Affiliation
a Kemerovo Institute of Food Science and Technology (University)
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Abstract
Due to the fact that commercial crediting is a relatively new form of credit relations in modern Russia, there are no complete methodical technologies aimed at credit risk estimate in production sphere in home literature. This explains the interest of the authors to recommendations of foreign scientists in the field of estimating procedures including those based on the quality vector of debit and credit debts as key characteristics of a commercial credit. Analytical and financial-engineering studies have been carried out in 2 stages: the identification and grouping of credit risk indicators in the field of commercial credit; unification of credit risk indicators in the form of the discursive algorithm. The identified credit risk indicators are of interest not so much from the standpoint of their private studies but in terms of the possibility of analytical tools engineering based on them. Construction of a new analytical scheme has been preceded by a thematic grouping of indicators necessary to highlight the key vectors in the estimating procedure. Five trends in credit risk estimate are clearly traced within the commercial credit analysis: the quality of debit indebtedness, the quality of creditor indebtedness, the degree of their contingency, liquidity, and stock dynamics. Based on the results of the thematic grouping of indicators, the authors have developed a discursive algorithm of debtors’ differentiation for credit risk groups taking into account their region-and-branch sectors.
Keywords
Credit risk,
commercial lending,
discursive algorithm,
credit risk indicators
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