Default Estimation for Low Default Portfolios

by Nicholas M. Kiefer of Cornell University

August 2006

Abstract: Risk managers at financial institutions are concerned with estimating default probabilities for asset groups both for internal risk control procedures and for regulatory compliance. Low-default assets pose an estimation problem that has attracted recent concern. The problem in default probability estimation for low-default portfolios is that here is little relevant historical data information. No amount of data processing can fix this problem. More information is required. Incorporating expert opinion formally is an attractive option. The probability (Bayesian) approach is proposed, its feasibility demonstrated, and its relation to supervisory requirements discussed.

JEL Classification: C11, C13, C44, G18, G32.

Keywords: Bayesian inference, Bayesian estimation, expert information Basel 2, risk management.

Published in: Journal of Empirical Finance, Vol.16, No. 1, (January 2009), pp. 164-173.

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