Data Analytics for Internal Auditors

There are many webinars and training courses on Data Analytics for Internal Auditors, but no handbook written from the practitioner’s viewpoint covering not only the need and the theory, but a practical hands-on approach to conducting Data Analytics. The spread of IT systems makes it necessary that auditors as well as management have the ability to examine high volumes of data and transactions to determine patterns and trends. The increasing need to continuously monitor and audit IT systems has created an imperative for the effective use of appropriate data mining tools. This book takes an auditor from a zero base to an ability to professionally analyze corporate data seeking anomalies.

Table of Contents

Chapter 1: Introduction to Data Analysis
Chapter 2: Understanding Sampling
Chapter 3: Judgmental versus Statistical Sampling
Chapter 4: Probability Theory in Data Analysis
Chapter 5: Types of Evidence
Chapter 6: Population Analysis
Chapter 7: Correlations, Regressions, and Other Analyses
Chapter 8: Conducting the Audit
Chapter 9: Obtaining Information from IT Systems for Analysis
Chapter 10: Use of Computer-Assisted Audit Techniques
Chapter 11: Analysis of Big Data
Chapter 12: Results Analysis and Validation
Chapter 13: Fraud Detection Using Data Analysis
Chapter 14: Root Cause Analysis
Chapter 15: Data Analysis and Continuous Monitoring
Chapter 16: Continuous Auditing
Chapter 17: Financial Analysis
Chapter 18: Excel and Data Analysis
Chapter 19: ACL and Data Analysis
Chapter 20: IDEA and Data Analysis
Chapter 21: SAS and Data Analysis
Chapter 22: Analysis Reporting
Chapter 23: Data Visualization and Presentation
Chapter 24: Conclusion