Which of the following would not be considered when planning an audit data Analytic ADA

Which of the following would not be considered when planning an audit data Analytic ADA

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Which of the following would not be considered when planning an audit data Analytic ADA

Which of the following would not be considered when planning an audit data Analytic ADA

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Highlights

Audit firms adopt advanced data analytics (ADA) through a process.

The process is composed of several activities across different organizational units.

The adoption of ADA is led by the Big Four and their close competitors.

The technological capabilities of audit firms are highly important for the successful adoption.

The identification of use cases is a crucial activity in the adoption process.

Abstract

Audit firms are increasingly engaging with advanced data analytics to improve the efficiency and effectiveness of external audits through the automation of audit work and obtaining a better understanding of the client’s business risk and thus their own audit risk. This paper examines the process by which audit firms adopt advanced data analytics, which has been left unaddressed by previous research. We derive a process theory from expert interviews which describes the activities within the process and the organizational units involved. It further describes how the adoption process is affected by technological, organizational and environmental contextual factors. Our work contributes to the extent body of research on technology adoption in auditing by using a previously unused theoretical perspective, and contextualizing known factors of technology adoption. The findings presented in this paper emphasize the importance of technological capabilities of audit firms for the adoption of advanced data analytics; technological capabilities within audit teams can be leveraged to support both the ideation of possible use cases for advanced data analytics, as well as the diffusion of solutions into practice.

Keywords

Audit digitization

Audit data analytics

Big data

Machine learning

Advanced data analytics in auditing

Audit innovation

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© 2021 The Authors. Published by Elsevier Inc.

16)Which of the following is not a reason for datacleansing?A)Fields that should contain dates may have lettersB)Data may be too large in volumeC)Fields may contain data outside preset acceptablevaluesD)All of theabove are reasons for datacleansing

17)The professional standards for audit documentationare quite high. The documentation must contain enoughinformation to allow an experienced auditor to understand thenature, timing, extent, and results of the audit. Which of thefollowing is required foraudit documentation forADA to meet thisstandard?

18)When performing an Audit Data Analytic (ADA), anauditor must exercise professional skepticism in all of thefollowing situationsexcept:

Which of the following would not be considered when planning an audit data Analytic ADA

A)Discovering and analyzing patterns in dataB)Identifying anomalies in dataC)Extracting useful information in dataD)All of thesechoices are correct.20)Which of the following would not be considered whenplanning an Audit Data Analytic (ADA)?

21)In order to be considered sufficient, documentationshould be prepared so that an experienced auditor, with noprior connection with the engagement can understandThenature, timing, and extent of procedures performedThedifficulty of the auditResults of procedures and evidenceobtainedConclusionsreached and significantjudgments madeA)I and IIIB)III and IVC)I, III, and IVD)I, II, III, andIV

22)Audit Data Analytics (ADA) allow the auditor totest/analyze 100% of the data rather than a sample. What isthe benefit of being able to test the entire population of data?

Which of the following would occur during the planning stage of ADA?

Which of the following would occur during the planning stage of Audit Data Analytics? Auditor must determine the nature, timing, and extent of the work that will be completed as part of the ADA.

What are all of the basic steps that an auditor might use for audit data analytics ADA )?

The 5-step approach includes:.
Step 1) Plan the Audit Data Analytics. ... .
Step 2) Access and prepare the data for the audit data analytics (ADA) ... .
Step 3) Consider the relevance and reliability of the data used. ... .
Step 4) Perform the ADA. ... .
Step 5) Evaluate the results and come to conclusion on ADA's overall effectiveness..

In which stage's of an audit can analytical procedures be performed quizlet?

Analytical procedures are performed in the audit planning stage to help the auditor decide the other evidence needed to satisfy sufficient competent evidence requirements.

Which assertion category does the following audit objective relate to accounts receivable include all claims on customers at the balance sheet date?

The account balance audit objective, "Accounts receivable presents gross claims on customers at balance date and agree with the sum of the accounts receivable subsidiary ledger", is derived from the assertion category of: accuracy, valuation and allocation.