Dear,
As we’ve discussed here before, we’re in a Systemic Financial Crisis which is driving a major transformation in the Financial System, from a business model based on Volume to a business model based in efficient Capital Management.
One of the most critical activities in Capital Management is the rating and scoring of Business Partners, Financial Instruments and Financial Transactions. Rating has a direct impact in the Valuation of the Portfolio (Fair Value) and the calculation of the Capital
Requirements (Risk Weighted Assets).
But Rating managements is becoming a very challenging activity; globalization makes very difficult tracking the risk of corporate counterparts operating in multiple countries, financial instability and unexpected credit events in some European countries have dried the credit markets impacting the solvency of governments and corporations; complex legal structures, including constructions in offshore jurisdictions have been used by insolvent counterparties for hiding unsustainable debts, by-passing solvency regulations.
On the other hand, efficient Rating management is a key activity for avoiding risky investments and taking corrective measures in case credit events damage the bank’s portfolio (Credit Default Swaps, Collateralization, Assets Protection Schemes, etc).
Fast response is critical; as detecting those damages and risks once they’re publicly known in the Capital Markets, makes the corrective measures much more expensive.
SAP Banking has a very complete set of components for offering a holistic management of the rating of the Banks assets; we’ll have a look at them in the next posts.
The Historical Database component of Bank Analyzer (included in the Credit Risk Analyzer/Basel II module) and its integration with Banking Services; which was initially developed for the calculation of some of the most important parameters of the Internal Rating Based Approach of the Basel II agreement, is in fact a very powerful tool for determining counterparty risk ratings, not only for the Capital Requirements calculation of the solvency regulation, but as a basis of other scoring activities.
A typical example is the calculation of the Probability of Default by selecting combination of characteristics defining micro-portfolios with analog risk dimensions. Measuring the historical number of defaulted and not-defaulted Financial Transactions in each micro-portfolio, and using logistic regression, the bank’s risk managers can make a statistical estimation of the Probability of Default, and consequently the rating of the Financial Transactions belonging to that micro-portfolio. The accuracy of rating estimation will depend on the risk dimensions selection and the statistical significance of the example.
Obviously there’re more complex models for Rating determination, including not only internal estimations, but external measures and combinations of external and internal models. We’ll talk about them in the next post.
Looking forward to read your comments.
K. Regards,
Ferran.
One of the most critical activities in Capital Management is the rating and scoring of Business Partners, Financial Instruments and Financial Transactions. Rating has a direct impact in the Valuation of the Portfolio (Fair Value) and the calculation of the Capital
Requirements (Risk Weighted Assets).
But Rating managements is becoming a very challenging activity; globalization makes very difficult tracking the risk of corporate counterparts operating in multiple countries, financial instability and unexpected credit events in some European countries have dried the credit markets impacting the solvency of governments and corporations; complex legal structures, including constructions in offshore jurisdictions have been used by insolvent counterparties for hiding unsustainable debts, by-passing solvency regulations.
On the other hand, efficient Rating management is a key activity for avoiding risky investments and taking corrective measures in case credit events damage the bank’s portfolio (Credit Default Swaps, Collateralization, Assets Protection Schemes, etc).
Fast response is critical; as detecting those damages and risks once they’re publicly known in the Capital Markets, makes the corrective measures much more expensive.
SAP Banking has a very complete set of components for offering a holistic management of the rating of the Banks assets; we’ll have a look at them in the next posts.
The Historical Database component of Bank Analyzer (included in the Credit Risk Analyzer/Basel II module) and its integration with Banking Services; which was initially developed for the calculation of some of the most important parameters of the Internal Rating Based Approach of the Basel II agreement, is in fact a very powerful tool for determining counterparty risk ratings, not only for the Capital Requirements calculation of the solvency regulation, but as a basis of other scoring activities.
A typical example is the calculation of the Probability of Default by selecting combination of characteristics defining micro-portfolios with analog risk dimensions. Measuring the historical number of defaulted and not-defaulted Financial Transactions in each micro-portfolio, and using logistic regression, the bank’s risk managers can make a statistical estimation of the Probability of Default, and consequently the rating of the Financial Transactions belonging to that micro-portfolio. The accuracy of rating estimation will depend on the risk dimensions selection and the statistical significance of the example.
Obviously there’re more complex models for Rating determination, including not only internal estimations, but external measures and combinations of external and internal models. We’ll talk about them in the next post.
Looking forward to read your comments.
K. Regards,
Ferran.
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