curves. In that way, by selecting the survivor curve that best "describes" the historical decay patterns of the test group, the future mortality behavior of each customer in the group can be estimated.

In a typical survivor curve, at age zero, 100 percent of the customer group is still surviving. As time passes, members of the customer group "retire" (i.e., are no longer customers of the company). Therefore, the percent of the customer group surviving decreases. This creates the downward sloping characteristic of the survivor curve. A survivor curve can be any mathematical function of age that can accurately depict the test group's mortality pattern.

The age at which 50 percent of the original customer group still survives is defined as the "average life." That is, a new customer relationship would have an expected life of the average life of the customer group. In reality, customers are "live" (i.e., active) across a wide range of possible time units. However, the expected life (i.e., the mean life) for a new customer relationship is the average life for the customer group.

The objective of RUL analysis is to estimate the specific RUL of each customer relationship. RUL is defined as the amount of time before a customer is expected to "retire" (and no further economic income can be expected from servicing that customer). An important procedure for estimating a customer's RUL is to calculate the "probable life" for each customer within the customer group. The probable life is the age at which a customer will "retire," given that it has already reached its current age. By subtracting the current age of a customer from its probable life, the RUL of the customer can be estimated. That is:

RUL = Probable Life minus Current Age.

The mathematical definition of the probable life of a customer relationship is the area under the survivor curve (i.e., using calculus, the integral) to the right of the current age of that customer. Every survivor curve has a corresponding probable life curve. For any customer relationship that is already "x" age units (e.g., months, years, etc.) years old, this relationship can be summarized in the following form:

Probable Life of the Survivor Customer Relationship =

∫

∞ Survivor χ Curve

There are several sets—or series—of survivor curve mathematical functions that may be used in the analytical method, including:

• Iowa-type curves (the exponential function is a special case of this type of survivor curve)
• Weibull distributions (Iowa-type curves themselves are a special case of this type of survivor curve)
• Gompertz-Makeham curves
• Polynomial equations

All of these mathematical functions should be considered when selecting the best-fitting survivor curve relative to a specific set of customer age-characteristic data. In summary, by selecting a survivor curve that accurately depicts the past decay performance of a customer group, the future retirement pattern of the customer group can be estimated. From this retirement pattern, the RUL of each customer relationship can be calculated.

In the analytical method, the procedure used to select an appropriate survivor curve is called "curve fitting." The basic concept is to find the survivor curve that best depicts (i.e., fits) the customer group's prior retirement pattern. The following procedures are typically involved in selecting the best fit survivor curve:

1. Selection of a sample population of "retired" (inactive) customers: A statistically valid random selection of the most recent retired customers is generated. The key information needed for the retired customer sample is the start date and the retirement date of each retired customer relationship.
2. Selection of a sample population of "live" (active) customer relationships: A statistically valid random selection of active customer relationships is generated. The key information needed for the live customer sample is the start date of the customer relationship.
3. Creation of the survivor table: A survivor table is created by using the random samples of retired and live customer relationships described above. A survivor table indicates the percent surviving of the sample customer group at a given age. The percent surviving at a given age "x" is:

   Percent Surviving at age x = [percent surviving at age (x-1)] X [1 - retirement rate at age (x)]

   The retirement rate at any given age is the ratio of number of customers that retired during the age divided by the number of customers exposed to retirement at the beginning of the age interval. The number of customers exposed to retirement is simply the number of active customer relationships at the beginning of the age interval.

4. Plotting of the survivor table: By selecting the pairs of coordinates (x,y), where x is the age and y is the percent surviving, an "actual" data curve is plotted.
5. Selection of best-fit survivor curve: All predetermined survivor curves are plotted on the same graph as the "actual" (i.e., survivor table) data described above. These curves are called the "ideal" curves. The difference between the actual percent surviving (i.e., the survivor table) and the "ideal" percent surviving is the "fitting error" at the particular age being examined. By summing all the squares of the fitting errors for a given survivor curve, a ranking factor describing the "fit" of the curve can be ascertained. The errors are squared both (1) to remove the "canceling" effect of negative fitting errors and (2) to put more emphasis on large errors. As a formula, the curve fitting procedure described above is:

   Ranking	n	[survivor table (age i)
   Factor =	∑	minus survivor curve
   	i = 1	(age i)]2

   where "n" is the number of entries in the survivor table selected for the fitting. The method described above is called the stub curve or stub period fitting process.

