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Credit Risk

The dedicated space to converse with peers and our experts on all aspects of credit risk, from the technicalities of modelling using internal approaches, credit decisioning and underwriting, credit risk appetite, governance and monitoring, provisioning, and regulatory requirements

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  • Our dedicated space to discuss practicalities and technicalities of credit risk modelling using internal modelling approaches

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    U

    While I recognize a lot of these points, I do think that we should not let the tail wag the dog

    If the non-financial factors add predictive power, I don’t think there is any reason on a first principles basis to categorically exclude them. But of course, I do appreciate that these kind of factors can be subjective and therefore of lower quality, so we should keep an eye on that and encourage the clients to improve data quality

    Also, many banks lump treatment of these kind of factors with overrides, which is almost always where the supervisory feedback is coming from. It is commonly used as a fudge factor, and that is poor practice. One can develop a disciplined, (high-quality) data based use of this type of information to avoid that pitfall

  • Credit Risk Modelling Survey

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    U

    @OP

    In which case,

    No change in default level – new Soft UTP is not adding any defaults (there must be fully correlated to any existing trigger or triggers e.g. 90DPD, bankruptcy, etc.)

    No timing difference of default event – therefore no PD or LGD impact even due to discounting

    Client has only limited historic time series to show proof

    Both 1 and 2 indicate there is full correlation to already existing triggers at the existing time period (but level of correlation can differ at time (t) for each trigger toward the new Soft UTP trigger).

    Based on the other responses to this question, a bootstrapping would be the correct approach, but the bank states on recent periods the outcome should be NULL (or similar like that)

    Therefore, an idea could be to simulate the uncertainty of the correlation in different macroeconomic environments

    Correlation analysis of macro economic factor vs existing triggers over time (t) Given that new Soft UTP trigger is correlated toward multiple triggers at time (t) (based on existing time period the bank has), the correlation variation found of each underlying existing trigger can be used to proxy new Soft UTP trigger back in time

    PLUS above should still be supplemented with a qualitative statement

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  • Materiality for revolving exposures in Definition of Default

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  • IRB approval level (Group vs Country)

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    U

    We’ve seen a variant of this issue in US/Canada, with the large Canadian Banks generally having IRB approval at the Group level (including for their main US loan books) and their US subsidiaries being on standardized

    In this case, there is no incentive for the US entity to seek IRB approval - but US regulators do care about the risk rating systems from a bank supervision perspective, which has raised some of the same questions about whether group models are suitable. Those banks have generally taken a view aligned to a previous poster, i.e., using local models for middle market and below, and trying to align to group models for larger companies and FI's

    On the last point, I'll say that we've seen US regulators challenge the support for those decisions heavily, but at least in some cases it seems to have stood up to that challenge.  In one case where the bank's prior analysis and documentation didn't provide great support, they are being pushed to redevelop those as well, though they are trying to do so in a way that they can ultimately extend back to group as well, for a C&I model that was getting a bit long in the tooth anyway

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    U

    I'll just flag that a Canadian bank who had decided to extend several of their existing "global" models to their US subsidiary based on similar logic, and while the logic makes sense broadly, they ran into significant issues with their US subsidiary’s regulator about the way they did it

    I would primarily attribute the root causes of those issues to:

    Operating model for how those decisions were taken and where they were reviewed and challenged – the Group development and validation teams led the substantive assessment of “fit-for-use”, and while there were some US stakeholders involved, the ones most involved were not very senior in stature, and often deferred to the expertise of Group.  But those US stakeholders then couldn’t / didn’t do a good job of credibly defending those decisions to their regulators, leading the regulators to question if US senior management had been sufficiently involved in determining that these models were appropriate for the US portfolio

    The documentation they produced justifying and validating the use of these models in the US was a narrow “fit for use assessment”, which taken as a standalone artifact fell far short of the comprehensive model documentation and validation expectations of SR 11-7.  This led regulators to question the “effective challenge” provided by US model risk management and more broadly by US senior management

  • Benchmarks for predictive power of retail underwriting models

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    U

    Thanks a lot, this was very helpful!

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    J

    Very interesting point. Would be great to know OW's experience with feedback from other players.

  • This topic is deleted!

