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A Note on the Comparison of Logit and Discriminant Models of Consumer Credit Behavior

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  1. repec:hum:wpaper:sfb649dp2005-009 is not listed on IDEAS
  2. Guo, Yanhong & Zhou, Wenjun & Luo, Chunyu & Liu, Chuanren & Xiong, Hui, 2016. "Instance-based credit risk assessment for investment decisions in P2P lending," European Journal of Operational Research, Elsevier, vol. 249(2), pages 417-426.
  3. Zeineb Affes & Rania Hentati-Kaffel, 2016. "Forecast bankruptcy using a blend of clustering and MARS model - Case of US banks," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01314553, HAL.
  4. Jane Brown & Anders Wäppling & Helen Woodruffe-Burton & Kate Black, 2017. "The orbit of consumer credit choices," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 22(2), pages 85-96, June.
  5. Zeineb Affes & Rania Hentati-Kaffel, 2016. "Forecast bankruptcy using a blend of clustering and MARS model - Case of US banks," Documents de travail du Centre d'Economie de la Sorbonne 16026, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  6. Hadis Abbasi & Shahrooz Bamdad & Morteza Rahimi, 2024. "Metaheuristic-based portfolio optimization in peer-to-peer lending platforms," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(8), pages 3629-3642, August.
  7. Härdle, Wolfgang Karl & Moro, Rouslan A. & Schäfer, Dorothea, 2005. "Predicting bankruptcy with support vector machines," SFB 649 Discussion Papers 2005-009, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  8. Yang, Yingxu, 2007. "Adaptive credit scoring with kernel learning methods," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1521-1536, December.
  9. Peresetsky, A. A., 2011. "What factors drive the Russian banks license withdrawal," MPRA Paper 41507, University Library of Munich, Germany.
  10. Moro, Russ & Härdle, Wolfgang Karl & Aliakbari, Saeideh & Hoffmann, Linda, 2011. "Forecasting corporate distress in the Asian and Pacific region," SFB 649 Discussion Papers 2011-023, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  11. Rafał Balina & Marta Idasz-Balina, 2021. "Drivers of Individual Credit Risk of Retail Customers—A Case Study on the Example of the Polish Cooperative Banking Sector," Risks, MDPI, vol. 9(12), pages 1-26, December.
  12. H-T Tsai & L C Thomas & H-C Yeh, 2005. "An economic model for credit assessment problems using screening approaches," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(7), pages 836-843, July.
  13. Ting Sun & Miklos A. Vasarhelyi, 2018. "Predicting credit card delinquencies: An application of deep neural networks," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 25(4), pages 174-189, October.
  14. Yao-Zhi Xu & Jian-Lin Zhang & Ying Hua & Lin-Yue Wang, 2019. "Dynamic Credit Risk Evaluation Method for E-Commerce Sellers Based on a Hybrid Artificial Intelligence Model," Sustainability, MDPI, vol. 11(19), pages 1-17, October.
  15. Li, Huan & Wu, Weixing, 2024. "Loan default predictability with explainable machine learning," Finance Research Letters, Elsevier, vol. 60(C).
  16. Anatoly Peresetsky & Alexandr Karminsky & Sergei Golovan, 2011. "Probability of default models of Russian banks," Economic Change and Restructuring, Springer, vol. 44(4), pages 297-334, November.
  17. Li Gan & Roberto Mosquera, 2008. "An Empirical Study of the Credit Market with Unobserved Consumer Typers," NBER Working Papers 13873, National Bureau of Economic Research, Inc.
  18. João A. Bastos, 2022. "Predicting Credit Scores with Boosted Decision Trees," Forecasting, MDPI, vol. 4(4), pages 1-11, November.
  19. Yu, Lean & Yao, Xiao & Zhang, Xiaoming & Yin, Hang & Liu, Jia, 2020. "A novel dual-weighted fuzzy proximal support vector machine with application to credit risk analysis," International Review of Financial Analysis, Elsevier, vol. 71(C).
  20. Bastos, Joao, 2007. "Credit scoring with boosted decision trees," MPRA Paper 8034, University Library of Munich, Germany.
