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4 - AAU - Accounting and Financial Auditing
AAU 205 - Data Analysis for Internal Auditors
| Code | Start Date | Duration | Venue | |
|---|---|---|---|---|
| AAU 205 | 15 April 2024 | 5 Days | Istanbul | Registration Form Link |
| AAU 205 | 20 May 2024 | 5 Days | Istanbul | Registration Form Link |
| AAU 205 | 24 June 2024 | 5 Days | Istanbul | Registration Form Link |
| AAU 205 | 29 July 2024 | 5 Days | Istanbul | Registration Form Link |
| AAU 205 | 02 September 2024 | 5 Days | Istanbul | Registration Form Link |
| AAU 205 | 07 October 2024 | 5 Days | Istanbul | Registration Form Link |
| AAU 205 | 11 November 2024 | 5 Days | Istanbul | Registration Form Link |
| AAU 205 | 16 December 2024 | 5 Days | Istanbul | Registration Form Link |
Please contact us for fees
Course Description
Executing a cost-effective and value-added audit requires an understanding of population analysis. Without this knowledge, you run the risk of spreading your resources and your sampling over low risk subsets of the population. This could result in crucial data not being collected. In this course, you will learn when and how to use population analysis in the planning phase of the audit and how to identify subsets of the population that behave differently from a benchmark data set.
Course Objectives
- Summarize introductory terminology and methodology related to Data Analysis.
- Understanding the conditions and methodology of population sampling
- Determine the measure of hypothesis tests
- Evaluate the important data needed and how to gather it
- Practice some statistical methods
Who Should Attend?
- Junior Internal Auditors
- Internal Audit Specialist
- Auditors
- Managers
- Executives working in both the public and private sectors
Course Details/Schedule
Day 1
- Concepts of big data
- Transforming data analytics to business
- Internal Auditor's function through the use of data and analytics
- Use of Data through the Audit Lifecycle
- Identify how data analytics can transform all parts of the audit lifecycle, from planning, risk assessment, execution, reporting, and through to monitoring
Day 2
- Recognising the data analytics maturity continuum
- Collecting and enriching data can be used for analysis,
- Understanding the audit environment better
- Identifying risks during the planning
Day 3
- Different types of analytics
- Descriptive, predictive, and prescriptive analytics
- Analytical techniques to auditing a business process
- The use of advanced analytics, such as machine learning, within audit testing
Day 4
- How to build the strategy around a data-enabled
- Internal Auditor function, considering people, process and technology
- The Landscape of tools applicable to data auditing
Day 5
- Methods to create impact and the business case for data analytics
- Identify areas within your existing IA function that can be improved via data
