IDEAS home Printed from https://ideas.repec.org/r/bis/biswps/146.html
   My bibliography  Save this item

Consumer credit scoring: do situational circumstances matter?

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Irving Fisher Committee, 2019. "The use of big data analytics and artificial intelligence in central banking," IFC Bulletins, Bank for International Settlements, number 50.
  2. O. Emre Ergungor & Stephanie Moulton, 2014. "Beyond the Transaction: Banks and Mortgage Default of Low‐Income Homebuyers," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(8), pages 1721-1752, December.
  3. de Andrade, Fabio Wendling Muniz & Thomas, Lyn, 2007. "Structural models in consumer credit," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1569-1581, December.
  4. Nicolás de Roux, 2021. "Exogenous shocks, credit reports and access to credit: Evidence from colombian coffee producers," Documentos CEDE 19769, Universidad de los Andes, Facultad de Economía, CEDE.
  5. Singh, Ramendra Pratap & Singh, Ramendra & Mishra, Prashant, 2021. "Does managing customer accounts receivable impact customer relationships, and sales performance? An empirical investigation," Journal of Retailing and Consumer Services, Elsevier, vol. 60(C).
  6. Leow, Mindy & Crook, Jonathan, 2014. "Intensity models and transition probabilities for credit card loan delinquencies," European Journal of Operational Research, Elsevier, vol. 236(2), pages 685-694.
  7. Urban, Carly & Schmeiser, Maximilian & Collins, J. Michael & Brown, Alexandra, 2020. "The effects of high school personal financial education policies on financial behavior," Economics of Education Review, Elsevier, vol. 78(C).
  8. Miettinen Marika Rosanna & Littunen Hannu, 2013. "Factors Contributing to the Success of Start-Up Firms Using Two-Point or Multiple-Point Scale Models," Entrepreneurship Research Journal, De Gruyter, vol. 3(4), pages 449-481, June.
  9. Dawn Burton, 2012. "Credit Scoring, Risk, and Consumer Lendingscapes in Emerging Markets," Environment and Planning A, , vol. 44(1), pages 111-124, January.
  10. Souphala Chomsisengphet & Ronel Elul, 2005. "Bankruptcy exemptions, credit history, and the mortgage market," Working Papers 04-14, Federal Reserve Bank of Philadelphia.
  11. Javier Gutiérrez Rueda & Dairo Estrada & Laura Capera, 2011. "Un análisis del endeudamiento de los hogares," Temas de Estabilidad Financiera 061, Banco de la Republica de Colombia.
  12. Dorfleitner, G. & Just-Marx, S. & Priberny, C., 2017. "What drives the repayment of agricultural micro loans? Evidence from Nicaragua," The Quarterly Review of Economics and Finance, Elsevier, vol. 63(C), pages 89-100.
  13. Thi Thu Tra Pham & Robert Lensink, 2008. "Household Borrowing in Vietnam," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 7(3), pages 237-261, December.
  14. Geetesh Bhardwaj & Rajdeep Sengupta, 2011. "Credit scoring and loan default," Working Papers 2011-040, Federal Reserve Bank of St. Louis.
  15. Fernando A. F. Ferreira & Ieva Meidutė-Kavaliauskienė & Edmundas K. Zavadskas & Marjan S. Jalali & Sandra M. J. Catarino, 2019. "A Judgment-Based Risk Assessment Framework for Consumer Loans," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(01), pages 7-33, January.
  16. Iulia Iuga & Ruxandra Lazea, 2012. "Study Regarding The Influence Of The Unemployment Rate Over Non-Performing Loans In Romania Using The Correlation Indicator," Annales Universitatis Apulensis Series Oeconomica, Faculty of Sciences, "1 Decembrie 1918" University, Alba Iulia, vol. 2(14), pages 1-18.
  17. 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.