  21. Natalia Nehrebecka, 2021. "Internal Credit Risk Models and Digital Transformation: What to Prepare for? An Application to Poland," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 3), pages 719-736.
  22. Lili Li & Jun Yang & Xin Zou, 2016. "A study of credit risk of Chinese listed companies: ZPP versus KMV," Applied Economics, Taylor & Francis Journals, vol. 48(29), pages 2697-2710, June.
  23. Ha-Thu Nguyen, 2014. "Default Predictors in Credit Scoring - Evidence from France’s Retail Banking Institution," EconomiX Working Papers 2014-26, University of Paris Nanterre, EconomiX.
  24. Dannenberg, Henry, 2006. "Die Verlustverteilung des unternehmerischen Forderungsausfallrisikos – Eine simulationsbasierte Modellierung," IWH Discussion Papers 10/2006, Halle Institute for Economic Research (IWH).
  25. Lu Gao & Kanshukan Rajaratnam & Peter Beling, 2016. "Loan origination decisions using a multinomial scorecard," Annals of Operations Research, Springer, vol. 243(1), pages 199-210, August.
  26. Goriunov Dmytro & Venzhyk Katerina, 2013. "Loan Default Prediction in Ukrainian Retail Banking," EERC Working Paper Series 13/07e, EERC Research Network, Russia and CIS.
  27. Lee, Kyungeun & Lee, Hyesu & Lee, Hyoseop & Yoon, Yoonjin & Lee, Eunjung & Rhee, Wonjong, 2018. "Assuring explainability on demand response targeting via credit scoring," Energy, Elsevier, vol. 161(C), pages 670-679.
  28. Kyriazopoulos Georgios, 2019. "Credit risk evaluation and rating for SMES using statistical approaches: the case of European SMES manufacturing sector," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 9(5), pages 1-4.
  29. Marco Muscettola, 2019. "Distinctiveness of Highly Risky Italian Firms That are Saved-A Logistic Approach," Applied Economics and Finance, Redfame publishing, vol. 6(1), pages 64-73, January.
  30. Fernandes, Guilherme Barreto & Artes , Rinaldo, 2013. "Spatial correlation in credit risk and its improvement in credit scoring," Insper Working Papers wpe_321, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
  31. Dalila Boughaci & Abdullah A. K. Alkhawaldeh & Jamil J. Jaber & Nawaf Hamadneh, 2021. "Classification with segmentation for credit scoring and bankruptcy prediction," Empirical Economics, Springer, vol. 61(3), pages 1281-1309, September.
  32. Tong Zhang & Guotai Chi, 2021. "A heterogeneous ensemble credit scoring model based on adaptive classifier selection: An application on imbalanced data," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4372-4385, July.
  33. Liu, Yi & Yang, Menglong & Wang, Yudong & Li, Yongshan & Xiong, Tiancheng & Li, Anzhe, 2022. "Applying machine learning algorithms to predict default probability in the online credit market: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 79(C).
  34. Liao, Jui-Jung & Shih, Ching-Hui & Chen, Tai-Feng & Hsu, Ming-Fu, 2014. "An ensemble-based model for two-class imbalanced financial problem," Economic Modelling, Elsevier, vol. 37(C), pages 175-183.
  35. Badreddine Benyacoub & Souad ElBernoussi & Abdelhak Zoglat & Mohamed Ouzineb, 2022. "Credit Scoring Model Based on HMM/Baum-Welch Method," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1135-1154, March.
  36. Ha Thu Nguyen, 2014. "Default Predictors in Credit Scoring - Evidence from France’s Retail Banking Institution," Working Papers hal-04141336, HAL.
  37. Adnan Dželihodžić & Dženana Đonko & Jasmin Kevrić, 2018. "Improved Credit Scoring Model Based on Bagging Neural Network," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(06), pages 1725-1741, November.
  38. Ying Zhou & Xia Lin & Guotai Chi & Peng Jin & Mengtong Li, 2024. "EWT‐SMOTE to improve default prediction performance in imbalanced data: Analysis of Chinese data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 615-643, April.
