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Capital adequacy for Credit Risk: a practical exercise

The financial crisis and its effect on the real economy initiated a debate at the beginning of 2009 on the need to change financial industry regulation in order to prevent new crises, mitigate systemic risk and develop a balanced framework for competition.

This process is resulting in a number of consultative documents and regulatory proposals by the Basel Committee, FSB1, FSF2, IASC3, CEBS4, and other international agencies and forums which, once calibrated on the basis of impact analysis studies (QIS5), will gradually enter into force until their full implementation in 2012.

In particular, the Basel Committee is developing different proposals6 in relation to the three Basel II pillars7. Within the framework of Pillar 2, these proposals emphasize the relevance of the capital measurement and planning process in assessing capital adequacy, as a fundamental part of the risk management and control function in a financial institution.

This process requires entities to engage in a capital self-assessment exercise whereby, based on the entity’s risk profile and on the current economic and financial environment, all material risks affecting the institution are identified and assessed in an integrated manner in order to reach a conclusion on its capital adequacy status. This process also involves performing a number of rigorous stress testing exercises prospectively, with a view to detecting possible developments or changes in market conditions that could negatively affect the entity.

Prior to the financial crisis, the scenarios used by entities in their capital planning processes tended to be continuous in nature, therefore stress tests did not always reflect a possible economic downturn and its impact on the solvency of institutions.

Institutions that are more advanced in risk management terms have developed internal risk measurement and management models and conducted planning exercises over the longer term, using three-year projections of the core capital base and capital consumption levels. This has made it possible to produce more accurate estimates of future solvency and to define contingency plans.

Within the context described above, this study provides an analysis of credit risk capital requirements under different scenarios and risk parameter assumptions in order to assess how these scenarios affect the regulatory capital model as well as economic capital consumption.

Risk parameters comprise the various quantitative aspects to which capital is sensitive, such as through-the-cycle adjusted PD, procyclicality, stochastic LGD, rating migration or concentration.

Such simulation exercise supplements the stress tests commonly undertaken by entities as part of their capital measurement and planning process, whereby, given a number of macroeconomic scenarios, specific risk parameters are set for each scenario and capital requirements are estimated.

For the purposes of the study, regulatory capital requirements were estimated, as was the figure that would result from using an economic capital model based on methodology commonly applied by IRB8 entities. Such estimates were made on the basis of standard portfolios9 from the Mortgage Loan (Retail) and SME segments of up to EUR 100 million turnover, since these portfolios are more representative of Spanish financial institutions in terms of exposure.

This document is structured into the following sections:

  • Executive summary of the conclusions reached in the study.
  • Description of the portfolio characteristics used in the analyses.
  • Methodological foundations used.
  • Tests performed and analysis of findings.


For more information, click here to access the full document in pdf (also available in Spanish).


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© GMS Management Solutions, S.L., 2019. All rights reserved. The information contained on this publication is of a general nature and does not constitute a professional opinion or an advisory service. The data used in this publication come from public sources. GMS Management Solutions, SL assumes no liability for the veracity or accuracy of such data.