Press Releases

NYU Stern Finance Professor Edward Altman Develops Z-Metrics Credit Analysis Tool

– Investors and Lenders Can Now More Accurately Estimate Company Credit Ratings and Default Risk Probabilities –

Z-Score creator and the world’s leading bankruptcy and distressed debt expert NYU Stern Professor Edward I. Altman has co-developed the Z-Metrics™ credit analysis tool to enable investors and lenders to more accurately estimate company credit ratings and default risk probabilities.

Using 15 “ratings” categories ranging from the highest quality “ZA+” rating to the lowest quality “ZF-” rating, the Z-Metrics model evaluates the credit-worthiness of non-financial enterprises. The rating categories are based on a firm’s probability of default for one- and five-year horizons.

“High default rates on U.S., Canadian and European high-yield bonds and leveraged loans over the past five years indicate the continuous need for credit institutions and other investors to carefully monitor the financial outlook and credit-worthiness of industrial and financial enterprises,” said Professor Altman, the Max L. Heine Professor of Finance at NYU Stern School of Business, and the Director of Research in Credit and Debt Markets at the NYU Stern Salomon Center for the Study of Financial Institutions. “Z-Metrics will offer investors, lenders and regulators a robust, independent alternative to assess default probabilities and measure credit risk.”

An international expert on corporate bankruptcy, high-yield bonds, distressed debt and credit risk, Professor Altman is well-known for creating his respected Z-Score method for assessing the financial health of companies and their risk of bankruptcy. Working as a consultant to RiskMetrics Group Inc., a provider of risk management and corporate governance products and services to participants in the global financial markets, he developed the Z-Metrics tool in partnership with the company as well as with Dr. Herbert Rijken of the Vrije University of Amsterdam. To learn more about Z-Metrics, visit: http://www.riskmetrics.com/z-metrics.