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The problem of timely repayment of loans at all times has been and continues to be actual for commercial banks. Overcoming this problem substantially depends on the quality of the solvency assessment of potential borrowers, which is carried out by experts on the basis of retrospective information. In the microcredit system, the assessment of the borrower's credit history is usually carried out by an expert who mainly relies on his heuristic knowledge and intuition, which usually extols subjective considerations that do not have sufficient grounds. In practice, the opinions of different analysts or those responsible for making credit decisions often differ, especially if controversial situations are considered that have many acceptable alternative solutions. As a result, in assessing the solvency of potential microloan borrowers, the subjective opinion of the expert and the incompetent or deliberate interpretation of the information resulting in the adoption of decisions that are detrimental to the microfinance organization are overweight. To increase the degree of objectivity, the paper discusses an approach to assessing the responsibility and solvency of microloan borrowers, based on the use of the fuzzy method of maximin convolution. This approach, given the poorly structured personal data of applicants, allows them to be flexibly and quickly assessed for the provision of microloans. The qualitative assessment criteria applied in this case are weighed based on expert opinions regarding the priority of each of them. An important advantage of the proposed model is that it is simple, convenient to use and able to adapt to the requirements of various micro-financial organizations.

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