(a)

the reliability and quality of the internal and external data sources and the range of data obtained from those sources, as well as the time period the sources cover;

(b)

the process of data merging, where the model is fed with data from multiple data sources;

(c)

the rationale and scale of data exclusions broken down by reason for exclusion, using statistics on the share of total data which each exclusion covers where certain data were excluded from the model development sample;

(d)

the procedures for dealing with erroneous and missing data and treatment of outliers and categorical data, and verify that, where there has been a change in the type of categorisation, this does not lead to decreased data quality or structural breaks in the data;

(e)

the processes for data transformation, including standardization and other functional transformations, and the appropriateness of those transformations having regard to the risk of model overfitting.

(a)

the comparability of risk characteristics of the obligors or facilities reflected in the data used to build the model with those of the exposures covered by a particular rating model;

(b)

the comparability of the current underwriting and recovery standards with the ones applied at the time to which the reference data set used for the modelling relates;

(c)

the consistency of default definition over time in the data used for the modelling and verify:

(d)

where external data or data pooled across institutions is used in the model development, the relevance and adequacy of such data for the institution’s exposures, products and risk profile.