Institutions must demonstrate that the data chosen for modelling is representative of the key attributes of the variables to be modelled. In particular, the time period, product types, obligor segments and geographies must be carefully chosen. The development should not proceed further if the data is deemed not representative of the variable being modelled. The institution should use a conservative buffer instead of a model, until a robust model can be built.
6.2.2
For the purpose of preparation and accurate representation, the data may need to be filtered. For instance, specific obligors, portfolios, products or time periods could be excluded in order to focus on the relevant data. Such filtering must be supported by robust documentation and governance, such that the institution is in a position to measure the impact of data filtering on model outputs. The tools and codes employed to apply filters must be fully transparent and replicable by an independent party.