Banks should quantify loan-loss model risk – academic

Models such as those used for IFRS 9, CECL or CCAR are prone to errors, and should be accounted for


Banks should account for – and capitalise against – the risk of the models they use to forecast losses on loans being wrong, says forthcoming research.

In Quantification of model risk in stress testing and scenario analysis, the SAS Institute’s Jimmy Skoglund proposes a method of quantifying model risk using stressed transition probability matrices for credit loss impairment forecasting, in a bid to put a dollar value on the amount banks should set aside against the risk of their models

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