A nature inspired Ying–Yang approach for intelligent decision support in bank solvency analysis

Gaussian case-based reasoning for business failure prediction with empirical data in China

“…Sun and Shenoy [51] used naive Bayesian network models for BFP. Nguyen et al [37] attempted to employ the Chinese theory of yin and yang for BFP. Sun and Li [48] presented a group decision-aiding method for business failure early warning signs, introducing a new style of predicting business failure supplementary to quantitative methods.…”

Detection of fraudulent financial statements using the hybrid data mining approach

“…Studies applying DT techniques to detect fraudulent financial statements include: Hansen et al ( 1992 ), Koh ( 2004 ), Kotsiantis et al ( 2006 ), Kirkos et al ( 2007 ), and Salehi and Fard ( 2013 ). Studies applying BBN techniques to detect fraudulent financial statements include: Kirkos et al ( 2007 ), and Nguyen et al ( 2008 ). Studies that apply SVM techniques to detect fraudulent financial statements include: Zhou and Kapoor ( 2011 ), Shin et al ( 2005 ), Chen et al ( 2006 ), Yeh et al ( 2010 ), Ravisankar et al ( 2011 ), Pai et al ( 2011 ).…”

Bank failure prediction using an accurate and interpretable neural fuzzy inference system

“…However, it is stated in [41] that soft computing models overcome the deficiencies of traditional statistical models whose results do not possess semantic meanings. The data set used in this paper has been analyzed by different NFISs in the literature [41,39,40,25,30] for different purposes with different configurations. In this paper, we focus on the balance between accuracy and interpretability (not studied in the previous works) of the constructed model and the effectiveness to generate early warnings for potentially failing banks.…”

“…In the bank failure prediction application, NFIS can be applied to identify the inherent characteristics of the failed banks and thus allows us to semantically and numerically understand the financial distress that leads to a bank failure. In the literature, there are a series of promising NFISs proposed to forecast bank failures [41,39,40,25,30]. Although these models are accurate in prediction, none of them focuses on the improvement of interpretability.…”