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Credit Analysis

There are a number of ways to find out whether customers are likely to pay their debts, that is, to carry out credit analysis. The most obvious indication is whether they have paid promptly in the past. Prompt payment is usually a good omen, but beware of the customer who establishes a high credit limit on the basis of small payments and then disappears, leaving you with a large unpaid bill.

If you are dealing with a new customer, you will probably check with a credit agency. Dun & Bradstreet, which is by far the largest of these agencies, provides credit ratings on several million domestic and foreign firms. In addition to its rating service, Dun & Bradstreet provides on request a full credit report on a potential customer. Credit agencies usually report the experience that other firms have had with your customer, but you can also get this information by contacting those firms directly or through a credit bureau.

Your bank can also make a credit check. It will contact the customer`s bank and ask for information on the customer`s average bank balance, access to bank credit, and general reputation.

In addition to checking with your customer`s bank, it might make sense to check what everybody else in the financial community thinks about your customer`s credit standing. Does that sound expensive? Not if your customer is a public company. You just look at the Moody`s or Standard & Poor`s rating for the customer`s bonds.3You can also compare prices of these bonds to the prices of other firms` bonds. (Of course the comparisons should be between bonds of similar maturity, coupon, and so on.) Finally, you can look at how the customer`s stock price has been behaving recently. A sharp fall in price doesn`t mean that the company is in trouble, but it does suggest that prospects are less bright than formerly.

FINANCIAL RATIO ANALYSIS

We have suggested a number of ways to check whether your customer is a good risk. You can ask your collection manager, a specialized credit agency, a credit bureau, a banker, or the financial community at large. But if you don`t like relying on the judgment of others, you can do your own homework. Ideally this would involve a detailed analysis of the company`s business prospects and financing, but this is usually too expensive.

Therefore, credit analysts concentrate on the company`s financial statements, using rough rules of thumb to judge whether the firm is a good credit risk. The rules of thumb are based on financial ratios. Earlier we described how these ratios are calculated and interpreted.

NUMERICAL CREDIT SCORING

Analyzing credit risk is like detective work. You have a lot of clues some important, some fitting into a neat pattern, others contradictory. You must weigh these clues to come up with an overall judgment. When the firm has a small, regular clientele, the credit manager can easily handle the process informally and make a judgment about what are often termed the five Cs of credit:

1. The customer`s character

2. The customer`s capacity to pay

3. The customer`s capital

4. The collateral provided by the customer4

5. The condition of the customer`s business

When the company is dealing directly with consumers or with a large number of small trade accounts, some streamlining is essential. In these cases it may make sense to use a scoring system to prescreen credit applications.

For example, if you apply for a credit card or a bank loan, you will be asked about your job, home, and financial position. The information that you provide is used to calculate an overall credit score. Applicants who do not make the grade on the score are likely to be refused credit or subjected to more detailed analysis.

Banks and the credit departments of industrial firms also use mechanical credit scoring systems to cut the costs of assessing commercial credit applications. One bank claimed that by introducing a credit scoring system, it cut the cost of reviewing loan applications by two-thirds. It cited the case of an application for a $5,000 credit linefrom a small business. A clerk entered information from the loan application into a computer and checked the firm`s deposit balances with the bank, as well as the owner`s personal and business credit files. Immediately the loan officer could see the applicant`s score: 240 on a scale of 100 to 300, well above the bank`s cut-off figure. All that remained for the bank was to check that there was nothing obviously suspicious about the application. ¬We don`t want to lend to set up an alligator farm in the desert, ­ said one

bank official.5

Firms use several statistical techniques to separate the creditworthy sheep from the impecunious goats. One common method employs multiple discriminant analysis to produce a measure of solvency called a Z score. For example, a study by Edward Altman suggested the following relationship between a firm`s financial ratios and its creditworthiness

(Z):6 Z = 3.3 EBIT + 1.0 sales + .6

market value of equity total assets total assets total book debt

+ 1.4 retained earnings + 1.2 working capital total assets total assets

This equation did a good job at distinguishing the bankrupt and nonbankrupt firms. Of the former, 94 percent had Z scores less than 2.7 before they went bankrupt. In contrast, 97 percent of the nonbankrupt firms had Z scores above this level.7

The nearby box describes how statistical scoring systems similar to the Z score can provide timely first-cut estimates of creditworthiness. These assessments can streamline the credit decision and free up labor for other, less mechanical tasks. The box notes that these scoring systems can be used in conjunction with large databases on firms, such as that of Dun & Bradstreet, to provide quick credit scores for thousands of firms.

CREDIT ANALYSIS

Procedure to determine the likelihood a customer will pay its bills.