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DATA ANALYTICS IN INTERNAL AUDIT

From Sampling to Certainty: Future-Proof Your Internal Audit with Data Analytics

Home / DATA ANALYTICS IN INTERNAL AUDIT WORKSHOP

Classroom Sessions:

Date Venue Fee
14-15 Oct | 10-11 Nov 2025 The Protea Balalaika Hotel, OR Tambo, Johannesburg ZAR: 9990.00

Online Sessions:

Date Venue Fee
14-15 Oct | 10-11 Nov 2025 Online via TEAMS ZAR: 7990.00

Overview

Internal Audit is at a crossroads. Traditional, sample-based audit methodologies that once served organisations well are increasingly becoming inadequate in today’s fast-paced, data-driven environment. The explosion of financial, operational, and unstructured data, coupled with heightened expectations from Boards, Regulators and Audit Committees, means that Internal Audit must evolve to remain relevant. Auditors are now expected to provide more than compliance checks — they must deliver timely insights, detect risks proactively, and support the organisation’s strategic objectives. Data analytics is the enabler that transforms this expectation into reality.

In South Africa, the pressure is particularly acute. Regulatory frameworks such as the King IV Code on Corporate Governance, the Companies Act, the Public Finance Management Act (PFMA) and the Municipal Finance Management Act (MFMA) demand higher levels of assurance, accountability and transparency. Without the use of analytics, Internal Audit risks missing critical red flags such as fraud, irregular expenditure, and non-compliance with legislation. Moreover, continued reliance on outdated, manual and time-consuming techniques undermines audit credibility, slows down reporting, and leaves organisations exposed to risks that could have been detected earlier.

This workshop is therefore not just a learning event — it is a call to action. By embracing data analytics, Internal Auditors can unlock efficiency gains, reduce costs, test entire populations instead of small samples, and deliver insights that add tangible value to the business. The alternative is stark: audit functions that fail to adopt analytics will fall behind, struggle to meet legislative and stakeholder demands, and risk being seen as obsolete. This 2-day programme provides the tools, techniques and confidence auditors need to make the transition, future-proofing their function and securing their credibility in the 21st century.

KEY TAKEAWAYS

    • Understand the concept of data analytics and its role in modern internal auditing.
    • Recognise the limitations of traditional, sample-based audit approaches.
    • Apply data analytics across high-risk areas such as accounts payable, payroll, revenue, inventory, and financial controls.
    • Understand South African governance and legislative requirements driving adoption of analytics.
    • Detect fraud and corruption risks earlier through data mining techniques.
    • Move from historical to predictive insights using analytics.
    • Gain confidence in applying audit tools such as IDEA, ACL, SQL and Excel.
    • Strengthen communication of audit results through impactful reporting and data visualisation.
    • Position Internal Audit as a strategic partner to management and the Board.
    • Future-proof their audit function against obsolescence in the digital age

WHO SHOULD ATTEND?

  • Internal Auditors at all levels (junior, senior, and audit managers) seeking to modernise their methodologies.
  • Chief Audit Executives (CAEs) and Heads of Internal Audit who need to align their functions with King IV and Board expectations.
  • Risk and Compliance Officers tasked with monitoring fraud, irregular expenditure, and governance breaches.
  • Finance Managers, Accountants, and Controllers responsible for ensuring accuracy, compliance, and efficiency in financial processes.
  • IT Auditors and Data Specialists who support internal audit in data extraction, mining, and testing.
  • Forensic and Fraud Investigators looking to enhance detection using data-driven techniques.
  • Public Sector Auditors and Oversight Professionals working under PFMA and MFMA requirements.
  • Board and Audit Committee Members who want to understand how analytics strengthens audit assurance and governance outcomes.
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By the end of this workshop, delegates will be able to:

  • Understand the concept of data analytics and its role in modern internal auditing.
  • Recognise the limitations of traditional, sample-based audit approaches.
  • Apply data analytics across high-risk areas such as accounts payable, payroll, revenue, inventory, and financial controls.
  • Understand South African governance and legislative requirements driving adoption of analytics.
  • Detect fraud and corruption risks earlier through data mining techniques.
  • Move from historical to predictive insights using analytics.
  • Gain confidence in applying audit tools such as IDEA, ACL, SQL and Excel.
  • Strengthen communication of audit results through impactful reporting and data visualisation.
  • Position Internal Audit as a strategic partner to management and the Board.
  • Future-proof their audit function against obsolescence in the digital age

PROGRAM TIMINGS

  • Registration will begin at 08.30 on Day One.
  • The program will commence at 09.00 each day and continue until 16.30.
  • There will be two refreshment breaks and lunch at appropriate intervals.

DAY 1: INTRODUCTION TO DATA ANALYSIS IN THE 4IR CONTEXT

This session will introduce the delegate to the principles of information flow within organizations as well as data analytic methodologies and terminology. The focus will be on developing an understanding of where critical data exists for analysis, the obtaining of access and the selection of the appropriate analytical techniques. We will examine the differences between a given set of data in the standard benchmark in terms of central tendency, variation and shape of curve. In addition we will examine the fundamental principles of Baysian probability theory. In general, this is a methodology used to trying to clarify the relationship between theory and evidence. It attempts to demonstrate how the probability that the theory is true is affected by a new piece of evidence. This can be critical to auditors in drawing conclusions about large populations based upon small samples drawn.

