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A comparison of neural networks and linear scoring models in the credit union environment

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Cited by:

  1. José Willer Prado & Valderí Castro Alcântara & Francisval Melo Carvalho & Kelly Carvalho Vieira & Luiz Kennedy Cruz Machado & Dany Flávio Tonelli, 2016. "Multivariate analysis of credit risk and bankruptcy research data: a bibliometric study involving different knowledge fields (1968–2014)," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(3), pages 1007-1029, March.
  2. Robert Till & David Hand, 2003. "Behavioural models of credit card usage," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(10), pages 1201-1220.
  3. Ding, Shusheng & Cui, Tianxiang & Bellotti, Anthony Graham & Abedin, Mohammad Zoynul & Lucey, Brian, 2023. "The role of feature importance in predicting corporate financial distress in pre and post COVID periods: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 90(C).
  4. G Verstraeten & D Van den Poel, 2005. "The impact of sample bias on consumer credit scoring performance and profitability," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(8), pages 981-992, August.
  5. Ha-Thu Nguyen, 2015. "How is credit scoring used to predict default in China?," EconomiX Working Papers 2015-1, University of Paris Nanterre, EconomiX.
  6. Emmanuel Flachaire & Gilles Hacheme & Sullivan Hu'e & S'ebastien Laurent, 2022. "GAM(L)A: An econometric model for interpretable Machine Learning," Papers 2203.11691, arXiv.org.
  7. Zhang, Faming & Tadikamalla, Pandu R. & Shang, Jennifer, 2016. "Corporate credit-risk evaluation system: Integrating explicit and implicit financial performances," International Journal of Production Economics, Elsevier, vol. 177(C), pages 77-100.
  8. Dumitrescu, Elena & Hué, Sullivan & Hurlin, Christophe & Tokpavi, Sessi, 2022. "Machine learning for credit scoring: Improving logistic regression with non-linear decision-tree effects," European Journal of Operational Research, Elsevier, vol. 297(3), pages 1178-1192.
  9. Evžen Kocenda & Martin Vojtek, 2011. "Default Predictors in Retail Credit Scoring: Evidence from Czech Banking Data," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 47(6), pages 80-98, November.
  10. Luca Barbaglia & Sebastiano Manzan & Elisa Tosetti, 2023. "Forecasting Loan Default in Europe with Machine Learning," Journal of Financial Econometrics, Oxford University Press, vol. 21(2), pages 569-596.
  11. Margherita Doria & Elisa Luciano & Patrizia Semeraro, 2022. "Machine learning techniques in joint default assessment," Papers 2205.01524, arXiv.org, revised Sep 2023.
  12. Bart Baesens & Rudy Setiono & Christophe Mues & Jan Vanthienen, 2003. "Using Neural Network Rule Extraction and Decision Tables for Credit-Risk Evaluation," Management Science, INFORMS, vol. 49(3), pages 312-329, March.
  13. Goriunov Dmytro & Venzhyk Katerina, 2013. "Loan Default Prediction in Ukrainian Retail Banking," EERC Working Paper Series 13/07e, EERC Research Network, Russia and CIS.
  14. Selwyn Piramuthu, 1999. "Feature Selection for Financial Credit-Risk Evaluation Decisions," INFORMS Journal on Computing, INFORMS, vol. 11(3), pages 258-266, August.
  15. Brad S. Trinkle & Amelia A. Baldwin, 2016. "Research Opportunities for Neural Networks: The Case for Credit," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 23(3), pages 240-254, July.
  16. Kizilaslan, Recep & Freund, Steven & Iseri, Ali, 2016. "A data analytic approach to forecasting daily stock returns in an emerging marketAuthor-Name: Oztekin, Asil," European Journal of Operational Research, Elsevier, vol. 253(3), pages 697-710.
  17. Dongwoo Kim, 2023. "Can investors’ collective decision-making evolve? Evidence from peer-to-peer lending markets," Electronic Commerce Research, Springer, vol. 23(2), pages 1323-1358, June.
  18. Pulina, Manuela & Paba, Antonello, 2010. "A discrete choice approach to model credit card fraud," MPRA Paper 20019, University Library of Munich, Germany.
  19. Shian-Chang Huang & Cheng-Feng Wu & Chei-Chang Chiou & Meng-Chen Lin, 2022. "Intelligent FinTech Data Mining by Advanced Deep Learning Approaches," Computational Economics, Springer;Society for Computational Economics, vol. 59(4), pages 1407-1422, April.
