Institutions should manage and collect data for rating models, in compliance with the MMS. The data collection, cleaning and filtering should be fully documented in such way that it can be traced by any third party.
2.3.2
A rigorous process for data collection is expected. The type of support strategy presented in earlier sections has no implications on the need to collect data for modelling and validation.
2.3.3
For the development of rating models, the data set should include, at a minimum, (i) the characteristics of the obligors and (ii) their performance, i.e. whether they were flagged as default. For each rating model, the number of default events included in the data sample should be sufficiently large to permit the development of a robust model. This minimum number of defaults will depend on business segments and institutions should demonstrate that this minimum number is adequate. If the number of defaults is too small, alternative approaches should be considered.
2.3.4
At a minimum, institutions should ensure that the following components of the data management process are documented. These components should be included in the scope of validation of rating models.
(i)
Analysis of data sources,
(ii)
Time period covered,
(iii)
Descriptive statistics about the extracted data,
(iv)
Performing and non-performing exposures,
(v)
Quality of the financial statements collected,
(vi)
Lag of financial statements,
(vii)
Exclusions and filters, and
(viii)
Final number of performing and defaulted obligors by period.