CLASSIFICATION OF BANK DEBTOR DISTRESS BASED ON OFFICIAL FINANCIAL STATEMENTS

Abstract

Rad predstavlja rezultate istraživanja klasifi kacije poslovnih problema trgovačkih društava dužnika banke. Istraživanje je provedeno na polaznom uzorku veličine 168 jedinica – dužnika banke, a korišteno je 15 omjera do-bijenih iz osnovnih fi nancijskih izvješća. U radu su primijenjeni višestruka diskriminacijska analiza, logit model i metoda višedimenzionalnih skala za razvrstavanje trgovačkih društava prema urednosti izmirenja obveza prema banci. Budući da diskriminacijskom analizom i logit modelom nije bilo moguće uspješno razlikovati dobra i srednja društva, polazni je uzorak sužen na 141 jedinicu, pa su ga činila trgovačka društva grupirana na dobra i loša. Svi kreirani modeli pokazali su visok stupanj pouzdanosti predviđanja poslovnih problema društava u poslovnim odnosima s bankom, što je potvrđeno i na kontrolnom uzorku. Istraživanje je također pokazalo da se i metodom višedimenzionalnih skala može uspješno koristiti pri grupiranju društava prema razini poslovnih problema uz korištenje odgovarajućih financijskih omjera.The paper presents research of models for classification of bank debtor distress based on ratios calculated from official financial statements. Basic sample consists of 168 company’s debtors of middle size bank, and 15 financial ratios were used. In research multiple discriminate analyses, logit model and multidimensional scaling method was used for classifying companies based on orderliness in payment of their liabilities. Since discriminate analysis and logit model could not successfully discriminate “good” and “medium” companies, basic sample was appropriately limited to 141 companies classified as “good” or “dubious”. All estimated models have high rate of reliability in prediction of orderliness in payment of liabilities that can express the degree of company’s efficiency or distress. Reliability of all created models was confirmed on control sample as well. This research also demonstrated that multidimensional scaling methods can be successfully used for classifying of companies based on magnitude of their business problems using appropriate financial ratios

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