LossCalc v2: Dynamic Prediction of LGD

by Greg M. Gupton of Moody's|KMV, and
Roger M. Stein of Moody's|KMV

January 2005

Abstract: LossCalc™ version 2.0 is the Moody's KMV model to predict loss given default (LGD) or (1 - recovery rate). Lenders and investors use LGD to estimate future credit losses. LossCalc is a robust and validated model of LGD for loans, bonds, and preferred stocks for the US, Canada, the UK, Continental Europe, Asia, and Latin America. It projects LGD for defaults occurring immediately and for defaults that may occur in one year.

LossCalc is a statistical model that incorporates information at different levels: collateral, instrument, firm, industry, country, and the macroeconomy to predict LGD. It significantly improves on the use of historical recovery averages to predict LGD, helping institutions to better price and manage credit risk.

LossCalc is built on a global dataset of 3,026 recovery observations for loans, bonds, and preferred stock from 1981-2004. This dataset includes over 1,424 defaults of both public and private firms--both rated and unrated instruments--in all industries.

LossCalc will help institutions better manage their credit risk and can play a critical role in meeting the Basel II requirements on advanced Internal Ratings Based Approach. This paper describes Moody's KMV LossCalc, its predictive factors, the modeling approach, and its out of-time and out of-sample model validation.

JEL Classification: C33, C52, G12, G20, G33.

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