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The importance of qualitative risk assessment in banking supervision before and during the crisis

  • Kick, Thomas
  • Pfingsten, Andreas

Banking supervision requires regular inspection and assessment of financial institutions. In Germany this task is carried out by the central bank ('Deutsche Bundesbank, BBK') in cooperation with the Federal Financial Supervisory Authority ('Bundesanstalt für Finanzdienstleistungsaufsicht, BaFin'). In accordance with the Basel II approach, quantitative and qualitative information is used. It is still an open question whether supervisors provide information, based on on-site inspections, which is not known from the numbers already, or simply duplicate the quantitative information, or even overrule it by their impressions gained through visits. In our analysis we use a unique dataset on financial institutions' risk profiles, i.e. the banking supervisors' risk assessment. Methodologically, we apply a partial proportional odds model to explain the supervisor's ordinal grading by a purely quantitative CAMEL covariate vector, which is standard in many bank rating models, and we also include the bank inspector's qualitative risk assessment into the model. We find that not only the quantitative CAMEL vector is clearly important for the final supervisory risk assessment; it is, indeed, also qualitative information on a bank's internal governance, ICAAP, interest rate risk, and other qualitative risk components that plays an equally important role. Moreover, we find evidence that supervisors have become more conservative in their final judgement at the beginning of the financial crisis, i.e. the supervisory assessment seems to be more forward-looking than the mere numbers. This result underpins the importance of bank-individual on-site risk assessments.

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Paper provided by Deutsche Bundesbank, Research Centre in its series Discussion Paper Series 2: Banking and Financial Studies with number 2011,09.

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Date of creation: 2011
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Handle: RePEc:zbw:bubdp2:201109
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  1. Rebel A. Cole & Jeffery W. Gunther, 1993. "Separating the likelihood and timing of bank failure," Financial Industry Studies Working Paper 93-2, Federal Reserve Bank of Dallas.
  2. Carletti, E. & Hartmann, P. & Ongena, S., 2008. "The Economic Impact of Merger Control Legislation," Discussion Paper 2008-006, Tilburg University, Tilburg Law and Economic Center.
  3. Kick, Thomas & Koetter, Michael, 2007. "Slippery slopes of stress: Ordered failure events in German banking," Journal of Financial Stability, Elsevier, vol. 3(2), pages 132-148, July.
  4. Richard Williams, 2006. "Generalized ordered logit/partial proportional odds models for ordinal dependent variables," Stata Journal, StataCorp LP, vol. 6(1), pages 58-82, March.
  5. Sinkey, Joseph F, Jr, 1975. "A Multivariate Statistical Analysis of the Characteristics of Problem Banks," Journal of Finance, American Finance Association, vol. 30(1), pages 21-36, March.
  6. Daniel Porath, 2006. "Estimating probabilities of default for German savings banks and credit cooperatives," Schmalenbach Business Review (sbr), LMU Munich School of Management, vol. 58(3), pages 214-233, July.
  7. Altman, Edward I., 1977. "Predicting performance in the savings and loan association industry," Journal of Monetary Economics, Elsevier, vol. 3(4), pages 443-466, October.
  8. Martin, Daniel, 1977. "Early warning of bank failure : A logit regression approach," Journal of Banking & Finance, Elsevier, vol. 1(3), pages 249-276, November.
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