The notion of using equity prices as part of a formula to quantify a company's credit risk first surfaced in the late 1960s, when Edward Altman, a professor at New York University's Stern School of Business, looked at two groups of industrial companies, one made up of companies that had defaulted and the other companies that hadn't defaulted. Looking back at the period prior to the defaults, Altman analyzed the companies' financial data to identify those numbers that provided early warnings of credit problems. The Z-score he devised includes a number of financial ratios, including one that incorporates the company's stock price.

Meanwhile, economists Fischer Black, Myron Scholes and Robert Merton came up with an insight about the relationship between a company's equity and its debt. "The real simple version is, you think about the level of the firm's assets and how volatile they are," says Christopher Finger, head of credit products at RiskMetrics Group, a financial risk analytics provider. "Based on that, you get an idea of how likely it is their assets drop below a level where they can service their liabilities."

That idea became the basis of the credit risk solutions that a company called KMV began to provide in the late 1980s. Its model for calculating a company's credit risk–its expected default frequency (EDF)–takes into account the company's stock price, the volatility of its stock and its outstanding debt, or leverage. In the years since, KMV, which was acquired by Moody's in 2002, has expanded its credit analysis products, including CreditEdge and RiskCalc, to cover companies all over the world.

Hewlett-Packard Co. (HP) has been using CreditEdge, which provides daily EDFs on more than 25,000 publicly traded companies worldwide, for about two years. Chris Patafio, director of global credit operations at Hewlett-Packard, says the company started using KMV as part of its effort to automate what had been a mostly manual process in which the company's analysts examined customers' financials to assess their creditworthiness. Patafio wanted to free up those credit analysts, who typically have graduate degrees, to spend their time looking at the riskiest customers and he wanted to add "more consistency" to the credit process. CreditEdge helps provide that, Patafio says, because it looks at publicly traded companies all over the world. "So that's one model that gives us one consistent response," he says.

Moody's KMV also helps HP look at private companies, he says, with "country-specific modeling tools" that provide a credit category once HP inputs some financial data. "It's similar to a rating, but more like a statistical calculation of expected time to default," Patafio says. It has also saved the company money, he says. Patafio's not willing to provide exact numbers on savings, but says they reflect an improvement in the company's percentage of bad debt. "Nothing beats your own history [with customers], but being able to layer on top of that a vendor with years and years of data and experience with companies, that's very powerful," he says. CreditEdge also helps the company make the best use of its credit staff by relieving them of "busy work," he says.

A SPRINKLE OF MARKET REALITY

Mary D'Agostino, a managing director at Moody's KMV, says more than half of the 50 biggest global companies now use Moody's KMV's products. "Market-based measures for risk are being well adopted and accepted by leading corporations," D'Agostino says. "This interest continues to grow."

The increased interest in market-based credit measures comes at the same time that many companies are moving toward quantifying credit decisions by using scores and also automating their credit processes. A 2003 survey by the Credit Research Foundation, an independent organization researching business credit issues, showed that about a third of companies were using credit scores. Of the companies not using scores, 30% expected to begin using them within two years and another 12% within five years. Lyle Wallis, vice president of research at the foundation, says that that move to automate credit decisions creates a demand for data to feed into the credit models, like market prices.

The obvious advantage of systems that use financial market prices is their timeliness. Public companies provide financial data once a quarter, and some private companies update their data just once a year, while a model incorporating equity prices can be refreshed every day. And some vendors of market-based credit risk information have started to extend their measures to cover the vast number of companies that don't have publicly traded stock. In 2000, Moody's KMV came out with RiskCalc, which provides estimated default frequencies on private companies by looking at the companies' financial data and market data related to their industry. Standard & Poor's Risk Solutions, a unit of the rating agency, also has a product, called Credit Risk Tracker, that provides default probabilities for private companies. "The need to quantify the credit risk of those [small and medium-sized enterprises] or counterparties is immense," says Yuval Bar-Or, global practice leader for risk solutions product management and development at S&P Risk Solutions. "And by definition, there's less information about those firms."

Of course, quantitative credit measures also reflect the stock market's volatility. How necessary is their timeliness for corporate credit departments given the volatility that can accompany it? Edgar Ortiz, head of global risk management analytics at D&B, argues that companies managing their receivables need a longer-term view–like that provided by D&B's data–that helps them judge whether customers will pay their bills in a year's time, or even be in business in a year's time.

Users of market-based credit information argue in favor of watching, analyzing and understanding as much data as possible, whether it's short-term or long-term in nature. Matthieu Royer, vice president in charge of portfolio coordination at investment bank Calyon in New York, says that from a bank's perspective, "you need to look at everything you can." Credit scores that factor in equity or other market prices may be more volatile, "but if you understand the respective market, you can adjust your response, and filter what you consider to be noise versus the real trend," Royer says. HP's Patafio acknowledges that market-based measures can be volatile. "But statistically, from a longer-term perspective, these things have been highly predictive of default," he says. And IP's Borcky says that while market-based measures may be volatile, "that's not bad if it gives me a heads up on something other people may not see for a month." He adds that a signal thrown off by a market price isn't used as a substitute for the company's own judgment on the creditworthiness of a customer. "All that does is allow us to say, 'Something's going on. Let's investigate.' That's how we use it."

Market-based credit data can be helpful in other ways. The framework that CreditEdge provides helps HP look at the risk involved in its entire portfolio of receivables, Patafio says. "We do a lot of portfolio analysis, on opportunities as well as wins." And KMV's products help HP take risk into account in its pricing, Patafio says. "We won't say to the customer, 'We're going to walk away.' We may price the deal differently, though."

SUPERMODEL PRICING

Of course, cost is a consideration. The market-based credit systems tend to be expensive, and many corporate credit managers have more modest budgets than financial institutions. Bar-Or of S&P Risk Solutions says the price of market-based measures reflects the costs of putting them together, including gathering the market data and feeding it into the system. "There will have to be a change of culture as corporations realize they need the more sophisticated credit risk measurement systems and those come at a price," Bar-Or says. "The pricing we seek to offer [corporates] will certainly be lower than the sky-high prices charged financial institutions. But I think CFOs will recognize there's a value to being able to filter through your suppliers or customers and realize who is riskier and be able to deal with them in a more granular fashion."

Calyon's Royer notes that many banks set up internal systems to monitor financial market prices for signals about credit risk, systems that track not only stock prices, but prices on bonds, credit default swaps and the secondary loan market. "You can't rely on only one of them," he says. Corporations could do the same, Royer says, and estimates that the price feeds and one or two employees capable of analyzing the data would cost about $500,000 a year. For a bank, he says, there's no question that spending that amount or more is justified, given the losses that a bank could face if a corporation defaulted on a loan, with a typical corporate loan holding now averaging $35 million to $50 million.

RiskMetric's Finger says that as the market for credit risk information matures, prices are likely to go down. The concept involved in market-based credit measures is "fairly straightforward," he says, and given that, "they can't help but get cheaper."