Preparing for Audit Data Analytics with the AICPA General Ledger Audit Data Standards

2020 ◽  
Author(s):  
Lorraine S. Lee ◽  
Gretchen Casterella ◽  
Barry Wray
Keyword(s):  
Data Analytics ◽  
Task Force ◽  
Writing Skills ◽  
Financial Statement ◽  
Journal Entry ◽  
Data Standards ◽  
Microsoft Access ◽  
Financial Statement Audit ◽  
Audit Data ◽  
Client Data

It is challenging for auditors to effectively and efficiently use data analytics in audit procedures and general ledger testing when the data acquired from clients is often incomplete and not in a usable format. Considerable time must be spent cleansing, transforming, standardizing, and validating the data prior to analyzing it. This problem motivated the AICPA task force to develop a set of Audit Data Standards for streamlining the exchange of data.  This paper describes an extensive exercise where students: 1) develop a Microsoft Access database that complies with the Audit Data Standards (ADS) for general ledger data; 2) cleanse and transform non-standardized client data for import into an ADS-compliant database; and 3) write queries for general ledger testing and journal entry testing. The exercise strengthens students’ database and query-writing skills while introducing the ADS in the context of realistic tasks to support a financial statement audit.

Automated Clustering for Data Analytics

2019 ◽  
Vol 16 (2) ◽  
pp. 43-58 ◽  
Author(s):  
Paul E. Byrnes
Keyword(s):  
Data Analytics ◽  
Financial Statement ◽  
Decision Point ◽  
Technical Aspects ◽  
Fraud Risk ◽  
Use Of Data ◽  
Decision Points ◽  
Financial Statement Audit ◽  
Mining Methods ◽  
Construction Model

ABSTRACT Today, auditors must consider the risks of material misstatement due to fraud during the financial statement audit (Messier, Glover, and Prawitt 2016). Current audit guidance recommends the use of data mining methods such as clustering to improve the likelihood of discovering irregularities during fraud risk assessment (ASB 2012). Unfortunately, significant challenges exist relative to using clustering in practice, including data preprocessing, model construction, model selection, and outlier detection. The traditional auditor is not trained to effectively address these complexities. One solution entails automation of clustering, thus eliminating the difficult, manual decision points within the clustering process. This would allow practitioners to focus on problem investigation and resolution, rather than being burdened with the technical aspects of clustering. In this paper, automated clustering is explored. In the process, each manual decision point is addressed, and a suitable automated solution is developed. Upon conclusion, a clustering application is formulated and demonstrated.

scholarly journals The Consideration Of Fraud In A Financial Statement Audit: Some Study Questions

2007 ◽  
Vol 3 (1) ◽  
pp. 37-44
Author(s):  
Eddie Metrejean ◽  
Lou X. Orchard ◽  
Dwight Sneathen Jr
Keyword(s):  
Financial Reporting ◽  
Major Part ◽  
Task Force ◽  
Financial Statement ◽  
Accounting Students ◽  
Fraudulent Financial Reporting ◽  
Financial Statement Audit ◽  
Auditing Standards

In October 2002, the Auditing Standards Board (ASB) issued Statement on Auditing Standards (SAS) No. 99, Consideration of Fraud in a Financial Statement Audit in response to recommendations from the Fraud Task Force. SAS No. 99 is intended to improve auditor performance during audits and to increase the likelihood that the auditors will detect fraudulent financial reporting if any is present. Since fraud awareness is such a major part of any audit, accounting students should be well versed on the content of SAS No. 99. However, not all accounting students read SASs in detail. Then how do accounting educators get this important content to these students?

Old Main Manufacturing: The Case of Unrecorded Sales Discounts

2012 ◽  
Vol 28 (1) ◽  
pp. 173-179
Author(s):  
David Peaden ◽  
Nathaniel M. Stephens
Keyword(s):  
Technical Writing ◽  
Writing Skills ◽  
Financial Statement ◽  
Applied Learning ◽  
Class Time ◽  
Reasonable Amount ◽  
Financial Statement Audit ◽  
Efficient Communication ◽  
Audit Information ◽  
Audit Program

ABSTRACT: The purpose of this case is to provide auditing students with an opportunity for applied learning in a realistic audit setting. The objectives of the case are: (1) to introduce students to the applied use of audit documentation, including the audit program and work papers; (2) to provide students with greater understanding of how various company records can be used by the auditor in his/her audit tests; (3) to demonstrate how the concept of materiality relates to the financial statement audit; and (4) to reinforce the importance of technical writing skills to effective and efficient communication of audit information. The case involves little class time, and students can complete the case in a very reasonable amount of time outside of class. Feedback from students has been very positive.

