4.4.1
| Once institutions have estimated and categorised realised LGD, they should analyse and understand the drivers of realised LGD in order to inform modelling choices in the subsequent step.
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4.4.2
| At a minimum, institutions should analyse and understand the impact of the following drivers on LGD:
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| | (i)
| The time at which LGD was observed in the economic cycle. The profile of the recovery pattern and the effect of the economic cycle on this pattern. |
| | (ii)
| The effect of collateral on the final LGD including the time to realise the collateral, the impact of the type of collateral, the difference between the last valuation and the liquidation value. |
| | (iii)
| The link between LGD and the obligor’s credit worthiness at the time of default captured by its rating or its PD. |
| | (iv) | The type of facility and its seniority ranking, where applicable. |
| | (v) | The obligor segments expressed by size, industry, and/or geography. |
| | (vi)
| Any change in the bankruptcy legal framework of the jurisdiction of exposure.
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4.4.3
| Institutions should identify the most appropriate segmentation of historical realised LGD, because this choice will subsequently inform model segmentation. Portfolio segmentation should be based upon the characteristics of the obligors, its facilities and its collateral types, if any.
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4.4.4
| Institutions should be cautious when using ‘Secured LGD’ and ‘Unsecured LGDs’ as portfolio segments. A secured LGD is a loss obtained from a facility secured by a collateral. It is based upon the estimation of a collateral coverage (defined as the ratio of the collateral value to the exposure). The loss resulting from such coverage can spread across a large range: from low values in the case of over-collateralization, up to high values in the case of small collateral amounts. An average (referred as Secured LGD) across such large range of values is likely to suffer from a lack of accuracy. Thus, it is preferable to employ collateral as a direct continuous driver of LGD, rather than use it to split a population of obligors.
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4.4.5
| Once segments have been identified, institutions should produce three types of LGD per segment to support the estimation of ECL as per accounting principles. These estimates should be used to calibrate the TTC LGD and PIT LGD models in subsequent modelling steps. The estimation of averages can be exposure-weighted or count-weighted. This choice depends on each portfolio and thus each institution.
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| | (i)
| The long run average by segment, through time across business cycles, estimated as the average of realised LGDs over the observation period. |
| | (ii) | The LGD during economic downturns. |
| | (iii)
| The LGD during periods of economic growth.
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4.4.6
| When analysing the effect of collateral on LGD outcomes, institutions should consider, at a minimum, the following collateral types. Note that personal guarantees should not be considered as eligible collateral for the purpose of modelling LGD. This list may evolve with the CBUAE regulation.
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| Table 6: Types of eligible collateral
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