  20. Alfonso Mendoza-Velázquez & Pilar Gómez-Gil, 2011. "Neural Networks, Ordered Probit Models and Multiple Discriminants. Evaluating Risk Rating Forecasts of Local Governments in Mexico," Working Papers 1, Centro de Investigación e Inteligencia Económica (CIIE), Departamento de Ciencias Sociales - UPAEP.
  21. Nawaf Almaskati, 2022. "Machine learning in finance: Major applications, issues, metrics, and future trends," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 9(03), pages 1-32, September.
  22. Feuerriegel, Stefan & Gordon, Julius, 2019. "News-based forecasts of macroeconomic indicators: A semantic path model for interpretable predictions," European Journal of Operational Research, Elsevier, vol. 272(1), pages 162-175.
  23. Enrico Supino & Nicola Piras, 2022. "Le performance dei modelli di credit scoring in contesti di forte instabilit? macroeconomica: il ruolo delle Reti Neurali Artificiali," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2022(2), pages 41-61.
  24. Finlay, Steven, 2011. "Multiple classifier architectures and their application to credit risk assessment," European Journal of Operational Research, Elsevier, vol. 210(2), pages 368-378, April.
  25. Sevim, Cuneyt & Oztekin, Asil & Bali, Ozkan & Gumus, Serkan & Guresen, Erkam, 2014. "Developing an early warning system to predict currency crises," European Journal of Operational Research, Elsevier, vol. 237(3), pages 1095-1104.
  26. Martin Řezáč, 2015. "ESIS2: Information Value Estimator for Credit Scoring Models," Computational Economics, Springer;Society for Computational Economics, vol. 45(2), pages 303-322, February.
  27. Mirta Bensic & Natasa Sarlija & Marijana Zekic‐Susac, 2005. "Modelling small‐business credit scoring by using logistic regression, neural networks and decision trees," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 13(3), pages 133-150, July.
  28. Almaskati, Nawaf & Bird, Ron & Yeung, Danny & Lu, Yue, 2021. "A horse race of models and estimation methods for predicting bankruptcy," Advances in accounting, Elsevier, vol. 52(C).
  29. 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.
  30. Brad S. Trinkle & Amelia A. Baldwin, 2007. "Interpretable credit model development via artificial neural networks," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 15(3‐4), pages 123-147, July.
  31. Elena Ivona DUMITRESCU & Sullivan HUE & Christophe HURLIN & Sessi TOKPAVI, 2020. "Machine Learning or Econometrics for Credit Scoring: Let’s Get the Best of Both Worlds," LEO Working Papers / DR LEO 2839, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
  32. Huei-Wen Teng & Michael Lee, 2019. "Estimation Procedures of Using Five Alternative Machine Learning Methods for Predicting Credit Card Default," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 22(03), pages 1-27, September.
  33. Hazar Altinbas & Goktug Cenk Akkaya, 2017. "Improving the performance of statistical learning methods with a combined meta-heuristic for consumer credit risk assessment," Risk Management, Palgrave Macmillan, vol. 19(4), pages 255-280, November.
  34. Baesens, Bart & Viaene, Stijn & Van den Poel, Dirk & Vanthienen, Jan & Dedene, Guido, 2002. "Bayesian neural network learning for repeat purchase modelling in direct marketing," European Journal of Operational Research, Elsevier, vol. 138(1), pages 191-211, April.
  35. Yiheng Li & Weidong Chen, 2020. "A Comparative Performance Assessment of Ensemble Learning for Credit Scoring," Mathematics, MDPI, vol. 8(10), pages 1-19, October.
  36. Ahmed Almustfa Hussin Adam Khatir & Marco Bee, 2022. "Machine Learning Models and Data-Balancing Techniques for Credit Scoring: What Is the Best Combination?," Risks, MDPI, vol. 10(9), pages 1-22, August.
  37. 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.
  38. Jun†Tae Han & Jae†Seok Choi & Myeon†Jung Kim & Jina Jeong, 2018. "Developing a Risk Group Predictive Model for Korean Students Falling into Bad Debt," Asian Economic Journal, East Asian Economic Association, vol. 32(1), pages 3-14, March.
  39. Chen, Shunqin & Guo, Zhengfeng & Zhao, Xinlei, 2021. "Predicting mortgage early delinquency with machine learning methods," European Journal of Operational Research, Elsevier, vol. 290(1), pages 358-372.
  40. Saulo Cardoso Maia & Gideon Carvalho Benedicto & José Willer Prado & David Alastair Robb & Oscar Neto Almeida Bispo & Mozar José Brito, 2019. "Mapping the literature on credit unions: a bibliometric investigation grounded in Scopus and Web of Science," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(3), pages 929-960, September.
