Decision-Making When Assessing Financing Risks Using the Logical and Linguistic Method

Problem statement: Decision-making when assessing the risks of lending to individuals is associated with the uncertainty of the influence of many factors that cannot be accurately described mathematically. This leads to situations that reduce the likelihood of assessing the risks of non-refund. Among the various methods for assessing the risk of non-repayment of funds, one can highlight the scenario approach, which uses methods of fuzzy set theory to calculate the values of membership functions. However, the problem of ranking a set of non-repayment risk scenarios, taking into account the mental properties of experts and borrowers, has not been sufficiently studied. The purpose: Assessing the risks of financing and lending to individuals, taking into account the borrower’s temperament and the preferences of experts based on the logical–linguistic method. Development of algorithms for calculating the risk assessment of lending to the analyzed individual and determining its rating. Results: Based on the proposed risk assessment method, an algorithm for calculating the risk assessment of non-repayment of funds has been developed. Using computer modeling, it is shown that when the opinions of experts vary, setting the significance coefficients of borrower indicators at approximately 30%, individual experts can give a worse risk forecast than the average assessment of several experts. Therefore, when assessing the risk of loan non-repayment of funds, it is advisable to use at least 5 experts and rank the borrower according to the average score. Practical significance: The research results can be used to create a methodology for assessing the risks lending to individuals.