Auditing Evolution: A Data Analytics Approach
Edition: 3
Copyright: 2026
Pages: 410
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$105.00 USD
Auditing Evolution: A Data Analytics Approach is designed to equip accounting students with the foundational and advanced knowledge and techniques for modern auditing practices. The textbook offers a comprehensive, flexible structure that accommodates the evolving demands of the accounting profession, including the integration of data analytics and preparation for the CPA Evolution exam.
Key Features and Structure:
The textbook is divided into two main parts, catering to different student needs and course structures:
- Modules 1–14: Core auditing concepts are generally applicable to all accounting students. These modules cover fundamental auditing principles with data analytics applications, including the audit environment, professional conduct, legal liabilities, risk assessment, internal controls, audit evidence, fraud detection, and reporting.
- Modules 15–22: Advanced modules focusing on practical approaches in auditing. These modules are specifically designed for students pursuing the AICPA auditing core path, aligning with the CPA Evolution model curriculum. The modules offer hands-on experience with modern audit tools and techniques.
This modular design provides flexibility for educational institutions:
- Single auditing course: Use Modules 1–14 for comprehensive coverage of fundamental auditing concepts for students not pursuing the audit core path of the AICPA exam.
- Single or Two-course sequence: Use modules 1-22 for a single course or Modules 1–14 for the first course and Modules 15–22 for the advanced course, offering students an in-depth, practical learning experience.
Emphasis on Data Analytics:
The textbook embraces the increasing role of data analytics in auditing by incorporating real-world problems and techniques. Students gain practical exposure to:
- Data analytics platforms: Alteryx, Tableau, and IDEA.
- Emerging technologies: Process Mining, Robotic Process Automation, Machine Learning, Audit AI, and Blue J Legal.
- Analytical procedures and fraud detection: Benford's Law, Regression Analysis, and advanced sampling methods.
Through case studies, students develop proficiency in using these tools to enhance audit efficiency and effectiveness.
CPA Evolution and Certification Readiness:
The textbook reflects the changes introduced by the CPA Evolution initiative. The structure of the textbook enables universities to tailor their curriculum according to their course offerings, ensuring that students are well-prepared for certification exams.
Module 1
Module 1.1 Audit Environment
Module 1.2 Code of Professional Conducts
Module 1.3 Auditor’s Legal Liabilities
Module 2
Module 2.1 Engagement Planning and Considerations
Module 2.2 Engagement Planning and Considerations
Module 3
Module 3.1 Understanding an Entity and its Environment
Module 3.2 Understanding an Entity and its Environment (continued)
Module 4
Module 4 Information Technology and the Audit
Module 5
Module 5.1 Fraud and Noncompliance Auditing
Module 5.2 Analytical Procedures
Module 6
Module 6 Assessing Risk of Material Misstatement
Module 7
Module 7 Materiality
Module 8
Module 8 Audit Evidence
Module 9
Module 9 Substantive Audit Procedures: Sampling
Module 10
Module 10.1 Special Consideration—Part 1
Module 10.2 Special Consideration—Part 2
Module 11
Module 11 Audit Conclusion
Module 12
Module 12.1 Standard Audit Report and Its Modifications
Module 12.2 Audit of Internal Control, Supplementary Information, and Other Information
Module 13
Module 13 Other Types of Reports
Module 14
Module 14 Audit of Governmental Entities
Dr. Deniz Appelbaum (appelbaumd@montclair.edu), Chair and Associate Professor of the Department of Accounting and Finance at the Feliciano School of Business of Montclair State University in New Jersey enriches her academic pursuits with a practical view, after twenty years of experience in operations, credit, and business development in the corporate world. Dr. Appelbaum has published over 25 manuscripts in Accounting Horizons, Journal of Emerging Technologies in Accounting, Auditing: Journal of Practice and Theory, Journal of information Systems, and in other academic and practitioner journals, based on her research regarding analytics, AI and machine learning, big data, blockchain, municipal reporting, and fraud detection. Dr. Appelbaum has conducted research with Proctor & Gamble, Dunn & Bradstreet, AICPA, GASB, the Volcker Alliance, the Asian Development Bank, and KPMG. Dr. Appelbaum emphasizes the use of data analytics and appropriate software tools in the classroom, to prepare accounting and auditing students for the technically advanced modern business environment. The accounting and auditing professions are currently undergoing huge disruptions due to technical innovations, and Dr. Appelbaum is devoted to preparing her students and the profession for these changes.
Dr. Hossein Nouri is an Emeritus Professor of Accounting at The College of New Jersey (TCNJ). He received his PhD in Accounting from Temple University. He was the Chair of the Accounting Department at The College of New Jersey between 2004 and 2008. During his 30 years at TCNJ, he taught Auditing Theory and Practice as his primary teaching course. In addition, he has taught various courses in accounting, including Financial Accounting & Reporting, Managerial Accounting, Fundamentals of Financial Accounting, internal auditing, and Selected Topics in Accounting. Before joining the academic work, Dr. Nouri was a manager for national and international auditing firms in Iran before joining academics in the USA.
Dr. Nouri’s research interests are in behavioral accounting and meta-analysis. He has published in major accounting and management journals, including the Journal of Management, Accounting, Organizations, and Society, Behavioral Research in Accounting, Journal of Accounting Literature, Journal of Forensic and Investigative Accounting, The British Accounting Review, Critical Perspectives in Accounting, Managerial Auditing Journal, Global Perspectives in Accounting Education, among others. His work has also been presented and published in numerous regional, national, and international conferences.
Dr. Ting Sun is an Associate Professor at The College of New Jersey. She holds a Ph.D. in Accounting Information Systems from Rutgers University and a Ph.D. in Accounting from Southwestern University of Finance and Economics. Her primary research areas include business data analytics and Artificial Intelligence applications in accounting and auditing. Her research has been published in prominent academic journals, such as Review of Accounting Studies, Accounting Horizons, Journal of Information Systems, Journal of Emerging Technologies in Accounting, Intelligent Systems in Accounting, Finance & Management, and Managerial Auditing Journal.
Dr. Nuriddin Tojiboyev is an Assistant Professor at The College of New Jersey. He received his Master of Accountancy from West Virginia University and his Ph.D. in Management, with a concentration in Accounting Information Systems, from Rutgers University. He brings several years of professional experience in cost accounting, indirect tax accounting, and internal audit, as well as academic experience teaching a range of accounting, auditing, and audit analytics courses.
Dr. Tojiboyev has been a Certified Public Accountant (CPA, Montana) since 2015. He is a member of the American Accounting Association’s Strategic and Emerging Technologies Section, for which he has served as program chair for midyear and annual meetings. He has also contributed to the profession through training sessions on audit data analytics for PCAOB investigators and through research collaborations on Audit Data Standards with the AICPA. His research focuses on developing data analytics, machine learning, and AI-based models to improve the effectiveness and efficiency of auditing. He also serves as an ad hoc reviewer for Accounting Horizons, the International Journal of Accounting Information Systems, and the Journal of Emerging Technologies in Accounting.