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In the World of Credit Risk Modelling, One Size Does Not Fit All

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In the World of Credit Risk Modelling, One Size Does Not Fit All

Banks and other financing institutions provide loans to a wide set of organizations, and also typically invest in bonds. This diversification is often done to help minimize risks. Lending and investing activities may involve traditional corporates (e.g., chemical companies) or even specialised vehicles (e.g., project or asset finance). This array of exposures can present a challenge for those in risk management and financial reporting, however, who need to monitor ongoing developments.  

Risk managers need to evaluate credit risk, which is the possibility of a loss resulting from the failure of an entity to repay a loan or meet contractual obligations. This requires that appropriate credit assessment frameworks be utilised in order to effectively evaluate many entities, while maintaining consistency across assessments to enable exposures to be consolidated for an overall view.

For those working in financial reporting, the task of estimating provisions under the Financial Reporting Standard 9 (IFRS9) can also be challenging. This is due to the need to estimate point-in-time (PIT) probabilities of default (PDs) and PIT loss given default (LGD) for a diverse portfolio of loans and investments.

More Traditional Approaches for Assessing Risks

Many organisations, both large and small, often utilise a “corporate” credit assessment framework for most, if not all, non-retail exposures. This may be due to:

    • The absence of internal credit expertise regarding non-corporate sectors.
    • The lack of internal default data on which to construct non-corporate and sector-specific credit assessment frameworks, since non-corporate sectors are usually characterised by a relatively low number of defaults.
    • A limited number of exposures to non-corporate entities, since non-corporate portfolios are often smaller than corporate or retail portfolios.

 

The use of a corporate credit assessment framework can introduce problems, however. For example, asset managers may be assessed with the same approach as chemical companies. Given this, an off-the-shelf credit assessment framework that is not purely built on default data, but also reflects expert judgement (based on both financial and non-financial factors), may be a way to efficiently assess niche portfolios.

One Size Doesn’t Fit All

Diversification strategies are in place because sectors and vehicles are not equal, so they should be treated differently for the purposes of credit risk analysis. So what causes these differences? Most are caused by structural variations between industries, which may be exaggerated by such things as regulations. For example, regulated utilities are able to sustain higher debt leverage ratios, on average, than upstream oil and gas companies, leading to the need for sector-specific considerations.

There are drawbacks to using a one size fits all approach. By definition, factors and weights will not be suitable for all sectors, potentially leading to inappropriate internal credit scores. This is particularly the case for highly regulated sectors, such as insurance.

In the World of Credit Risk Modelling, One Size Does Not Fit All

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