| Abstract [eng] |
Analytical procedures are the most widely used tool in the auditor’s work. The application of analytical procedures is considered to be an integral part of the overall audit process and a valuable tool in gathering and evaluating appropriate and sufficient audit evidence, which enables the auditor to express an opinion on the financial statements. The literature has examined that analytical procedures are diverse, i. y. they can be performed on the basis of both financial and non-financial data of the audited entities. Analytical procedures can simplify the audit process by focusing on the planning phase and save time and money for audit firms if they are performed and interpreted correctly and efficiently. Carefully designed analytical procedures can be as efficient as essential detailed tests or, depending on the circumstances, even more effective. Research findings and insights suggest that the use of these procedures in financial audits will increase in the future, through the integration of audited clients' financial and non-financial information and the use of modern automated tools such as data analytics or artificial intelligence techniques. These tools make it easier for auditors to analyze large amounts of data and gain a better understanding of client’s business operations, in this way increasing the effectiveness and efficiency of external audit. For this reason, the aim of this master thesis was to develop an extended analytical procedures application model in audit planning, which collects and evaluates audit evidence depending on audited business specifics with a focus on assessing the risk of material misstatement. The developed model is a practical and effective tool for the application of analytical procedures, implementing the auditor’s goal of performing audits more efficiently and effectively ensuring high audit quality. The model was tested on the example of five small companies with different activities. After identifying and considering the specific risk areas of the analyzed businesses during the qualitative study, the appropriate extended analytical procedure and system of indicators is applied to each analyzed company in the quantitative study. The results confirmed that knowing the risky areas of companies in the audited industries during the planning phase can steer the procedures in a targeted direction, which leads to reduced time costs, detected distortions in customer data more quickly and decrease the need to apply other tests. |