  39. Arno Botha & Esmerelda Oberholzer & Janette Larney & Riaan de Jongh, 2023. "Defining and comparing SICR-events for classifying impaired loans under IFRS 9," Papers 2303.03080, arXiv.org, revised Aug 2024.
  40. Andrew R. Sanderford & George A. Overstreet & Peter A. Beling & Kanshukan Rajaratnam, 2015. "Energy-efficient homes and mortgage risk: crossing the chasm at last?," Environment Systems and Decisions, Springer, vol. 35(1), pages 157-168, March.
  41. Petr Jakubík & Petr Teplý, 2011. "The JT Index as an Indicator of Financial Stability of Corporate Sector," Prague Economic Papers, Prague University of Economics and Business, vol. 2011(2), pages 157-176.
  42. Zhang, Zhiwang & Gao, Guangxia & Shi, Yong, 2014. "Credit risk evaluation using multi-criteria optimization classifier with kernel, fuzzification and penalty factors," European Journal of Operational Research, Elsevier, vol. 237(1), pages 335-348.
  43. Tang, Lingxiao & Cai, Fei & Ouyang, Yao, 2019. "Applying a nonparametric random forest algorithm to assess the credit risk of the energy industry in China," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 563-572.
  44. Ernest Urbanovich & Ella E. Young & Martin L. Puterman & Sidney O. Fattedad, 2003. "Early Detection of High-Risk Claims at the Workers' Compensation Board of British Columbia," Interfaces, INFORMS, vol. 33(4), pages 15-26, August.
  45. Clifford B. Hawley & Edwin T. Fujii, 1991. "Discrimination in Consumer Credit Markets," Eastern Economic Journal, Eastern Economic Association, vol. 17(1), pages 21-30, Jan-Mar.
  46. Fernandes, Guilherme Barreto & Artes, Rinaldo, 2016. "Spatial dependence in credit risk and its improvement in credit scoring," European Journal of Operational Research, Elsevier, vol. 249(2), pages 517-524.
  47. repec:zbw:bofitp:2004_021 is not listed on IDEAS
  48. Lorenzo Gai & Federica Ielasi, 2014. "Operational drivers affecting credit risk of mutual guarantee institutions," Journal of Risk Finance, Emerald Group Publishing, vol. 15(3), pages 275-293, May.
  49. Scognamiglio, Elisabetta & Di Lorenzo, Emilia & Sibillo, Marilena & Trotta, Annarita, 2019. "Social uncertainty evaluation in Social Impact Bonds: Review and framework," Research in International Business and Finance, Elsevier, vol. 47(C), pages 40-56.
  50. Mark Schreiner, 2001. "Scoring Drop-Out at a Microlender in Bolivia," Development and Comp Systems 0109009, University Library of Munich, Germany.
  51. Anatoly Peresetsky & Alexandr Karminsky & Sergei Golovan, 2011. "Probability of default models of Russian banks," Economic Change and Restructuring, Springer, vol. 44(4), pages 297-334, November.
  52. Westgaard, Sjur & van der Wijst, Nico, 2001. "Default probabilities in a corporate bank portfolio: A logistic model approach," European Journal of Operational Research, Elsevier, vol. 135(2), pages 338-349, December.
  53. Пересецкий А.А., 2007. "Методы Оценки Вероятности Дефолта Банков," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 43(3), июль.
  54. Carlos Giner-Baixauli & Juan Tinguaro Rodríguez & Alejandro Álvaro-Meca & Daniel Vélez, 2021. "Modelling Interaction Effects by Using Extended WOE Variables with Applications to Credit Scoring," Mathematics, MDPI, vol. 9(16), pages 1-26, August.
  55. Hong Wang & Qingsong Xu & Lifeng Zhou, 2015. "Large Unbalanced Credit Scoring Using Lasso-Logistic Regression Ensemble," PLOS ONE, Public Library of Science, vol. 10(2), pages 1-20, February.
  56. Peresetsky, Anatoly, 2013. "Modeling reasons for Russian bank license withdrawal: Unaccounted factors," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 30(2), pages 49-64.
  57. Mo Leo S. F. & Yau Kelvin K. W., 2010. "Survival Mixture Model for Credit Risk Analysis," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 4(2), pages 1-20, July.
