Covid chaos spurs on search for model risk aggregation

Many models failed in pandemic, but analysing them in clusters easier than whole-bank view

The Covid pandemic tested bank risk modelling beyond breaking point. The sudden and near-total economic shutdown in 2020 was accompanied by unprecedented levels of government support that cushioned the impact, and then followed by the equally sudden recovery as lockdowns were lifted in 2021.

All those events fell outside the boundaries of most model assumptions, even accounting for realistic tail risks. But banks don’t want to throw out all the models just because they could not keep up with

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Calibrating interest rate curves for a new era

Dmitry Pugachevsky, director of research at Quantifi, explores why building an accurate and robust interest rate curve has considerable implications for a broad range of financial operations – from setting benchmark rates to managing risk – and hinges on…

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