Munich Personal RePEc Archive

IFRS9 Expected Credit Loss Estimation: Advanced Models for Estimating Portfolio Loss and Weighting Scenario Losses

Yang, Bill Huajian and Wu, Biao and Cui, Kaijie and Du, Zunwei and Fei, Glenn (2019): IFRS9 Expected Credit Loss Estimation: Advanced Models for Estimating Portfolio Loss and Weighting Scenario Losses. Forthcoming in: The Journal of Risk Model Validation

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Abstract

Estimation of portfolio expected credit loss is required for IFRS9 regulatory purposes. It starts with the estimation of scenario loss at loan level, and then aggregated and summed up by scenario probability weights to obtain portfolio expected loss. This estimated loss can vary significantly, depending on the levels of loss severity generated by the IFSR9 models, and the probability weights chosen. There is a need for a quantitative approach for determining the weights for scenario losses. In this paper, we propose a model to estimate the expected portfolio losses brought by recession risk, and a quantitative approach for determining the scenario weights. The model and approach are validated by an empirical example, where we stress portfolio expected loss by recession risk, and calculate the scenario weights accordingly.

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