ABSTRACT

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.

chapter 1|13 pages

Introduction to Data Analysis

chapter 2|14 pages

Understanding Sampling

chapter 3|16 pages

Judgmental versus Statistical Sampling

chapter 4|10 pages

Probability Theory in Data Analysis

chapter 5|16 pages

Types of Evidence

chapter 6|11 pages

Population Analysis

chapter 8|19 pages

Conducting the Audit

chapter 10|23 pages

Use of Computer-Assisted Audit Techniques

chapter 11|11 pages

Analysis of Big Data

chapter 12|10 pages

Results Analysis and Validation

chapter 13|23 pages

Fraud Detection Using Data Analysis

chapter 14|5 pages

Root Cause Analysis

chapter 15|14 pages

Data Analysis and Continuous Monitoring

chapter 16|11 pages

Continuous Auditing

chapter 17|25 pages

Financial Analysis

chapter 18|11 pages

Excel and Data Analysis

chapter 19|11 pages

ACL and Data Analysis

chapter 20|9 pages

IDEA and Data Analysis

chapter 21|6 pages

SAS and Data Analysis

chapter 22|17 pages

Analysis Reporting

chapter 23|16 pages

Data Visualization and Presentation

chapter 24|9 pages

Conclusion