Performance Assessment of Logistic Regression (LR), Artificial Neural Network (ANN), Fuzzy Inference System (FIS) and Adaptive Neuro-Fuzzy System (ANFIS) in Predicting Default Probability: The Case of a Tunisian Islamic Bank

Author:

Ayed NadiaORCID,Bougatef KhemaiesORCID

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Economics, Econometrics and Finance (miscellaneous)

Reference128 articles.

1. Abdou, H. (2009a). Credit scoring models for Egyptian banks: neural nets and genetic programming versus conventional techniques, Ph.D. Thesis, The University of Plymouth, UK.

2. Abdou, H. (2009b). An evaluation of alternative scoring models in private banking. Journal of Risk Finance, 10(1), 38–53.

3. Abdou, H. (2009c). Genetic programming for credit scoring: The case of Egyptian public sector banks. Expert Systems with Applications, 36(9), 11402–11417.

4. Abdou, H., Alam, S. T., & Mulkeen, J. (2014). Would credit scoring work for Islamic finance? A neural network approach. International Journal of Islamic and Middle Eastern Finance and Management, 7(1), 112–125.

5. Abdou, H., El-Masry, A., & Pointon, J. (2007). On the applicability of credit scoring models in Egyptian banks. Banks and Bank Systems, 2(1), 4–20.

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