The AICPA Assurance Services Executive Committee Emerging Assurance Technologies Task Force: The Audit Data Standards (ADS) Initiative

2012 ◽  
Vol 26 (1) ◽  
pp. 199-205 ◽  
Author(s):  
Li Zhang ◽  
Amy R. Pawlicki ◽  
Dorothy McQuilken ◽  
William R. Titera
Keyword(s):  
Task Force ◽  
Leading Edge ◽  
Data Access ◽  
Audit Process ◽  
Process Data ◽  
Data Standards ◽  
External Auditors ◽  
Audit Data ◽  
Assurance Services ◽  
Audit Technology

ABSTRACT Data acquisition difficulties have hindered the application of advanced audit technology and audit analytics, and accentuated the challenges to meet growing audit demands. To alleviate this problem, this paper discusses the main drivers to evolve the audit process: data standards, data access, audit applications, and continuous audit. As a joint effort between the AICPA and academia, this paper provides guidance and suggestions to internal and external auditors, as well as scholars to develop knowledge for leading edge practice (Kaplan 2011).

The Effects of the Internal Control Opinion and Use of Audit Data Analytics on Perceptions of Audit Quality, Assurance, and Auditor Negligence

2021 ◽  
Author(s):  
Dereck Barr-Pulliam ◽  
Helen L Brown-Liburd ◽  
Kerri-Ann Sanderson
Keyword(s):  
Quality Assurance ◽  
Internal Control ◽  
Data Analytics ◽  
Audit Quality ◽  
Financial Statements ◽  
Entire Population ◽  
Statistical Sampling ◽  
Testing Methods ◽  
Audit Failure ◽  
Audit Data

Audit data analytics (ADAs) allow auditors to analyze the entire population of transactions which has measurable benefits for audit quality. However, auditors caution that the level of assurance on the financial statements is not incrementally increased. We examine whether the testing methodology and the type of ICFR opinion issued affect jurors' perceptions of auditor negligence. We predict and find that when auditors issue an unqualified ICFR opinion, jurors make higher negligence assessments when auditors employ statistical sampling than when they employ ADAs. Further, when auditors issue an adverse ICFR opinion, jurors attribute less blame to auditors and more blame to the investor for an audit failure. Additionally, jurors perceive the use of ADAs as an indicator of higher audit quality and are less likely to find auditors negligent. However, jurors do not perceive a difference in the level of assurance provided when auditors use ADAs versus sampling testing methods.

Fraud Detection and Investigation: Microcomputer Consulting Services

1999 ◽  
Vol 14 (1) ◽  
pp. 99-115 ◽  
Author(s):  
Bonita K. Peterson ◽  
Thomas H. Gibson
Keyword(s):  
Fraud Detection ◽  
Internal Controls ◽  
Financial Statement ◽  
Sufficient Evidence ◽  
Red Flags ◽  
Fine Line ◽  
Consulting Services ◽  
Financial Statement Audit ◽  
Audit Team ◽  
University Setting

This nonfictional case of inventory fraud in a university setting exposes students to fraud detection and investigation. These skills are becoming increasingly important for auditors, as evidenced by the alarming rate of fraud. The accounting profession has acknowledged the seriousness of this issue with the issuance of SAS No. 82, Consideration of Fraud in a Financial Statement Audit, developed in part to improve detection of frauds by auditors. The case raises many of the fraud-related issues faced by accountants: recognizing red flags indicative of fraud; the importance of a good system of internal controls; the profile of the typical fraud perpetrator; the fine line auditors walk when investigating a fraud; the need to develop an audit team with the appropriate level of expertise which may require members from a variety of disciplines (e.g., investigative, legal and forensic areas); and the difficulty of obtaining sufficient evidence to prosecute and convict perpetrators.

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