  18. Cuccaro, Laura Muriel & Sangiácomo, Máximo & Tumini, Lucía, 2022. "El crédito formal en la Argentina: un análisis con perspectiva de género," Documentos de Proyectos 47813, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).
  19. Gush, Karon & Laurie, Heather & Scott, James, 2015. "Job loss and social capital: the role of family, friends and wider support networks," ISER Working Paper Series 2015-07, Institute for Social and Economic Research.
  20. Anastasios Petropoulos & Vasilis Siakoulis & Evaggelos Stavroulakis & Aristotelis Klamargias, 2019. "A robust machine learning approach for credit risk analysis of large loan level datasets using deep learning and extreme gradient boosting," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Are post-crisis statistical initiatives completed?, volume 49, Bank for International Settlements.
  21. Nicola Jentzsch, 2017. "Secondary use of personal data: a welfare analysis," European Journal of Law and Economics, Springer, vol. 44(1), pages 165-192, August.
  22. K Rajaratnam & P Beling & G Overstreet, 2010. "Scoring decisions in the context of economic uncertainty," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(3), pages 421-429, March.
  23. He, Ping & Hua, Zhongsheng & Liu, Zhixin, 2015. "A quantification method for the collection effect on consumer term loans," Journal of Banking & Finance, Elsevier, vol. 57(C), pages 17-26.
  24. Rodrigo Alfaro & Natalia Gallardo & Roberto Stein, 2010. "The Determinants of Household Debt Defa," Working Papers Central Bank of Chile 574, Central Bank of Chile.
  25. Khandani, Amir E. & Kim, Adlar J. & Lo, Andrew W., 2010. "Consumer credit-risk models via machine-learning algorithms," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2767-2787, November.
  26. Oh, Joon-Hee & Johnston, Wesley J., 2014. "Credit lender–borrower relationship in the credit card market – Implications for credit risk management strategy and relationship marketing," International Business Review, Elsevier, vol. 23(6), pages 1086-1095.
  27. L N Allen & L C Rose, 2006. "Financial survival analysis of defaulted debtors," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(6), pages 630-636, June.
  28. Tang, Xinyin & Feng, Chong & Zhu, Jianping & He, Minna, 2022. "How Can We Learn from Borrowers’ Online Behaviors? The Signal Effect of Borrowers’ Platform Involvement on Their Credit Risk," SocArXiv qga8j, Center for Open Science.
  29. Federico Ferretti, 2007. "Consumer credit information systems: a critical review of the literature. Too little attention paid by Lawyers?," European Journal of Law and Economics, Springer, vol. 23(1), pages 71-88, February.
  30. Chomsisengphet, Souphala & Elul, Ronel, 2006. "Bankruptcy exemptions, credit history, and the mortgage market," Journal of Urban Economics, Elsevier, vol. 59(1), pages 171-188, January.
  31. Anastasios Petropoulos & Vasilis Siakoulis & Evaggelos Stavroulakis & Aristotelis Klamargias, 2019. "A robust machine learning approach for credit risk analysis of large loan-level datasets using deep learning and extreme gradient boosting," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The use of big data analytics and artificial intelligence in central banking, volume 50, Bank for International Settlements.
  32. K. Majamaa & A.-R. Lehtinen, 2022. "An Analysis of Finnish Debtors Who Defaulted in 2014–2016 Because of Unsecured Credit Products," Journal of Consumer Policy, Springer, vol. 45(4), pages 595-617, December.
  33. Fabián Enrique Salazar Villano, 2013. "Cuantificación del riesgo de incumplimiento en créditos de libre inversión: un ejercicio econométrico para una entidad bancaria del municipio de Popayán, Colombia," Estudios Gerenciales, Universidad Icesi, December.
  34. Nicolás de Roux, 2020. "Weather Variability, Credit Scores and Access to Credit: Evidence from Colombian Coffee Farmers," Documentos CEDE 17800, Universidad de los Andes, Facultad de Economía, CEDE.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.