The application of data envelopment analysis to credit measurement

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dc.contributor.author Caldis, Adamandia Paraskevi
dc.date.accessioned 2008-06-30T09:06:40Z
dc.date.available 2008-06-30T09:06:40Z
dc.date.issued 2008-06-30T09:06:40Z
dc.identifier.uri http://hdl.handle.net/10539/4997
dc.description.abstract In competitive markets only the strong survive. For an institution to survive it needs to achieve high levels of performance through continued improvements and learning. Credit risk measurement has come under intense scrutiny with the recent Basel II Accord, an Accord that obliges banks to seek more efficient means for the management of their credit risk. In this dissertation I examine Data Envelopment Analysis (DEA), its extensions and applications to credit risk measurement. DEA is a performance measurement technique used to evaluate relative efficiency of a group. It is a quantitative model with a solid mathematical and economic underpinning; solving several linear programs simultaneously. Its greatest advantage is a feature that allows it to process multiple inputs and multiple outputs, thus uncovering relationships which remain hidden from other methodologies. We consider DEA as a useful tool for improving credit risk measurement within peer group analysis, a supplement or complement to the credit ratings and a validation tool for credit ratings. We apply DEA models to two credit risk measurement areas: Corporate Credit Risk and Country Risk. In the first application we apply DEA to corporate entities and compare efficiency to corporate credit ratings. Overall we find efficiency and credit rating have common elements. This confirms the common sense notion that corporates receiving better credit ratings are more efficient. In the second application we apply DEA to countries. We identify those countries that are performing better than the rest based on their efficiency. We discover that when a country’s efficiency is compared to country credit rating, efficiency and credit rating are measuring two different but equally important aspects. We find that efficiency is a good indicator of relative economic acceleration. We observe that efficiency has the potential to identify future improvements in country credit quality. Based on the application of DEA to Corporate and Country Credit Risk, we recommend the use of DEA as a complementary tool to credit rating models and a means of facilitating better measurement and management of credit risk within banks. en
dc.format.extent 938232 bytes
dc.format.mimetype application/pdf
dc.language.iso en en
dc.title The application of data envelopment analysis to credit measurement en
dc.type Thesis en


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