Regulatory requirements are evolving towards mandating financial institutions to estimate and report their climate-related financial risks. Climate risks are medium- to long-term in nature and are important risk factors for credit portfolios. Threshold models for portfolio credit risk specify account level models with both systematic and idiosyncratic effects. These aggregate to generate the portfolio loss distribution from which risk metrics are calculated.

Distortion provides a method for re-weighting a probability distribution. The amount of deformation depends on the choice of distortion function and its parameter. Here, we propose distortion as a way of incorporating climate risk into existing credit risk models. Some properties of the distorted credit risk models are derived and explored. The relation between our proposed models and existing climate-adjusted portfolio credit risk models will be discussed.