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  • Effective maturity for FIRB

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    U

    I suspect the answer will depend on what regulators require – for example the PRA expects all FIRB firms to use effective maturity (there’s currently a carve-out for SMEs, but they want to remove that too under Basel 3.1 – see below)

    I have to admit, I cannot recollect what ECB/ EBA has had to say about this, but I think it would be pretty hard to justify using it in most places but not some – would very much feel like a bank would be open to challenge around whether it was cherry-picking

    PRA CP16/22 proposal around Effective Maturity

    4.305 The PRA currently specifies within IRB permissions that firms using the
    FIRB approach must calculate effective maturity rather than apply fixed
    parameters. This is because the PRA considers that calculation of effective
    maturity is a more risk-sensitive approach, which better reflects the economic
    substance of the exposures, and thus enhances the safety and soundness of firms.
    Furthermore, using effective maturity facilitates effective competition because
    firms using the AIRB approach are also required to apply the effective maturity
    approach.

    4.306 The PRA proposes to maintain the substance of its existing approach and
    that firms using  the FIRB approach would continue to be required to apply the
    effective maturity approach. The PRA proposes to include this provision in its
    rules as it considers this would be more appropriate than applying the
    requirement on a firm-by-firm basis as is currently the case.

    4.307 The PRA considers that the proposed approach is in line with the Basel 3.1
    standards as these include a discretion for national supervisors to require
    firms using the FIRB approach to calculate effective maturity for all exposures.

    4.308 Similarly, to improve risk-sensitivity, the PRA proposes to remove the
    option currently setout in the CRR that allows firms that are otherwise
    calculating maturity to instead apply fixed maturity values for exposures to
    small UK corporates.

  • IFRS9 - LGD Models

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  • How long for a portfolio to be eligible for IRB?

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  • Risk Rating Model Overrides: Supporting evidence

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  • Internal Risk Rating Development Questions

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    U

    The other C&I related criteria I have seen for segmentation (may or may not be captured by your size / sector view):

    Rated / quoted vs. not (on the basis these firms have access to additional sources of funding plus an extra source of predictive info, although that can be reflected by other mechanisms) Specialised lending vs not (Basel has some rules re: when should be viewed as specialised – to some extent it comes down to legal form) Legal form e.g. limited liability vs. partnership vs sole trader (at bottom end) Leverage finance / recent transaction e.g. divestiture, M&A … (on the basis that they are more sensitive to changes and historical performance data may be less relevant
  • IRB - Migration Matrix

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    U

    Might also be worth taking a look at the detail in sections 2.5.5.1 - 2.5.5.2 dealing with customer migrations and migration matrix stability respectively, in the ECB's Instructions for reporting the validation results of internal models, pgs. 23 - 24

  • Wholesale Credit Risk PD Model

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    U

    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 )

  • Are aeroplanes just ships of the sky?

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    U

    Airplanes are ships of the sky from an LGD perspective, but not from a PD perspective. Railcars are also ships of the land by the same token

    From a PD perspective, they are generally separate. The maritime companies and airlines have very different obligor dynamics

    From an LGD perspective, the main drivers are downtime (i.e. how long the asset sits idle after a default) and shortfall (i.e. the decrease in the new lease after a default since usually periods of default coincides with pressure on asset prices and lease rates), but not the value on the plane. It is seldom that you’d actually lose the asset in any meaningful way, so that does not affect the LGD. There are international treaties that lessors would seek the jurisdiction of the lessee be a part of, before sending an expensive plane over with a long lifetime left on the asset. The other jurisdictions get the older planes where the lessor does not care all that much, whether they get it back or not

    To be clear, you’d parameterize the LGD model differently for different assets as the downtime and shortfall dynamics are different. But the model structure is the same. So, it becomes a bit of an optical choice on whether you call that a single model or not

  • Credit risk rating models for FIs - use of structural models

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    U

    This may just be a rumour and so worth trying to Google to verify it, but I recall a long time ago that the MKMV model didn’t work well for banks, this was a known shortcoming of the model

    It’s not at all clear what other type of structural model (other than something like KMV) one could even attempt for a bank…

  • Using external model for PD modelling?

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  • Inclusion of COVID period for credit modelling

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