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A credit scoring approach for the commercial banking sector

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  • Emel, Ahmet Burak
  • Oral, Muhittin
  • Reisman, Arnold
  • Yolalan, Reha

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  • Emel, Ahmet Burak & Oral, Muhittin & Reisman, Arnold & Yolalan, Reha, 2003. "A credit scoring approach for the commercial banking sector," Socio-Economic Planning Sciences, Elsevier, vol. 37(2), pages 103-123, June.
  • Handle: RePEc:eee:soceps:v:37:y:2003:i:2:p:103-123
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    19. Frydman, Halina & Altman, Edward I & Kao, Duen-Li, 1985. "Introducing Recursive Partitioning for Financial Classification: The Case of Financial Distress," Journal of Finance, American Finance Association, vol. 40(1), pages 269-291, March.
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    Cited by:

    1. Ha-Thu Nguyen, 2015. "How is credit scoring used to predict default in China?," EconomiX Working Papers 2015-1, University of Paris Nanterre, EconomiX.
    2. Wojciech Lichota, 2016. "Efektywność finansowa specjalnych stref ekonomicznych w Polsce," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 1, pages 99-130.
    3. Tien-Chin Wang & Ying-Ling Lin, 2009. "Using a Multi-Criteria Group Decision Making Approach to Select Merged Strategies for Commercial Banks," Group Decision and Negotiation, Springer, vol. 18(6), pages 519-536, November.
    4. Korol, Tomasz, 2013. "Early warning models against bankruptcy risk for Central European and Latin American enterprises," Economic Modelling, Elsevier, vol. 31(C), pages 22-30.
    5. Tomasz Korol, 2018. "The Implementation of Fuzzy Logic in Forecasting Financial Ratios," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 12(2), June.
    6. Salihu, Armend & Shehu, Visar, 2020. "A Review of Algorithms for Credit Risk Analysis," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2020), Virtual Conference, in: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Virtual Conference, 10-12 September 2020, pages 134-146, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb.
    7. Apostolos G. Christopoulos & Ioannis G. Dokas & Sofia Katsimardou & Konstantinos Vlachogiannatos, 2016. "Investigation of the relative efficiency for the Greek listed firms of the construction sector based on two DEA approaches for the period 2006–2012," Operational Research, Springer, vol. 16(3), pages 423-444, October.
    8. Hsiang-Hsi Liu & Tser-Yieth Chen & Jia-Wen Chen, 2013. "Incorporating the Credit Ranking Measure to Evaluate the Operating Efficiency of Financial Holding Companies in Taiwan," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 3(10), pages 1386-1404, October.
    9. Artur Wyszyński, 2017. "Sytuacja finansowa klubów Ekstraklasy w ujęciu metody DEA," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 2, pages 69-99.
    10. Ioannis Tsolas, 2015. "Firm credit risk evaluation: a series two-stage DEA modeling framework," Annals of Operations Research, Springer, vol. 233(1), pages 483-500, October.
    11. Catarina Figueira & Joseph Nellis, 2009. "Bank merger and acquisitions activity in the EU: much ado about nothing?," The Service Industries Journal, Taylor & Francis Journals, vol. 29(7), pages 875-886, July.
    12. Sahoo, Biresh K. & Acharya, Debashis, 2010. "An alternative approach to monetary aggregation in DEA," European Journal of Operational Research, Elsevier, vol. 204(3), pages 672-682, August.
    13. Lobna Abid & Afif Masmoudi & Sonia Zouari-Ghorbel, 2018. "The Consumer Loan’s Payment Default Predictive Model: an Application of the Logistic Regression and the Discriminant Analysis in a Tunisian Commercial Bank," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 9(3), pages 948-962, September.
    14. Kheiri Chari , Mohammad & Aliheidari Bioki , Tahereh & Khademizare , Hasan, 2013. "The New Method for Ranking Grouped Credit Customer Based on DEA Method," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 8(4), pages 75-98, October.
    15. Somayeh Moradi & Farimah Mokhatab Rafiei, 2019. "A dynamic credit risk assessment model with data mining techniques: evidence from Iranian banks," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-27, December.
    16. Paulo M.M. Rodrigues & Fernando A. F. Ferreira & Sérgio P. Santos, 2009. "Adding Value to Bank Branch Performance Evaluation Using Cognitive Maps and MCDA: A Case Study," Working Papers w200923, Banco de Portugal, Economics and Research Department.
    17. Hussein A. Abdou & John Pointon, 2011. "Credit Scoring, Statistical Techniques And Evaluation Criteria: A Review Of The Literature," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 18(2-3), pages 59-88, April.
    18. Nyitrai, Tamás & Virág, Miklós, 2019. "The effects of handling outliers on the performance of bankruptcy prediction models," Socio-Economic Planning Sciences, Elsevier, vol. 67(C), pages 34-42.
    19. Virág, Miklós & Nyitrai, Tamás, 2017. "Magyar vállalkozások felszámolásának előrejelzése pénzügyi mutatóik idősorai alapján [Predicting the liquidation of Hungarian firms using a time series of their financial ratios]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(3), pages 305-324.
    20. Psillaki, Maria & Tsolas, Ioannis E. & Margaritis, Dimitris, 2010. "Evaluation of credit risk based on firm performance," European Journal of Operational Research, Elsevier, vol. 201(3), pages 873-881, March.
    21. Anna Feruś, 2010. "The Application of DEA Method in Evaluating Credit Risk of Companies," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 4(4), December.
    22. Anatol RACUL & Petru TOMIŢA, 2015. "A Parametric Approach To Assessing The Creditworthiness For The Moldovan Rural Development Network," Agricultural Economics and Rural Development, Institute of Agricultural Economics, vol. 12(1), pages 45-60.

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