Feature Selection in a Credit Scoring Model
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- Y Liu & M Schumann, 2005. "Data mining feature selection for credit scoring models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(9), pages 1099-1108, September.
- Jacobson, Tor & Roszbach, Kasper, 2003.
"Bank lending policy, credit scoring and value-at-risk,"
Journal of Banking & Finance, Elsevier, vol. 27(4), pages 615-633, April.
- Jacobson, Tor & Roszbach, Kasper, 1998. "Bank Lending Policy, Credit Scoring and Value at Risk," SSE/EFI Working Paper Series in Economics and Finance 260, Stockholm School of Economics.
- Jacobson, Tor & Roszbach, Kasper, 1998. "Bank Lending Policy, Credit Scoring and Value at Risk," Working Paper Series 68, Sveriges Riksbank (Central Bank of Sweden).
- B Baesens & T Van Gestel & S Viaene & M Stepanova & J Suykens & J Vanthienen, 2003. "Benchmarking state-of-the-art classification algorithms for credit scoring," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(6), pages 627-635, June.
- Martens, David & Baesens, Bart & Van Gestel, Tony & Vanthienen, Jan, 2007. "Comprehensible credit scoring models using rule extraction from support vector machines," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1466-1476, December.
- D. J. Hand & W. E. Henley, 1997. "Statistical Classification Methods in Consumer Credit Scoring: a Review," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 160(3), pages 523-541, September.
- Lkhagvadorj Munkhdalai & Tsendsuren Munkhdalai & Oyun-Erdene Namsrai & Jong Yun Lee & Keun Ho Ryu, 2019. "An Empirical Comparison of Machine-Learning Methods on Bank Client Credit Assessments," Sustainability, MDPI, vol. 11(3), pages 1-23, January.
- Kasper Roszbach, 2004.
"Bank Lending Policy, Credit Scoring, and the Survival of Loans,"
The Review of Economics and Statistics, MIT Press, vol. 86(4), pages 946-958, November.
- Roszbach, Kasper, 1998. "Bank Lending Policy, Credit Scoring and the Survival of Loans," SSE/EFI Working Paper Series in Economics and Finance 261, Stockholm School of Economics.
- Roszbach, Kasper, 2003. "Bank Lending Policy, Credit Scoring and the Survival of Loans," Working Paper Series 154, Sveriges Riksbank (Central Bank of Sweden).
- Kim, Hong Sik & Sohn, So Young, 2010. "Support vector machines for default prediction of SMEs based on technology credit," European Journal of Operational Research, Elsevier, vol. 201(3), pages 838-846, March.
- Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
- David A. Belsley, 1988. "A Guide to Using the Collinearity Diagnostics," Boston College Working Papers in Economics 190, Boston College Department of Economics.
- Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
- Laborda, Ricardo & Laborda, Juan, 2017. "Can tree-structured classifiers add value to the investor?," Finance Research Letters, Elsevier, vol. 22(C), pages 211-226.
- Srinivasan, Venkat & Kim, Yong H, 1987. "Credit Granting: A Comparative Analysis of Classification Procedures," Journal of Finance, American Finance Association, vol. 42(3), pages 665-681, July.
- Lessmann, Stefan & Baesens, Bart & Seow, Hsin-Vonn & Thomas, Lyn C., 2015. "Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research," European Journal of Operational Research, Elsevier, vol. 247(1), pages 124-136.
- Sudheer Chava & Robert A. Jarrow, 2008.
"Bankruptcy Prediction with Industry Effects,"
World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 21, pages 517-549,
World Scientific Publishing Co. Pte. Ltd..
- Sudheer Chava & Robert A. Jarrow, 2004. "Bankruptcy Prediction with Industry Effects," Review of Finance, European Finance Association, vol. 8(4), pages 537-569.
- Tay, Francis E. H. & Cao, Lijuan, 2001. "Application of support vector machines in financial time series forecasting," Omega, Elsevier, vol. 29(4), pages 309-317, August.
- Shumway, Tyler, 2001. "Forecasting Bankruptcy More Accurately: A Simple Hazard Model," The Journal of Business, University of Chicago Press, vol. 74(1), pages 101-124, January.
- 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:
- Babaei, Golnoosh & Giudici, Paolo & Raffinetti, Emanuela, 2023. "Explainable FinTech lending," Journal of Economics and Business, Elsevier, vol. 125.
- Ivan Tikshaev & Roman Kulshin & Gennadii Volokitin & Pavel Senchenko & Anatoly Sidorov, 2022. "The Possibilities of Using Scoring to Determine the Relevance of Software Development Tenders," Mathematics, MDPI, vol. 10(24), pages 1-13, December.
- Xinlin Wang & Zs'ofia Kraussl & Mats Brorsson, 2024. "Datasets for Advanced Bankruptcy Prediction: A survey and Taxonomy," Papers 2411.01928, arXiv.org.
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Keywords
operational research in banking; machine learning; credit scoring; classification algorithms; feature selection methods;All these keywords.
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