Fuzzy Model for Assessing the Creditworthiness of Ukrainian Coal Industry Enterprises

of representation of fuzzy knowledge at an estimation of
creditworthiness of the enterprises of the coal industry of Ukraine and
perfection of a fuzzy mathematical model of an estimation of
creditworthiness of the enterprises is carried out. Based on settheoretic analysis, a set of 11 criteria for assessing the
creditworthiness of enterprises is formed and divided into 3 groups:
indicators of financial stability, analysis of profits and losses, the
efficiency of enterprise management. A membership function is
constructed for each criterion, which will reveal the uncertainty in the
input data, leading to a normalized form for comparison. To construct
membership functions, a study was conducted to determine their type
and type, as well as the parameters of membership functions based
on the experience of credit experts and data sets on indicators, using
real financial reports of Ukrainian coal industry enterprises for 2020.
The improved fuzzy mathematical model for assessing the
creditworthiness of enterprises, which reveals the vagueness of input
data, derives the assessment of creditworthiness based on the
reasoning of the decision-maker (DM), determines the linguistic level
of ability to repay financial obligations on time. Based on the built
model, a general six-step algorithm is constructed, which can be
quickly implemented in the software product. The developed
information model and the improved fuzzy mathematical model were
tested on real data of credit assessment of the Lvivugol State
Enterprise of Ukraine. Outcome, models, and approaches to
presenting fuzzy knowledge for indicators of creditworthiness
assessment of Ukrainian coal industry enterprises, which will be a
model for other countries to follow.