The Use of the Discriminant Analysis for Obtaining Audit Evidence (I)
Author:
Prof. Univ. PhD Elisabeta JABA, Ioan-Bogdan ROBU
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DOI:
Keywords:
discriminant analysis, audit evidence, analytical procedures, influence factors
Abstract:
In the current economic context, the financial audit mission plays an essential role in terms of providing financial information and a valid quality. Given the complexity but also many economic operations which a firm can perform, the financial auditor has its own methodology and instruments, which will help him to issue the audit report.\r\nThe classic status of a firm can be analyzed by economico-financial indicators surprised in the balance sheet, income statement and related situations. Thus, based on this information, financial audit mission requires to express a competent and reasonable opinion on substantial evidence contained in these situations, whose aim is to ensure compliance with an identified financial reporting framework.\r\nHaving to use a statistical tool for diagnosis the state firms at some point, in the financial audit mission of collecting the audit evidence through analytical procedures proposed by the International Standard on Auditing (ISA) 500 ”Audit evidence”, ISA 520 ”Analytical Procedures” and ISA 530 ”Audit Sampling”, one of the proposed solution for diagnostic is discriminant analysis. Intended use is to classify firms by their state, expressed through economic and financial indicators. Thus, starting from the standard levels of performance in the literature and from a number of factors of influence, in this paper is built a discriminatory function that can be used for the classification of firms, in order to obtain audit evidence.\r\nThe study was conducted on a sample of 60 companies, listed on Bucharest Stock Exchange (BSE). The results obtained are a classification of firms into 3 categories (leader, middle, least). The mathematical model obtained can be used to forecast the state of any company not covered by the sample on the basis of economic and financial results, using discriminatory function.\r\n