Intelligent financial warning model using Fuzzy Neural Network and case-based reasoning

Creating an applicable and precise financial early warning model is highly desirable for decision makers and regulators in the financial industry. Although Business Failure Prediction (BFP) especially banks has been extensively a researched area since late 1960s, the next critical step which is the decision making support scheme has been ignored. This paper presents a novel model for financial warning which combines a fuzzy inference system with the learning ability of neural network as a Fuzzy Neural Network (FNN) to predict organizational financial status and also applies reasoning capability of Fuzzy Case-Based Reasoning (FCBR) to support decision makers measuring appropriate solutions. The proposed financial warning model generates an adaptive fuzzy rule base to predict financial status of target case and then if it is predicted to fail, the FCBR is used to find similar survived cases. Finally according similar cases and a fuzzy rule base, the model provides financial decisions to change particular features as company goals in upcoming year to avoid future financial distress.

[1]  Antonio Terceño Gómez,et al.  A model for the prediction of "diseases" of firms by means of fuzzy relations , 2008, Fuzzy Sets Syst..

[2]  Hui Li,et al.  Business failure prediction using hybrid2 case-based reasoning (H2CBR) , 2010, Comput. Oper. Res..

[3]  Sofie Balcaen,et al.  35 years of studies on business failure: an overview of the classic statistical methodologies and their related problems , 2006 .

[4]  Shaio Yan Huang,et al.  Alternative diagnosis of corporate bankruptcy: A neuro fuzzy approach , 2009, Expert Syst. Appl..

[5]  Jyh-Shing Roger Jang,et al.  ANFIS: adaptive-network-based fuzzy inference system , 1993, IEEE Trans. Syst. Man Cybern..

[6]  Ruei-Yuan Chang,et al.  A New Approach to Modeling Early Warning Systems for Currency Crises : can a machine-learning fuzzy expert system predict the currency crises effectively? , 2006 .

[7]  Kyung-shik Shin,et al.  A genetic algorithm application in bankruptcy prediction modeling , 2002, Expert Syst. Appl..

[8]  C. R. Mount,et al.  A case-based reasoning system for identifying failure mechanisms , 2000 .

[9]  E. Davis,et al.  Comparing early warning systems for banking crises , 2008 .

[10]  Gary M. Weiss.  Mining with rarity: a unifying framework , 2004, SKDD.

[11]  Chin-Teng Lin,et al.  An ART-based fuzzy adaptive learning control network , 1997, IEEE Trans. Fuzzy Syst..

[12]  Hamid R. Berenji,et al.  Learning and tuning fuzzy logic controllers through reinforcements , 1992, IEEE Trans. Neural Networks.

[13]  Chai Quek,et al.  A novel fuzzy neural approach to data reconstruction and failure prediction , 2009 .

[14]  Ramón López de Mántaras,et al.  Case-Based Reasoning: An Overview , 1997, AI Commun..

[15]  Hiok Chai Quek,et al.  FCMAC-EWS: A bank failure early warning system based on a novel localized pattern learning and semantically associative fuzzy neural network , 2008, Expert Syst. Appl..

[16]  Nitesh V. Chawla,et al.  Editorial: special issue on learning from imbalanced data sets , 2004, SKDD.

[17]  Hiok Chai Quek,et al.  GenSo-EWS: a novel neural-fuzzy based early warning system for predicting bank failures , 2004, Neural Networks.

[18]  Nathalie Japkowicz,et al.  The class imbalance problem: A systematic study , 2002, Intell. Data Anal..

[19]  Ruowei Zhou,et al.  POPFNN-AAR(S): a pseudo outer-product based fuzzy neural network , 1999, IEEE Trans. Syst. Man Cybern. Part B.

[20]  Ester Bernadó-Mansilla,et al.  Evolutionary rule-based systems for imbalanced data sets , 2008, Soft Comput..

[21]  María José del Jesús,et al.  On the influence of an adaptive inference system in fuzzy rule based classification systems for imbalanced data-sets , 2009, Expert Syst. Appl..

[22]  Enric Plaza,et al.  CasedBased Reasoningc an overview , 1997 .

[23]  Yongsheng Ding,et al.  Forecasting financial condition of Chinese listed companies based on support vector machine , 2008, Expert Syst. Appl..

[24]  Sheng-Tun Li,et al.  Predicting financial activity with evolutionary fuzzy case-based reasoning , 2009, Expert Syst. Appl..

[25]  Vadlamani Ravi,et al.  Bankruptcy prediction in banks and firms via statistical and intelligent techniques - A review , 2007, Eur. J. Oper. Res..

[26]  Tae Yoon Kim,et al.  Usefulness of artificial neural networks for early warning system of economic crisis , 2004, Expert Syst. Appl..

[27]  Zhongsheng Hua,et al.  Predicting corporate financial distress based on integration of support vector machine and logistic regression , 2007, Expert Syst. Appl..

[28]  María José del Jesús,et al.  Hierarchical fuzzy rule based classification systems with genetic rule selection for imbalanced data-sets , 2009, Int. J. Approx. Reason..

[29]  Ingoo Han,et al.  A case-based reasoning with the feature weights derived by analytic hierarchy process for bankruptcy prediction , 2002, Expert Syst. Appl..