Business Analytics Applications for Consumer Credits
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- Lean Yu & Zebin Yang & Ling Tang, 2016. "A novel multistage deep belief network based extreme learning machine ensemble learning paradigm for credit risk assessment," Flexible Services and Manufacturing Journal, Springer, vol. 28(4), pages 576-592, December.
- Hardeep Chahal & Jeevan Jyoti & Jochen Wirtz (ed.), 2019. "Understanding the Role of Business Analytics," Springer Books, Springer, number 978-981-13-1334-9, April.
- 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.
- Altman, Edward I. & Marco, Giancarlo & Varetto, Franco, 1994. "Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience)," Journal of Banking & Finance, Elsevier, vol. 18(3), pages 505-529, May.
- Martin Leo & Suneel Sharma & K. Maddulety, 2019. "Machine Learning in Banking Risk Management: A Literature Review," Risks, MDPI, vol. 7(1), pages 1-22, March.
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Keywords
Business Analytics; Machine Learning; Banking; Credit Risk Assessment; Scoring Models; Consumer Credits;All these keywords.
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