Table 1 Proposed models of credit risk. The researchers have tried to solve the customer credit risk assessment problem, using a different approach and technique, and each of them has tried to present a more accurate model than others. Table 1 summarizes these researches. It shows that 90.9% of the previous models are static and only 9.1% of them are dynamic
From: A dynamic credit risk assessment model with data mining techniques: evidence from Iranian banks
Authors’ name | Techniques | Static / Dynamic | Type of predictor (Certain/Uncertain) |
|---|---|---|---|
Hussain Ali Bekhet et al., 2014 | ANN: RBF | Static | Certain |
Gusti Ngurah Narndra Mandalaa. Et al, 2012 | Decision Tree: c 5.0 | Static | Certain |
Weimin Chen et al., 2012 | Clustering, SVM | Static | Certain |
Fatemeh Nemati Koutanaei et al., 2015 | GA, SVM, PCA | Static | Certain |
Zhiwang Zhang et al., 2014 | Kernel, fuzzification, penalty factors | Static | Certain |
Danenas P et al., 2015 | SVM | Static | Certain |
Ghodselahi, 2011 | SVM, Fuzzy clustering | Static | Certain |
Shahrzad Zaman, 2013 | MLP, RBF | Static | Certain |
Vahid Baradaran, 2015 | ANFIS | Static | Certain |
Blanco et al., 2013 | MLP, linear discriminant analysis, quadratic discriminant analysis, logistic regression | Dynamic | Certain |
Bensic et al., 2005 | Logistic regression, NNs and Classification and regression trees | Static | Certain |
West, 2000 | Linear discriminant, analysis and logistic regression, decision trees, kernel density estimation, nearest neighbor | Static | Certain |
Witkowska et al., 2004 | MLP, RBF | Static | Certain |
Yeh et al., 2009 | K-nearest neighbor (KNN) classifiers, Logistic regression, Discriminant analysis, Naı¨ve Bayesian classifier, Classification trees, ANN | Static | Certain |
Ping et al., 2011 | SVM | Static | Certain |
Tsai, 2008 | MLP | Static | Certain |
Twala, 2010 | ANN, decision tree, NaĂŻve Bayes,k-NN,logistic, discriminant analysis | Static | Certain |
Hsieh et al., 2010 | NN, support vector machine, and Bayesian network | Static | Certain |
Paleologo et al., 2010 | SVM, decision trees, KNN, AdaBoost, Subagged classifiers | Static | Certain |
Wang et al., 2011 | SVM | Static | Certain |
Oreski et al., 2014 | Presented a new hybrid GA with ANN | Static | Certain |
Maria Rocha Sousa et al., 2016 | Generalized Additive Model (GAM) | Dynamic | Certain |