  58. Constangioara Alexandru, 2008. "Risks Management. A Propensity Score Application," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 4(1), pages 173-175, May.
  59. Thomas, Lyn C., 2000. "A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers," International Journal of Forecasting, Elsevier, vol. 16(2), pages 149-172.
  60. Ge Gao & Hongxin Wang & Pengbin Gao, 2021. "Establishing a Credit Risk Evaluation System for SMEs Using the Soft Voting Fusion Model," Risks, MDPI, vol. 9(11), pages 1-12, November.
  61. Yu, Lean & Wang, Shouyang & Lai, Kin Keung, 2009. "An intelligent-agent-based fuzzy group decision making model for financial multicriteria decision support: The case of credit scoring," European Journal of Operational Research, Elsevier, vol. 195(3), pages 942-959, June.
  62. Shen, Feng & Zhang, Xin & Wang, Run & Lan, Dao & Zhou, Wei, 2022. "Sequential optimization three-way decision model with information gain for credit default risk evaluation," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1116-1128.
  63. Catalin-Emanuel CIOBOTA & Manuela-Violeta TUREATCA, 2022. "Prediction of Business Bankruptcy with the Help of Extreme Gradient Increase," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 3, pages 178-185.
  64. Lee, Tian-Shyug & Chiu, Chih-Chou & Chou, Yu-Chao & Lu, Chi-Jie, 2006. "Mining the customer credit using classification and regression tree and multivariate adaptive regression splines," Computational Statistics & Data Analysis, Elsevier, vol. 50(4), pages 1113-1130, February.
  65. TOBBACK, Ellen & MARTENS, David, 2017. "Retail credit scoring using fine-grained payment data," Working Papers 2017011, University of Antwerp, Faculty of Business and Economics.
  66. Paleologo, Giuseppe & Elisseeff, André & Antonini, Gianluca, 2010. "Subagging for credit scoring models," European Journal of Operational Research, Elsevier, vol. 201(2), pages 490-499, March.
  67. Carlos Serrano-Cinca & Begoña Gutiérrez-Nieto & Nydia M. Reyes, 2013. "A Social Approach to Microfinance Credit Scoring," Working Papers CEB 13-013, ULB -- Universite Libre de Bruxelles.
  68. Wolfgang K. Härdle & Rouslan A. Moro & Dorothea Schäfer, 2004. "Rating Companies with Support Vector Machines," Discussion Papers of DIW Berlin 416, DIW Berlin, German Institute for Economic Research.
  69. Mehdi Khashei & Akram Mirahmadi, 2015. "A Soft Intelligent Risk Evaluation Model for Credit Scoring Classification," IJFS, MDPI, vol. 3(3), pages 1-12, September.
  70. Rebeca Peláez & Ricardo Cao & Juan M. Vilar, 2022. "Bootstrap Bandwidth Selection and Confidence Regions for Double Smoothed Default Probability Estimation," Mathematics, MDPI, vol. 10(9), pages 1-25, May.
  71. Kun Liang & Jun He & Peng Wu, 2022. "Trust Evaluation Method of E-Commerce Enterprises with High-Involvement Experience Products," Sustainability, MDPI, vol. 14(23), pages 1-19, November.
  72. Zeineb Affes & Rania Hentati-Kaffel, 2016. "Forecast bankruptcy using a blend of clustering and MARS model - Case of US banks," Post-Print halshs-01314553, HAL.
  73. Kun Liang & Chen Zhang & Cuiqing Jiang, 2022. "Analyzing default risk among P2P platforms based on the LAS-STACK method by considering multidimensional signals under specific economic contexts," Electronic Commerce Research, Springer, vol. 22(1), pages 77-111, March.
  74. Rayo Cantón, Salvador & Lara Rubio, Juan & Camino Blasco, David, 2010. "A Credit Scoring Model For Institutions Of Microfinance Under The Basel Ii Normative," Journal of Economics, Finance and Administrative Science, Universidad ESAN, vol. 15(28), pages 89-124.
  75. Ibtissem Baklouti, 2014. "A Psychological Approach To Microfinance Credit Scoring Via A Classification And Regression Tree," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 21(4), pages 193-208, October.
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