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Threshold Accepting for Credit Risk Assessment and Validation

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Author Info

  • Marianna Lyra
  • Akwum Onwunta
  • Peter Winker

Abstract

According to the latest Basel framework of Banking Supervision, financial institutions should internally assign their borrowers into a number of homogeneous groups. Each group is assigned a probability of default which distinguishes it from other groups. This study aims at determining the optimal number and size of groups that allow for statistical ex post validation of the efficiency of the credit risk assignment system. Our credit risk assignment approach is based on Threshold Accepting, a local search optimization technique, which has recently performed reliably in credit risk clustering especially when considering several realistic constraints. Using a relatively large real-world retail credit portfolio, we propose a new technique to validate ex post the precision of the grading system.

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File URL: http://comisef.eu/files/wps039.pdf
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Bibliographic Info

Paper provided by COMISEF in its series Working Papers with number 039.

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Length: 27 pages
Date of creation: 25 May 2010
Date of revision:
Handle: RePEc:com:wpaper:039

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Web page: http://www.comisef.eu

Related research

Keywords: credit risk assignment; Threshold Accepting; statistical validation;

This paper has been announced in the following NEP Reports:

References

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  1. Krink, Thiemo & Paterlini, Sandra & Resti, Andrea, 2007. "Using differential evolution to improve the accuracy of bank rating systems," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 68-87, September.
  2. Marianna Lyra & Johannes Paha & Sandra Paterlini & Peter Winker, 2009. "Optimization Heuristics for Determining Internal Rating Grading Scales," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 09031, Universita di Modena e Reggio Emilia, Facoltà di Economia "Marco Biagi".
  3. Dietsch, Michel & Petey, Joel, 2004. "Should SME exposures be treated as retail or corporate exposures? A comparative analysis of default probabilities and asset correlations in French and German SMEs," Journal of Banking & Finance, Elsevier, vol. 28(4), pages 773-788, April.
  4. Merton, Robert C., 1973. "On the pricing of corporate debt: the risk structure of interest rates," Working papers 684-73., Massachusetts Institute of Technology (MIT), Sloan School of Management.
  5. Krink, Thiemo & Paterlini, Sandra & Resti, Andrea, 2008. "The optimal structure of PD buckets," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2275-2286, October.
  6. Varetto, Franco, 1998. "Genetic algorithms applications in the analysis of insolvency risk," Journal of Banking & Finance, Elsevier, vol. 22(10-11), pages 1421-1439, October.
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Cited by:
  1. Marianna Lyra, 2010. "Heuristic Strategies in Finance – An Overview," Working Papers 045, COMISEF.

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