DATA ANALYSIS FOR INTERNAL AUDITORS
“Leveraging Data to Drive Audit Quality, Risk Insight, and Strategic Assurance”
Course Schedule
| Date | Venue | Fees (Face-to-Face) |
|---|---|---|
| 20 – 24 Jan 2025 | Dubai, UAE | USD 3495 per delegate |
| 09 – 13 Feb 2025 | Muscat, Oman | USD 3495 per delegate |
| 04 – 08 Aug 2025 | Dubai, UAE | USD 3495 per delegate |
Course Introduction
Modern internal audit functions must go beyond traditional sampling and manual reviews. Data analysis now plays a central role in delivering audit assurance that is more accurate, insightful, and risk-based. Auditors who can extract meaning from data can detect anomalies, improve coverage, and provide strategic value to boards and stakeholders.
This intensive five-day course gives internal auditors hands-on experience with data analysis techniques, tools, and frameworks specifically applied to the audit lifecycle. From risk assessments and fraud detection to audit testing and reporting, participants will gain practical skills in Excel and data logic that can be applied immediately.
Course Objectives
By the end of this course, participants will be able to:
- Apply data analysis throughout the audit process—from planning to reporting.
- Use structured logic to identify anomalies, trends, and control weaknesses.
- Design audit tests using population-level data rather than small samples.
- Improve audit evidence quality through analytical procedures.
- Use Excel tools to automate, visualize, and summarize audit findings.
- Support continuous auditing and real-time assurance through data-driven techniques.
Key Benefits of Attending
- Build confidence in applying analytics to audits, even without advanced coding skills.
- Learn how to test full data populations, not just samples.
- Detect hidden risk patterns using pivot tables, filters, and logic-based checks.
- Develop your role as a value-added risk advisor using data insights.
- Bridge the gap between audit judgment and objective analysis.
Intended Audience
This program is designed for:
- Internal auditors and audit managers
- Risk and compliance professionals
- Finance and control officers supporting audits
- New audit team members seeking analytic skills
- Operational auditors working on process risk reviews
Individual Benefits
Key competencies that will be developed include:
- Analytical thinking and risk interpretation
- Excel-based data analysis skills
- Control design validation through data
- Data visualization for reporting and dashboards
- Logical structuring of audit evidence and procedures
Organization Benefits
Upon completing the training course, participants will demonstrate:
- Enhanced audit testing quality and coverage
- Reduced audit effort through smart analytics
- Improved risk insights and fraud detection
- Better documentation for external reviews and regulators
- Value-added audit recommendations based on evidence
Instructional Methdology
The course follows a blended learning approach combining theory with practice:
- Live Demonstrations – Excel audit analysis tools
- Hands-On Activities – Data tests using financial and operational records
- Templates – Audit logs, red-flag indicators, and checklists
- Case Studies – Process-specific testing and detection
- Group Exercises – Risk scenarios and analytics walkthroughs
- Peer Exchange – Sharing tools, use cases, and challenges
Course Outline
Detailed 5-Day Course Outline
Training Hours: 7:30 AM – 3:30 PM
Daily Format: 3–4 Learning Modules | Coffee breaks: 09:30 & 11:15 | Lunch Buffet: 01:00 – 02:00
Day 1: Foundations of Audit Data Analysis
- Module 1: The Role of Data in Internal Auditing (07:30 – 09:30)
- What is data-driven auditing?
- Audit quality, coverage, and independence through analytics
- Tools overview: Excel, IDEA, ACL, Power BI
- Module 2: Audit Data Sources and Structure (09:45 – 11:15)
- Transaction logs, GL data, master data
- Data fields, formats, and constraints
- Cleaning, validating, and preparing audit data
- Module 3: Excel as an Audit Analytics Tool (11:30 – 01:00)
- Lookup, filter, match, and conditional logic
- Building audit flags and validation tests
- Error-proofing formulas
- Module 4: Practice – Importing and Cleaning Audit Data (02:00 – 03:30)
- Real dataset exercise with peer feedback
Day 2: Audit Testing and Red Flag Development
- Module 5: Transaction Testing with Full Populations (07:30 – 09:30)
- Duplicate detection, sequence gaps, and cutoff testing
- Exception identification logic
- Applying conditions to identify anomalies
- Module 6: Control Testing and Risk Triggers (09:45 – 11:15)
- Segregation of duties and system access testing
- Approval chain reviews and outlier detection
- Matching against thresholds or unauthorized actions
- Module 7: Fraud and Policy Violation Analytics (11:30 – 01:00)
- T&E claims, ghost vendors, duplicate invoices
- Conflict of interest indicators
- Linking data points to audit interviews
- Module 8: Exercise – Designing a Red Flag Audit Tool (02:00 – 03:30)
- Custom template creation and risk validation
Day 3: Process Analytics and Continuous Testing
- Module 9: Process-Based Audit Models (07:30 – 09:30)
- AP, AR, procurement, payroll audits
- Data flow and key controls
- Mapping processes to data checks
- Module 10: Automation of Audit Scripts in Excel (09:45 – 11:15)
- Macros, named ranges, dynamic filters
- Recording repeatable procedures
- Using buttons and form controls
- Module 11: Risk Dashboards and Visualization (11:30 – 01:00)
- Charts, pivot tables, slicers
- Visualization of risks and performance
- Dashboard storytelling for audit committee use
- Module 12: Simulation – Continuous Monitoring Model (02:00 – 03:30)
- Case: Monthly payroll review automation
Day 4: Documentation, Reporting, and Impact
- Module 13: Linking Data Tests to Audit Objectives (07:30 – 09:30)
- Audit planning and program alignment
- Sampling vs. full population design
- Test objectives, criteria, and result capture
- Module 14: Reporting Results with Impact (09:45 – 11:15)
- Tables, summaries, and visual risk flags
- Communicating uncertainty, assumptions, and scope
- Audit report data inserts and appendices
- Module 15: Quality Assurance for Audit Analytics (11:30 – 01:00)
- Reviewing analytics for error and bias
- Peer review and supervisory sign-off
- Archiving audit data and logic
- Module 16: Team Workshop – Report and Presentation (02:00 – 03:30)
- Teams present analysis, conclusions, and recommendations
Day 5: Strategic Integration and Future Skills
- Module 17: Integrating Analytics into Audit Strategy (07:30 – 09:30)
- Audit universe and risk heatmap support
- Thematic audits and data cycle reviews
- Cross-functional collaboration
- Module 18: Tools Beyond Excel – What Comes Next? (09:45 – 11:15)
- IDEA, Power BI, Python: when and why
- Creating a roadmap for your audit function
- Training, licenses, and culture shifts
- Module 19: Analytics in Agile and Continuous Audit (11:30 – 01:00)
- Ongoing testing and dashboards
- Integrating with control self-assessments
- Reporting to leadership and audit committee
- Module 20: Final Review, Q&A and Certification (02:00 – 03:30)
- Peer feedback, instructor coaching, and wrap-up
Certification
Participants who complete the program will receive a Certificate of Completion in Data Analysis for Internal Auditors, recognizing their ability to apply structured analytics for high-impact audit testing, fraud detection, and risk-based assurance.