Introduction:

In today's increasingly digital and data-driven world, the role of auditors has evolved significantly. Traditional audit techniques are no longer sufficient to handle the complexity and volume of data generated by modern organizations. The Data Analytics for Auditors program, developed by Global Horizon Training Center, is designed to empower auditors with the tools, knowledge, and techniques needed to effectively audit IT systems, databases, and digitalized environments, including those powered by Artificial Intelligence (AI), Internet of Things (IoT), and emerging innovations in digitalization. This hands-on program bridges the gap between traditional audit methodologies and modern data analytics, ensuring participants are well-equipped to conduct insightful, risk-based, and technology-driven audits.

Objectives:

By the end of this program, participants will be able to:

• Understand the fundamentals and importance of data analytics in auditing.

• Apply data analysis techniques to extract, analyze, and visualize audit-relevant information.

• Conduct audits of databases, digital systems, and IT environments using analytical tools.

• Evaluate risks and controls in systems involving AI, IoT, and other digital innovations.

• Leverage modern analytics platforms and tools to enhance audit quality and efficiency.

Organizational Impact:

Implementing data analytics in auditing empowers organizations to:

• Enhance risk management and fraud detection capabilities.

• Improve audit coverage and effectiveness across digital systems.

• Gain real-time insights from operational and financial data.

• Foster a culture of data-driven decision-making.

• Stay ahead of regulatory and compliance standards through innovative audit techniques.

Target Audience:

This program is ideal for:

• Internal and external auditors

• IT auditors and compliance professionals

• Risk management and governance officers

• Audit team leaders and managers

• Professionals involved in digital transformation and data governance

Outlines:

Day 1: Foundations of Data Analytics in Auditing

• Evolution of auditing in digital environments

• Role of data analytics in risk-based auditing

• Types of audit analytics (descriptive, diagnostic, predictive)

• Understanding audit data sources (ERP, financial systems, operational data)

• Overview of analytics tools used in audit:

  • Excel (Power Query, Pivot)

  • ACL / IDEA

  • Power BI (basic dashboards)

• Data governance, privacy, and ethical considerations

Day 2: Data Extraction & Database Auditing

• Basics of database structures relevant to auditors

• Introduction to SQL concepts for auditors

• Extracting and validating data for audit purposes

• Common data integrity issues and red flags

• Segregation of duties (SoD) analysis using data

• Case example: Auditing financial transactions in ERP systems

Day 3: IT Systems, Automation & Emerging Technologies

• Overview of IT audit principles

• Key IT control areas in digital systems

• Introduction to AI, automation, and RPA in organizations

• Risks related to automated decision systems

• Basic approach to auditing AI-supported processes

• Cybersecurity risks relevant to auditors

Day 4: Fraud Detection & Advanced Analytics Techniques

• Data sampling techniques using analytics

• Anomaly detection and trend analysis

• Duplicate payments, unusual transactions, journal entry testing

• Benford’s Law in auditing

• Basic risk scoring models

• Using dashboards for audit reporting

Day 5: Integrating Analytics into the Audit Process

• Embedding analytics into audit planning

• Using data analytics in fieldwork and reporting

• Continuous monitoring vs traditional audit cycles

• Building a simple audit analytics roadmap

• Emerging technologies impacting audit (Cloud, AI, Blockchain – overview only)

• Final case discussion & wrap-up