Application of the Oriented Fuzzy Numbers in Credit Risk Assessment

Abstract

Over the years, banks have faced many difficulties, related mainly to lax credit standards for borrowers and counterparties. The goal of credit risk management is to maintain the volume of credit risk at acceptable level as it is a vital feature in risk management. Credit analysts take into consideration factors of a wider spectrum, e.g., the prospects of the line of business, the experience of board members, credibility of suppliers, etc. Those factors are often considered on the linguistic scale, which includes such imprecise and inaccurate phrases, for instance, such as: more/less experienced, better/worse prospects, etc., which, for the experts and decision makers, are justified and result from their personal experience, preferences and human nature. The paper presents the approach of supporting methods in the credit risk decision-making process. It presents evaluation scales of imprecise phrases commonly used during the process of credit risk assessment based on experts’ preferences. Due to the imprecision, the oriented fuzzy numbers are a useful tool. For such described evaluation scales, we use a scoring function determined with the use of an adapted Simple Additive Weighting (SAW) method.

Associated probabilities aggregations in multistage investment decision-making

“…Application of the AsF M operators in fuzzy MSDMM for optimal investments Authors often use heuristic approaches in their works dedicated to credit risk assessments. These include fuzzy modeling, fuzzy neural networks, machine learning, genetic programming and more (Breeden, 2021;Chang et al, 2020;De et al, 2019;Deng and Yuan, 2021;Froelich and H ajek, 2019;Hassani et al, 2021;Kamalloo and Saniee Abadeh, 2014;Santana et al, 2018;Shen et al, 2019;Shen et al, 2018;Song et al, 2020;W ojcicka-W ojtowicz and Piasecki, 2021;Wu et al, 2014;Zhang et al, 2015;Zhu et al, 2019).…”

“…This method combines the use of fuzzy logic with a neural network and a variable population optimization technique to obtain fuzzy classification rules. The work developed in Wójcicka-Wójtowicz and Piasecki (2021) presents the approach of supporting methods in the credit risk decision-making process. It presents evaluation scales of imprecise phrases commonly used during the process of credit risk assessment based on experts' preferences.…”

The Extended Linguistic Hellwig’s Methods Based on Oriented Fuzzy Numbers and Their Application to the Evaluation of Negotiation Offers

“…The differences between fuzzy numbers, Kosiński numbers, and oriented fuzzy numbers have been discussed in detail by Piasecki and Łyczkowska-Hanćkowiak [ 33 , 34 ]. The OFNs were used in economics and finance for evaluation of the process of the assessment of the credit standing of the potential borrower [ 35 , 36 ], for modeling Japanese candles [ 37 ], for present value evaluation under the impact of behavioral factors [ 38 ], in portfolio analysis [ 39 ] or imprecise investment recommendations [ 40 ].…”

“…The applications of the TOPSIS technique based on oriented fuzzy numbers (OF-TOPSIS) to support the evaluation of negotiation offers have been studied by Piasecki and Roszkowska [ 17 ]. In other papers, the problems of the SAW technique based on oriented fuzzy numbers (OF-SAW) were discussed, especially the fuzzy ranking of evaluated alternatives [ 21 ], the impact of the orientation of the ordered fuzzy assessment on the OF-SAW method, application of the OF-SAW method in credit risk assessment [ 35 , 36 ].…”