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Managing Your IFRS 9 Forward-Looking Overrides – Key Considerations

As part of the group that was the second company worldwide to become IFRS9 compliant, IFRS9 has been at the forefront of what we do.  We have assisted nearly 20 companies on their IFRS9 journey over the last two years.  This blog forms part of a more extensive series on IFRS9. In this blog, we explore the administering of management overrides.

Part of IFRS9 is creating data-driven models to most accurately predict credit losses.  On top of the technical models are the compulsory forward-looking economic models (empirical or expert based) and the optional management overrides.

We are frequently asked about management adjustments, how many are acceptable, how do you manage them and when are they justified?  The technical models are derived on historical data and for various reasons, and because we need to consider forward-looking predictions, the future may not be exactly like the past.  Hence there is a requirement for occasional expert adjustments with management foresight.

For an analytical purist, the movement from a scientific “deductive approach” utilising data to make your conclusion to a “motivated reasoning” approach where “convenient” data can be cherry-picked to draw a pre-determined conclusion ought to send shivers down a quant’s spine. Nevertheless, it may be necessary due to a variety of reasons below.  If one is going to apply expert adjustments, then there are some important principles to consider.

Examples of data that can be amended:

  1. Expected credit sales (for transactional accounts)
  2. Valuations (for assets)
  3. Macro-economic or regulatory events (consider both forecasted events and events that have already happened where the effects were not observed in the modelling data)
  4. Environmental factors (for example for agricultural loans)
  5. Industry related trends (downward/upward forecasts)
  6. Operational or technology changes (e.g. a change of collection system may have temporary adverse impacts and long-term favourable effects)
  7. Metrics for new sub-products/segments not catered for in the models
  8. Credit risk management policy or strategy changes that could change the risk mix or performance within a risk class
  9. Changes in accounting policies such as write-off policy
  10. Changes in debt-sale appetite and the related debt sale prices

Key considerations:

  1. Substantial change means strong motivation: Remember the adage that an “extraordinary adjustment requires an extraordinary motivation”.  Adjustments should generally be slight and conservative; if not there needs to be a strong motivation why. While historical data might not be able to showcase the event for which an override is being defined, data analytics should still be underpinning the expected size and timing of expected impacts.
  2. Stronger models mean fewer changes. If the original models were limited from a data-perspective or non-representative of the expected future trends, then the motivation is stronger, but this should be illustrated in the write-up. For Black-Swan (i.e. unprecedented) events, special adjustments may be necessary. Often a model focuses on macro-economic events, and as such, it may leave any expected strategic events unresolved.   Lagged impacts of an economic or strategic event could be modelled through early performance indicators.  These indicators predict typical model under or over-predictions.
  3. Expert touch. The individuals making the motivation for adjustment(s) should be those with good authority on the matters. The individual should be seen as acting objectivelyand not in favour of achieving a predefined goal/objective.
  4. Team involvement. The adjustments should be agreed by the larger team responsible for provisions within a formal governance committee with recorded conclusions.
  5. Show your evidence. The adjustments should be supported by suitable and additional analytics (if possible). If external factors are cited, then the use of external data is strongly advised.
  6. Objective approach. Under IAS39 conservatism was the preferred method. IFRS9 asks for absolute objectivity.   It continues to ask that forward-looking overrides are based on scenario-weighted outcomes.   In other words, it requires all forward-looking overrides to be applied to the extent that they are likely to realise (based on probability).

It is required by IFRS9 (within reasonable cost and effort) to consider scenario weighted forward-looking adjustments.  Per inference, this would require you to adopt multiple forward-looking scenarios. Our advice is to stick to a modelled approach as described under the “economic forecasting and credit-loss relationship modelling” section and avoid the use of management judgements (where possible) unless manual adjustments are shown to be entirely necessary. When regular management adjustments become the norm, it may be worth considering rebuilding your models.

Principa offers a wide range of products and services relating to IFRS9.  These include analytical, advisory, model templates, reporting packs, deployment support, model software, etc.  We’ve also been able to help companies post-IFRS9 to make the most of their modelsContact us to find out how Principa might be able to help your business.

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