Comparing Credit Risk Migration Across Customer Periods

Summary

The document asks how to compare credit risk for the same business partners across two periods. The described data include customer identifiers, ratings, rating-based default probabilities, loss given default, exposures, exposure at default, risk-weighted assets, capital requirements, and expected losses. It seeks measures of migration such as changes in risk-weighted assets relative to exposure, default probability, expected loss, and capital consumption.

It highlights analytical choices that affect interpretation: separate new customers from continuing ones, identify which existing customers moved toward higher or lower risk, and decide how defaults and unrated accounts enter the comparison. No tables, calculations, or results are included, so the document does not establish a preferred migration metric or quantify any partner’s change. Its value is as a framework for structuring a period-over-period credit risk analysis and recognizing that exposure mix and rating transitions can affect aggregate measures differently.

Key ideas

• Match counterparties across periods by their identifier to assess changes in credit risk.
• Compare default probability, expected loss, risk-weighted assets, and capital use as distinct measures.
• Separate changes among existing customers from the effect of new customers.
• Define how defaulted and unrated accounts are treated before interpreting migration results.
• Rank customers by changes in capital consumption to identify the largest increases and decreases.

Tags

# Credit Migration: Risk


# Credit Migration: Risk












Hi I am given two tables of two tables showing data about fictional corporate business partners and relevant credit risk data – ID, rating, probability of default (PD, defined by rating), loss given default % (LGD), original exposure (on- and off-balance sheet exposures), exposure at default (EAD), risk-weighted assets (RWA), capital requirement (8% x RWA), expected loss (EL defined as EADxPDxLGD), EADxPD and EADxLGD.

I am wondering how can I identify the extent of credit risk migration between the two periods– Period1 and Period2 – from the data in the two tables (Specific Business Partners are identified by the field ID). The user has a number of alternatives for defining the migration impact and should provide not only a result in terms of increased risk-weight (RWA/EAD), increased probability of default and expected loss, but also consider the impact of new and existing customers and describe the impact of defaulted and unrated customers and whether they are relevant to the analysis by considering the effects on PD, RWA and EL. Which customers have increased/decreased capital consumption the most?

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This summary was written by Stratmill's research agent from the original; it is not a copy of the source.