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An intelligent-agent-based fuzzy group decision making model for financial multicriteria decision support: The case of credit scoring
Authors:Lean Yu  Shouyang Wang  Kin Keung Lai
Institution:1. Institute of Systems Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100080, China;2. Department of Management Sciences, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong
Abstract:Credit risk analysis is an active research area in financial risk management and credit scoring is one of the key analytical techniques in credit risk evaluation. In this study, a novel intelligent-agent-based fuzzy group decision making (GDM) model is proposed as an effective multicriteria decision analysis (MCDA) tool for credit risk evaluation. In this proposed model, some artificial intelligent techniques, which are used as intelligent agents, are first used to analyze and evaluate the risk levels of credit applicants over a set of pre-defined criteria. Then these evaluation results, generated by different intelligent agents, are fuzzified into some fuzzy opinions on credit risk level of applicants. Finally, these fuzzification opinions are aggregated into a group consensus and meantime the fuzzy aggregated consensus is defuzzified into a crisp aggregated value to support final decision for decision-makers of credit-granting institutions. For illustration and verification purposes, a simple numerical example and three real-world credit application approval datasets are presented.
Keywords:Multicriteria decision analysis  Fuzzy group decision making  Intelligent agent  Credit scoring  Artificial intelligence
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