Model architectures

Exotic, black box model architectures are not acceptable – in fact models need to exhibit a very high level of ‘explain-ability’​

Data standards

Data needs to meet rigorous standards in terms of coverage, volume, quality and overall representativeness​

Audit transparency

The overall process is subject to intensive audit at any point in time by the Group Audit function

Independent review

A dedicated function (‘Group Risk’ in many banks) reviews and approves the model to exacting standards, providing a rigorous challenge process​

Rigorous model selection processes

Selection of a final model needs to be exhaustive and systematic, using a range of methods – and special subsets of the data – to prove that the model will perform well​

Stakeholder approvals

A group of key stakeholders need to review and sign-off every intermediate stage of modelling and key artefacts​

Modelling process

The modelling process needs to be extensively documented – modellers need to show [1] a strong understanding of advanced parameter estimation, and model diagnostics; and [2] that the model is compliant with the law​