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.

Why you Should Attend

  • 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.

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