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Regulation (EU) No 575/2013 of the European Parliament and of the Council of 26 June 2013 on prudential requirements for credit institutions and investment firms and amending Regulation (EU) No 648/2012 Text with EEA relevance article 174 CELEX: 02013R0575-20250629 Use of models
Institutions shall use statistical or other mathematical methods (‘models’) to assign exposures to obligor or facility grades or pools. The following requirements shall be met: (a) the model shall have good predictive power and own funds requirements shall not be distorted as a result of its use; (b) the institution shall have in place a process for vetting data inputs into the model, which includes an assessment of the accuracy, completeness and appropriateness of the data; (c) the data used to build the model shall be representative of the population of the institution's actual obligors or exposures; (d) the institution shall have a regular cycle of model validation that includes monitoring of model performance and stability; review of model specification; and testing of model outputs against outcomes; |
Regulation (EU) No 575/2013 of the European Parliament and of the Council of 26 June 2013 on prudential requirements for credit institutions and investment firms and amending Regulation (EU) No 648/2012 Text with EEA relevance article 174 CELEX: 02013R0575-20250629 (e) the institution shall complement the statistical model by human judgement and human oversight to review model-based assignments and to ensure that the models are used appropriately. Review procedures shall aim at finding and limiting errors associated with model weaknesses. Human judgements shall take into account all relevant information not considered by the model. The institution shall document how human judgement and model results are to be combined.
For the purposes of the first paragraph, point (a), the input variables shall form a reasonable and effective basis for the resulting predictions. The model shall not have material biases. There shall be a functional link between the inputs and the outputs of the model, which may be determined through expert judgement, where appropriate. |