  41. 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.
  42. Andrey Filchenkov & Natalia Khanzhina & Arina Tsai & Ivan Smetannikov, 2021. "Regularization of Autoencoders for Bank Client Profiling Based on Financial Transactions," Risks, MDPI, vol. 9(3), pages 1-16, March.
  43. 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.
  44. 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.
  45. Sanjeev Mittal & Pankaj Gupta & K. Jain, 2011. "Neural network credit scoring model for micro enterprise financing in India," Qualitative Research in Financial Markets, Emerald Group Publishing Limited, vol. 3(3), pages 224-242, October.
  46. Sullivan Hué, 2022. "GAM(L)A: An econometric model for interpretable machine learning," French Stata Users' Group Meetings 2022 19, Stata Users Group.
  47. Lars Ole Hjelkrem & Petter Eilif de Lange, 2023. "Explaining Deep Learning Models for Credit Scoring with SHAP: A Case Study Using Open Banking Data," JRFM, MDPI, vol. 16(4), pages 1-19, April.
  48. 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.
  49. Timotej Jagric & Vita Jagric & Davorin Kracun, 2011. "Does Non-linearity Matter in Retail Credit Risk Modeling?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 61(4), pages 384-402, August.
  50. Akkoç, Soner, 2012. "An empirical comparison of conventional techniques, neural networks and the three stage hybrid Adaptive Neuro Fuzzy Inference System (ANFIS) model for credit scoring analysis: The case of Turkish cred," European Journal of Operational Research, Elsevier, vol. 222(1), pages 168-178.
  51. Joseph L. Breeden, 2024. "An Age–Period–Cohort Framework for Profit and Profit Volatility Modeling," Mathematics, MDPI, vol. 12(10), pages 1-23, May.
  52. Maria Rocha Sousa & João Gama & Elísio Brandão, 2013. "Introducing time-changing economics into credit scoring," FEP Working Papers 513, Universidade do Porto, Faculdade de Economia do Porto.
  53. Nikolaos Schetakis & Davit Aghamalyan & Michael Boguslavsky & Agnieszka Rees & Marc Rakotomalala & Paul Robert Griffin, 2024. "Quantum Machine Learning for Credit Scoring," Mathematics, MDPI, vol. 12(9), pages 1-12, May.
  54. D Martens & T Van Gestel & M De Backer & R Haesen & J Vanthienen & B Baesens, 2010. "Credit rating prediction using Ant Colony Optimization," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(4), pages 561-573, April.
  55. Lars Ole Hjelkrem & Petter Eilif de Lange & Erik Nesset, 2022. "The Value of Open Banking Data for Application Credit Scoring: Case Study of a Norwegian Bank," JRFM, MDPI, vol. 15(12), pages 1-15, December.
  56. Malhotra, Rashmi & Malhotra, D. K., 2003. "Evaluating consumer loans using neural networks," Omega, Elsevier, vol. 31(2), pages 83-96, April.
  57. Malhotra, Rashmi & Malhotra, D. K., 2002. "Differentiating between good credits and bad credits using neuro-fuzzy systems," European Journal of Operational Research, Elsevier, vol. 136(1), pages 190-211, January.
  58. 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.
  59. 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.
  60. Tsionas, Mike G. & Andrikopoulos, Athanasios, 2020. "On a High-Dimensional Model Representation method based on Copulas," European Journal of Operational Research, Elsevier, vol. 284(3), pages 967-979.
  61. Dawei Cheng & Zhibin Niu & Yi Tu & Liqing Zhang, 2017. "Prediction defaults for networked-guarantee loans," Papers 1702.04642, arXiv.org, revised Jun 2020.
  62. 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.
  63. Asil Oztekin, 2018. "Creating a marketing strategy in healthcare industry: a holistic data analytic approach," Annals of Operations Research, Springer, vol. 270(1), pages 361-382, November.
  64. Jing Quan & Xuelian Sun, 2024. "Credit risk assessment using the factorization machine model with feature interactions," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-10, December.
  65. Lean Yu & Xinxie Li & Ling Tang & Zongyi Zhang & Gang Kou, 2015. "Social credit: a comprehensive literature review," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 1(1), pages 1-18, December.
  66. Qifeng Qiao & Peter A. Beling, 2016. "Decision analytics and machine learning in economic and financial systems," Environment Systems and Decisions, Springer, vol. 36(2), pages 109-113, June.
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