Wholesale Credit Risk PD Model
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We are currently working with US FBO with a large Corporate and Institutional Banking business. They are currently planning on migrating their local wholesale credit PD risk rating model used to cover general industries to align with the global methodology with some key methodological changes:
Model structure comprises of 3 sub-modules to generate the internal PD risk rating, by order of operations:
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Module 1. Investment Grade module – which identifies an obligor as investment grade and generates a through-the-cycle risk rating
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Module 2. Non-IG module – if determined not to be IG, this module generates a non-IG TTC risk rating
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Module 3. Point-in-time module – generates a PIT risk rating, which is used to adjust the TTC modeled rating to capture short-term factors (e.g., point in the credit cycle)
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Removal of qualitative input factors:
- Previously, qualitative factors (e.g., quality of management, strength of sources of repayment) were an input into the risk rating model
- In the new model, only quantitative factors are captured as inputs into the model, with qualitative factors accounted for in the post-model adjustment process
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Removal of size segmentation, i.e., all wholesale obligors will use the same model (whereas previously, Large Corporates used a different model than e.g., Middle Market)
Has anyone come across a similar model structure before, especially as it relates to the sequencing of the model?
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A number of UK banks have their wholesale PD models produce both “TTC” and “PIT” ratings – with the latter typically being driven by some sort of adjustment based on Moody’s KMV EDF’s or equivalents – you also have a number of other banks that for IFRS 9 will apply macro-economic model outputs on top of a largely TTC rating model to produce a PIT PD for IFRS 9 provisioning/ allowances purposes. The dual rating approach at big UK banks was heavily driven by a couple of modellers by the names of Scott Aguais and Lawrence Forest, and they have published a few papers describing their approach.
On the question of splitting by “investment Grade” vs “non-investment grade”, I’ve never seen this, although a split between leveraged and non-leveraged is common historically (when we built the model for one of the large German banks, we were able to reintegrate them). But size r whether a customer is rated/ quoted/ listed is a common basis for segmentation in the commercial space.
For EU banks, qualitative questions still tend to be included, although people are working to make them objective where possible, but not sure many have entirely removed them (again Scott Aguais was wanting to do this for one of the big UK banks – not sure whether he succeeded) – the issue with qualitatives is whether you can find the sweet-spot – at bottom end SME, often I don’t think credit officers have any real insights into their customers given how many they cover; at top-end, question is whether the credit officer has real insight beyond what can be captured by tools such as Factiva Sentiment Signals
Historically, it has been difficult to remove size segmentation from the entire corporate customer base, in part because you tend to see some factors have different relationships for small vs large firms (e.g. you might want a fair bit of cash on balance sheet of an SME, but for a large firm, this would be inefficient and you’d perhaps worry if management wasn’t trying to make their cash work hard )