Default Estimation and Expert Information
by Nicholas M. Kiefer of Cornell University
February 7, 2008
Abstract: Default is a rare event, even in segments in the midrange of a bank's portfolio. Inference about default rates is essential for risk management and for compliance with the requirements of Basel II. Most commercial loans are in the middle-risk categories and are to unrated companies. Expert information is crucial in inference about defaults. A Bayesian approach is proposed and illustrated using a prior distribution assessed from an industry expert. The binomial model, most common in applications, is extended to allow correlated defaults. A check of robustness is illustrated with an є- mixture of priors.
Keywords: Bayesian inference, robustness, correlated defaults, Basel II, risk management, prior assessment.
Published in: Journal of Business and Economic Statistics, Vol. 28, No. 2, (April 2010), 320-328.