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We focus on quantitative measurement of credit risk. Guided by economic theory and aided by large amounts of empirical data, we build quantitative models for estimating default and recovery risk, pricing of credit instruments, and credit portfolio management. Our objective is to create models that are accurate and forward-looking, yet intuitive, robust, and transparent. These models form the backbone of the credit risk solutions offered by Moody's KMV.
Recognizing the critical importance of empirical data in credit risk modeling, Moody's KMV has developed and maintains the largest database for credit risk modeling in the world. The database contains more than 30 years of default and loss information, spanning tens of thousands of public firms and millions of private companies, healthy and distressed, domestic and international. This information is further augmented with data on correlations, market prices, and historical performance.
This rich database lets us create credit risk models of unparalleled breadth and depth for major markets around the globe. Our Expected Default Frequency™ (EDF™) credit measures are generally recognized as the most accurate and forward-looking indicators of default risk, featuring comprehensive geographic coverage of public and private firms. Our Public EDF model combines information extracted from financial statements with equity market data to obtain forward-looking measures of credit risk for publicly traded firms. Our Private firm EDF model combines fundamental analysis and quantitative techniques to capture drivers of default for private firms.
In addition, we conduct pioneering research on credit valuation and portfolio management. Our model for valuing credit instruments is based on a comprehensive study of the link between market-observable credit spreads and the underlying risk drivers, such as default, recovery, systematic risk and other factors. Our extensive dataset drives Moody's KMV Empirical Credit Migration model, which in turn enables accurate risk/return assessment of complex, credit-contingent financial instruments. Risk/return measures are estimated for a portfolio of credit instruments using our Global Correlation Factor Model (Gcorr™), which is actively updated to capture current market dynamics. The Moody's KMV portfolio model treats a diverse set of credit instruments of all asset classes and structured products and incorporates an array of tools for active credit portfolio management.
In addition to product specific research, we actively engage in theoretical and empirical research on credit risk modeling. Our researchers regularly contribute to academic journals. Our team members hold Ph.D. and M.S. degrees from the top schools across the globe, with diverse backgrounds ranging from finance, accounting, and economics to operational research, mathematics, and statistics.
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