magistrsko delo
Rebeka Dobaja (Author), Iztok Kolar (Mentor)

Abstract

Računovodske prevare in še posebej prevarantsko poročanje so pereč problem, ki predstavljajo trn v peti revizorjev, investitorjem, forenzičnim računovodjem in vsem drugim, ki sprejemajo odločitve o obravnavanem podjetju. Na prvi pogled je precej težko oceniti, ali podjetje resnično in pošteno prikazuje svoje poslovanje skozi računovodske izkaze in poslovno poročilo. Zato so se v praksi uveljavile različne tehnike, načini, pristopi, ki odločevalcem omogočajo pridobitev informacij na drugačen način, s tem pa bodo ocenili verjetnost, ali podjetje prevarantsko poroča ali ne. Cilj magistrske naloge je preučiti analitične pristope, njihove sestavne dele, izračune in interpretacijo rezultatov ter le-to uporabiti na primeru podjetja, ki verjetno ni manipulator, in na primeru podjetja, ki verjetno je manipulator. Uporabljena modela sta nam podala rezultate in informacije, s katerimi smo lahko potrdili že znana dejstva o podjetjih, predstavili informacijo za tiste, ki se o obravnavanem podjetju odločajo in sprejemajo odločitve, ter primerjali razlike in podobnosti dobljenih končnih rezultatov za tekoče leto in še za štiri pretekla leta med dvema različnima podjetjema. Za podjetje X smo na podlagi modela M-vrednosti in modela C-vrednosti ugotovili, da z veliko verjetnostjo ni manipulator, za podjetje Y pa smo na podlagi istih modelov ugotovili, da je večja verjetnost, da je podjetje Y manipulator, posledično pa so računovodski izkazi prikrojeni. To smo ugotovili predvsem za leto 2017 in 2020 na podlagi modela M-vrednosti, na podlagi modela C-vrednosti pa zgolj za leto 2020. Po opravljenih preučevanjih modelov in analitičnih pristopov ugotavljamo, da modeli niso povsem zanesljivi, pa vendar bi lahko odločevalcem lahko pravilno sugerirali pri sprejemanju odločitev oziroma vsaj pri ocenjevanju tveganosti sprejema odločitve glede obravnavanega podjetja.

Keywords

računovodski izkazi;prevare;tveganje;analiza;analitični pristop;

Data

Language: Slovenian
Year of publishing:
Typology: 2.09 - Master's Thesis
Organization: UM EPF - Faculty of Economics and Business
Publisher: R. Dobaja
UDC: 657.6:343.721
COBISS: 81868035 Link will open in a new window
Views: 353
Downloads: 88
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Other data

Secondary language: English
Secondary title: Application and analytical approaches in detecting fraud in the financial statements
Secondary abstract: Accounting fraud and especially fraudulent reporting are a burning issue tasking auditors, investors, forensic accountants, and all others who make decisions about the company in question. At first glance, it is quite difficult to assess whether a company is truly and fairly presenting its business through financial statements and a business report. To this end, different techniques, methods, and approaches have been established in practice. All that enables decision-makers to obtain information in a different way. Thus, they will assess the probability of whether the company is fraudulently reporting or not. The goal of the master's thesis is to examine analytical approaches, their components, calculations, and interpretation of results, as well as to apply them in the case of a company that is unlikely to be a manipulator and in the case of a company that is likely to be a manipulator. The used models gave us results and information with which we could confirm already known facts about companies, present information for those who decide and make decisions about the company in question, and compare the differences and similarities of the final results for the current year and also four more previous years between two different companies. Based on the M-Score model and the C-Score model, we ascertained with a high probability for company X that it is not a manipulator. Also based on the M-Score model and the C-Score model, we ascertained for company Y that there is a higher probability that company Y is a manipulator. Consequently, the financial statements are tailored. We ascertained this mainly for 2017 and 2020 on the basis of the M-Score model. On the other hand, we ascertained this only for the year 2020 on the basis of the C-Score model. After studying the models and analytical approaches, we find that the models are not completely reliable. However, we could correctly suggest to decision-makers when making decisions or, at least, when assessing the risk of making decisions about the company in question.
Secondary keywords: Accounting Fraud;Fraudulent reporting;Risk management;Beneish M-Score model;Montier’s C-Score model.;
Type (COBISS): Master's thesis/paper
Thesis comment: Univ. v Mariboru, Ekonomsko-poslovna fak.
Pages: III, 67 str., 5 str. pril.
ID: 13274260