For statistical models, institutions must choose a final model amongst a pool of constructed models. Institutions must implement an explicit mechanism to filter out models and select a final model amongst several available options. It is recommended to select a main model and a challenger model up to the pre-implementation validation step. The selection of a model should include, at a minimum, the criteria outlined below. Institutions should consider all criteria together. Statistical performance should not be the only decisive factor to choose a model.
(i)
The chosen model must demonstrate adequate performance, statistical stability and robustness as shown by the statistical indicators and their thresholds.
(ii)
The chosen model must be based on appropriate causal relationships, i.e. it should be constructed with variables and relationships that meet economic intuition and make logical business sense, as per the definition section of the MMS. For that purpose, causal diagrams are encouraged.
(iii)
The chosen model must also lead to outcomes that meet economic intuition, can be explained easily and can support decision-making appropriately.
(iv)
The chosen model must be implementable.
6.8.2
For deterministic and expert-based models, institutions must choose a final model amongst the pool of constructed models based on various assumptions. Institutions must put in place an explicit mechanism to prioritise certain assumptions and therefore choose a model amongst several candidates. In particular, the selection process should incorporate the following criteria:
(i)
The relationships between variables should be based on established causal links. The assumptions and limitations of these links should be assessed thoroughly.
(ii)
The chosen model should lead to outcomes that make meet economic intuition as defined in the MMS, can be explained easily and can support decision-making appropriately.