The aim of the subject of the study was to formulate a new methodological approach and a mathematical model based on the theory of fuzzy sets that will help to make the right decision on the need for lending to small business enterprises.

The speaker noted that for creditworthiness evaluations are built indicator ratings fuzzy subsets. Moreover, each level has its numerical value.

It should also be noted that 22 indicators were examined for creditworthiness assessment, which in turn divided into 2 groups; qualitative and quantitative.

The speaker also presented the peculiarities of the rating determination process. It is made for all the X crowd indices and the resulting ratings are summarized by forming the final rating-Q.This allows making a decision to refuse or provide lending.

Taking into account all options of the bank lending scheme and Q, the optimal option is chosen.At the end of the seminar, the rapporteur noted that in order to ensure that borrowers' creditworthiness assessment reliability in commercial banks is necessary to conduct the automation of assessment process, with the use of fuzzy sets tools and the mathematical rules.

This will reduce the credit risk, the risk of subjectivity of a credit evaluation specialist, will minimize the impact of deliberate errors in the information provided by the enterprise and accelerate the decision making process.