Credit Risk Assessment by Ordered Fuzzy Numbers

Abstract

Credit risk assessment usually is a complex process which consists of many successive steps and numerous criteria. Selection of good customers and rejection of potentially bad ones is vital as it directly and significantly affects the quality of bank’s credit portfolio. Also, ordering the decision alternatives is an important part of the whole decision-making analysis which takes place before making a final decision. The importance and complexity of the problem on one hand call for strictly analytical methods, however, on the other, also for a method which enables intuitive decision-making, imprecision and inaccurate linguistic ranks based on experts’ personal experience. The paper presents the utility of Simple Additive Weighting (SAW) method (which belongs to the multicriteria decision-making approach) in case of a credit risk assessment. The presented illustrative example bases on experts’ knowledge and their perception and evaluation of various linguistic, frequently imprecise criteria. Therefore, the order scale is described by ordered fuzzy numbers (OFN).