Have a personal or library account? Click to login
A Comparative Analysis of Credit Scoring Models and Generative AI Techniques Cover

References

  1. Bensic, M., Sarlija, N., and Zekic-Susac, M. (2006). Modelling small-business credit scoring by using logistic regression, neural networks and decision trees. Intelligent Systems in Accounting, Finance and Management, Vol. 13(3), 133-150
  2. Desai, V.S., Crook, J.N., and Overstreet Jr, G.A. (1996). A comparison of neural networks and linear scoring models in the credit union environment. European Journal of Operational Research, Vol. 95(1), 24-37
  3. Dumitrescu, E., Hue, S., Hurlin, C., and Tokpavi, S. (2022). Machine learning for credit scoring: Improving logistic regression with non-linear decision-tree effects. European Journal of Operational Research, Vol. 297(3), 1178-1192
  4. Liu, W., Fan, H., and Xia, M. (2022). Credit scoring based on tree-enhanced gradient boosting decision trees. Expert Systems with Applications, Vol. 189, 116034
  5. Luo, C., Wu, D., and Wu, D. (2017). A deep learning approach for credit scoring using credit default swaps. Engineering Applications of Artificial Intelligence, Vol. 65, 465-470
  6. Plawiak, P., Abdar, M., and Acharya, U.R. (2019). Application of new deep genetic cascade ensemble of SVM classifiers to predict the Australian credit scoring. Applied Soft Computing, Vol. 84, 105740
  7. West, D. (2000). Neural network credit scoring models. Computers & Operations Research, Vol. 27(11-12), 1131-1152
  8. Xia, Y., Liu, C., Da, B. and Li, Y. and Liu, N. (2017). A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring. Expert Systems with Applications, Vol. 78, 225-241
  9. Xia, Y., Liu, C., Da, B. and Xie, F. (2018). A novel heterogeneous ensemble credit scoring model based on stacking approach. Expert Systems with Applications, Vol. 93, 182-199
  10. Zhang, H., He, H., and Zhang, W. (2018). Classifier selection and clustering with fuzzy assignment in ensemble model for credit scoring. Neurocomputing, Vol. 316, 210-221
Language: English
Page range: 1235 - 1247
Published on: Jul 24, 2025
Published by: Bucharest University of Economic Studies
In partnership with: Paradigm Publishing Services
Publication frequency: 1 times per year

© 2025 Andreea-Mădălina Bozagiu, Georgian-Dănuț Mihai, Andrei Costin Neacşu, George Alexandru Neacşu, published by Bucharest University of Economic Studies
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.