All potential survivor curves are fitted over a logical range of average lives, and a ranking factor is assigned to each fitting. The best fit curve is the survivor curve at the specified average life that has the smallest ranking factor. This procedure is typically called minimizing the sum of the squared errors. As each potential survivor curve is "fitted," a correlation coefficient is determined. The correlation coefficient is a ranking from -1 to +1 that describes how well the potential survivor curve fits the actual survivor table data. A correlation coefficient of +1 suggests that the potential survivor curve—at the average life being fitted—accurately predicts the customer sample's past retirement pattern. A correlation coefficient of -1 suggests that the potential survivor curve being fitted is not a good estimator of the sample customer group's actual past retirement pattern.

Once a "best-fit" survivor curve has been selected, the RUL for all active customer relationships can be calculated using the procedure described above. The RUL represents the remaining number of time periods that the company is expected to enjoy an economic benefit from the customer.

Customer Relationships Valuation

Numerous measures of economic income are relevant to the customer relationships valuation. Some of the common measures of economic income include the following:

• gross or net revenues
• gross income (or gross profit)
• net operating income
• net income before tax
• net income after tax
• operating cash flow
• net cash flow
• several others (such as incremental income)

Given the different measures of economic income that may be used, an essential procedure in the customer relationships valuation is to ensure that the present-value discount rate or the direct capitalization rate used in the analysis is derived on a consistent basis with the measure of economic income used. Although there are at least as many valuation methods as there are measures of economic income, all of the methods have similar conceptual underpinnings and similar practical applications. All of the customer-relationship valuation methods may be grouped into two analytical categories: (1) those that rely on direct capitalization, and (2) those that rely on yield capitalization.

In a direct-capitalization analysis, the analyst estimates the appropriate measure of economic income for one period (i.e., one period future to the valuation date) and divides that measure by an appropriate investment rate of return. The appropriate investment rate of return is called the direct capitalization rate. The capitalization rate is derived for a specified finite period of time, depending on the RUL of the customer relationships.

In a yield-capitalization analysis, the analyst projects the appropriate measure of economic income for several discrete time periods into the future. This projection of prospective economic income is converted into a present value by the use of a present value discount rate, which is the investor's required rate of return, or yield-capitalization rate, over the economic income projection period. The discrete projection period depends on the RUL of the customer relationships.

Illustrative Example of Customer-relationship Valuation

This illustrative example will present the valuation of customer/client relationships. Alpha Beta is a long-distance telephone services reseller, with both commercial and residential recurring customer/client relationships. Alpha Beta is in bankruptcy, and it has pledged the value of its intangible assets as collateral on its secured debt. This example will estimate the value of the customer-related intangible asset of Alpha Beta, as of Dec. 31, 2002—i.e., the date of the bankruptcy filing.

The following table summarizes the valuation of the Alpha Beta recurring customer/client relationships. An income-approach method is illustrated in the table. Specifically, the yield-capitalization method (using net cash flow as the appropriate measure of economic income) is illustrated. In this example, the average RUL of the Alpha Beta customer relationships is determined to be three years. This conclusion was based on an analysis of the historical "placements" and "retirements" of the company's customer relationships. In addition to the RUL of three years, the analysis indicated that the "survivor curve" and "retirement rate" of the customer relationships was estimated by an exponential function. As presented on the table, the indicated value of the Alpha Beta customer relationships intangible value is $8 million. This is the value of this intangible asset collateral for the Alpha Beta secured creditors.

Summary and Conclusion

This article discussed the valuation of customer/client relationships as intangible assets that are part of a bankruptcy estate. As in the appraisal of real estate, there are three approaches to the valuation of discrete intangible assets such as customer/client relationships: cost, market and income. The income approach is most often applicable to the valuation of customer/client relationships.

In the income approach, the value of customer relationships is based on the economic income earned by the company servicing the subject customers. Some of the common measures of economic income include operating income, net income, operating cash flow and net cash flow. The selected measure of economic income is capitalized (through direct capitalization or yield capitalization) by an appropriate capitalization rate in order to estimate the customer/client relationship value. The RUL of the customer relationships will obviously impact the valuation results. For example, customer relationships with an RUL of three years will have a lower value than the same customer relationships with an RUL of 15 years, all other factors held equal. There are several methods to estimate the RUL of intangible assets. However, for customer/client relationships, the analytical method is the most common method.

Customer/client relationships are an important intangible asset of many service-oriented companies. Therefore, the valuation of this discrete intangible asset will be an integral component of any bankruptcy or reorganization analysis.