Course Description
Today’s Internal Audit environment demands audit departments to “do more, with less”. A formal data analytics program can go a long way in helping an audit function become more efficient, easily scalable and significantly reduce auditing errors all while providing greater audit and fraud risk coverage. Data analytics programs can provide long term continuous auditing or monitoring around legal and compliance issues as well as the ability to do ad hoc audit testing, business reviews and fraud investigations. Data analytics is the cornerstone for fraud detection programs in many organizations, providing audit and fraud teams the ability to immediately and easily identify potential fraud without having to manually sample large quantities in order to detect fraud and fraud patterns.
Data analytics programs can provide the opportunity for an audit function to add value to their organization, enhance assurance for audits, fraud detection and Sarbanes-Oxley testing. However, implementing an effective program will pose challenges for most audit departments. This course will help auditors understand what data analytics can do, what tools are available for data analytics, what is really involved starting a data analytics program, what areas should be targeted and most importantly, where to start.
Participants will learn interactively through a combination of lecture, live demonstrations, and exercises.
Learning Objectives
- Understand Data Analytics Concepts
- Distinguish Between Continuous Auditing and Continuous Monitoring
- Identify How Data Analytics Adds Value and Efficiency to Your Audits
- Learn How to Implement Data Analytics Program
- Identify the Various Data Analytic Tools and Their Uses
- Learn How to Present Your Findings in the Compelling Manner
Course Outline
Overview of Data Analytics
- Defining Data Analytics
- Big Data
- Continuous Auditing vs Monitoring
Data Analytics for Internal Audit
- The Need for Analytics in Internal Audit
- What Is the Value Proposition of Data Analytics
- Where Can You Add Value to Your Audits
- Getting Creative
- Data Analytics as a Fraud Discovery Tool
Implementing Analytics
- Implementation Life Cycle
Step-by-Step – Implementing Data Analytics
- Understanding the Data
- Documentation Techniques
- Vetting Your Data – Avoiding GIGO
- Importing Data
- Using Databases
- Data Analytic Tools
- Choosing the Right Tool
- Vendor Hosting – The Good, Bad and Ugly
- Techniques for Discovery
- Quantitative vs Qualitative Analysis
- Benford’s Law
- Regression Analysis
- Reasonableness Testing
- Fuzzy Logic
Presenting Findings
- Visualization
- Using “Eye-Candy” to Report Your Results
- Avoiding Too Much Detail
Best Practices
Additional Information
Who Should Attend
Internal auditor staff and management
Learning Level
Intermediate
Delivery
Group Live or Group Internet-Based
Field
Auditing
Recommended Prerequisites
Auditors with at least 2 years’ experience in order to draw upon their professional audit experience
Session Duration
On Site: 2 days
CPE Credits: 16