Group decision-making using improved multi-criteria decision making methods for credit risk analysis
2016
Credit risk analysis is a core research issue in the field of financial risk
management. This paper first investigates the analytic hierarchy process
(AHP) as a method of measuring index weights for group decision-making (GDM).
AHP for group decision-making (AHP-GDM) is then researched and applied,
taking into full account the cognitive levels of different experts. Second,
the concept of grey relational degree is introduced into the ideal solution
of the technique for order of preference by similarity to ideal solution
(TOPSIS). This concept fully considers the relative closeness of grey
relational degree between alternatives and the ”ideal” solution in order to
strengthen their relationship. The AHP-GDM method overcomes the problem of
subjectivity in measuring index weights, and the revised TOPSIS (R-TOPSIS)
method heightens the effectiveness of assessment results. An illustrative
case using data from Chinese listed commercial banks shows that the R-TOPSIS
method is more effective than both TOPSIS and grey relational analysis (GRA)
in credit risk evaluation. The two improved multi-criteria decision making
(MCDM) methods are also applied to empirical research regarding the credit
risk analysis of Chinese urban commercial banks. The results indicate the
validity and effectiveness of both methods.
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