6.7.1
| Statistical models:
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| | (i)
| The construction of statistical models must be based upon robust statistical techniques to reach a robust assessment of the coefficients. The statistical techniques should be chosen amongst those commonly employed in the industry for financial modelling and/or those supported by academic scientific literature. |
| | (ii)
| Institutions must demonstrate that they have undertaken best efforts to understand the characteristics of the data and the nature of the relationships between the dependent and independent variables. In particular, institutions should analyse and discuss the observed correlations between variables and expected economic causations between them. Institutions should discuss the possibility of non-linear relationships and second order effects. Upon this set of analysis, a clear conclusion must be drawn in order to choose the best-suited approach for the model at hand. The analyses, reasoning and conclusions must be all documented. |
| | (iii)
| Statistical indicators must be computed and reported in order to support the choice of a model. Thresholds should be explicitly chosen upfront for each statistical indicator. The indicators and associated thresholds should be justified and documented. |
| | (iv)
| The implementation of statistical techniques is expected to lead to several potential candidate models. Consequently, institutions should identify candidates and rank them by their statistical performance as shown by the performance indicators. The pool of candidate models should form part of the modelling documentation. All model parameters must be clearly documented.
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6.7.2
| Deterministic models:
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| | (i)
| Deterministic models, such as financial forecasting models or valuation models, do not have statistical confidence intervals. Instead, the quality of their construction should be tested through (a) a set of internal consistency and logical checks and (b) comparison of the model outputs against analytically derived values. |
| | (ii)
| Amongst other checks, one form of verification consists of computing the same quantity by different approaches. For instance, cash flows can be computed with a financial model through the direct or the indirect methods, which should both lead to the same results. Institutions must demonstrate and document that they have put in place a set of consistency checks as part of the development process of deterministic models. |
| | (iii)
| Several deterministic models can be constructed based on a different set of assumptions. These models should constitute the pool of candidate models to be considered as part of the selection process.
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6.7.3
| Expert-based models:
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| | (i)
| Expert-based models, also referred to as ‘judgemental models’, must be managed according to a comprehensive life-cycle as for any other model. The construction of such models must follow a structured process, irrespective of the subjective nature of their inputs. The documentation must be sufficiently comprehensive to enable subsequent independent validations. In particular, the relationship between variables, the model logic and the rationale for modelling choices should all be documented and approved by the Model Oversight Committee. |
| | (ii)
| The collection of subjective inputs must be treated as a formal data collection process. This means that the input data must be part of the DMF, with suitable quality control. Expert-based models provided by third parties must be supported by an appropriate involvement of internal subject matter experts. |
| | (iii)
| Institutions are expected to develop several candidate models based on different assumptions. For all candidates, they should assess the uncertainty of the outputs, which will be a key driver of the model selection. |
| | (iv)
| Institutions must be mindful of the high Model Risk associated with expert-based models. They must be in a position to justify that appropriate actions have been taken to manage such Model Risk. An additional degree of conservatism should be employed for the design, calibration and usage of expert-based models. The usage of such models for material portfolios could result into additional provisions and/or capital upon reviews from the CBAUE.
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