  • The rise in the Fourth Industrial Revolution (4IR)
  • Understanding Data Analytics
  • The Data Analytics Process
  • Data Analytic Tools
  • Resource Requirements and Challenges
  • Internal Audit use
  • Approach to Implementation

DATA AND ITS PROPERTIES

This session looks at specific characteristics of data that make it useful for decision making. It looks at:

  • Characteristics that Make Data Useful for Decision Making
  • Structured vs. Unstructured Data
  • Data Types
  • Data Dictionaries
  • Wide Data vs. Long Data
  • Merging Data
  • Data Automation
  • Visualizing Data Relationships

AUDITING AND AN ANALYTICS MINDSET

In this session, you will learn to recognize the importance of making room for empirical enquiry in decision making. You will explore characteristics of an analytical mindset in business and accounting contexts, and link those to your core courses. You will then evaluate a framework for making data-driven decisions using big data.

  • Making Room for Empirical Enquiry
  • Applying Analytical Thinking
  • Inductive and Deductive Reasoning 
  • Advanced Analytics and the Art of Persuasion

UNDERSTANDING SAMPLING

This session will cover the fundamental assumptions underlying the use of sampling techniques, the nature of populations and the use of variables. Distribution frequencies and central tendency measurement will be covered as well as the impact on analysis of distribution characteristics. It will also examine the differences between judgmental and statistical sampling, the applicability of both in audit practice, and the dangers inherent in confusing the two. 

The differences in selection methods will be covered as well as their impact on the analysis and interpretation possible within the sampling methods.

  • Judgmental vs Statistical Sampling
  • Probability theory in Data Analysis
  • Types of Evidence
  • Population Analysis
  • Correlations and Regressions

APPLYING DIFFERING ANALYTICAL TECHNIQUES

This session will examine typical CAATs in common use in the selection of the appropriate technique based upon the type of evidence and the audit objective. Included will be the dangers to the auditor inherent in pre-judgment of expected results and the subsequent distortion of the analysis based upon these pre-conceptions. It will also examine the audit methodologies for the analysis of Big data. Big data is a term given to large datasets containing a variety of data types. Big data analysis allows the auditor to seek for hidden patterns and identify concealed correlations, market trends and other data inter-relationships which can indicate areas for improved operational efficiencies within business processes.

Topics covered in this session include:

  • Big Data Structures
  • OLAP
  • Statistical Analysis and Big Data
  • Substantive Analytical Procedures
  • Validation
  • Questionnaire Analysis and Likert Scales
  • Statistical Reliability Analysis

DAY 2: FRAUD DETECTION USING DATA ANALYSIS

This session will examine the techniques available to the auditor in order to identify the red flags and indicators that fraud may be occurring or may have occurred in the past as well as the obtaining of forensically acceptable data analytical evidence.

Topics covered in this session include:

  • Red Flags and Indicators
  • Nature of Computer Fraud
  • Seeking Fraud Evidence
  • Planning the Fraud Analysis
  • Common mistakes in Forensic Analysis
  • Conducting Root Cause Analysis

DATA AND FINANCIAL ANALYSIS

This session will examine the various types of evidence available to the auditor in financial systems in order to evaluate both the adequacy and effectiveness of the system of internal controls. This will include the identification of population types and the division into sub-populations for analytic purposes. Differing collection types and evidence sources will also be identified.

Topics covered in this session include:

  • Monitoring Tools
  • Implementing continuous monitoring
  • Potential benefits
  • Implementing continuous auditing
  • Structuring the implementation
  • Perceived downside
  • Obtaining and maintaining support
  • Analyzing Financial Data
  • Use of ratios
  • Horizontal and vertical analysis
  • Subsidiary ledgers
  • Financial database analysis

DAY 3: CHOOSING YOUR DATA ANALYTICAL SOFTWARE

This session will cover the assessment of IT software in order to determine the appropriateness of use in evidentiary analysis as well as the techniques the auditor may use in order to obtain, extract and, if necessary, transform such data to facilitate analysis.

Topics covered in this session include:

  • Management Use of Excel
  • Use of Excel in financial analysis
  • Data Acquisition
  • Excel Database Functions
  • Excel Financial Functions
  • Ratio Analysis
  • Du Pont Analysis
  • Z-Score Analysis
  • ACL Add-in
  • ACL and Data Analysis
  • Seeking Anomalous Data
  • ACL Analysis Options
  • Using ACL Scripts
  • IDEA and Data Analysis
  • SAS and Data Analysis
  • Other Popular Audit Software

REPORTING AND USING THE ANALYSIS

With Sophisticated analysis, the audit department is frequently judged on the quality of its primary output, the Audit Report and this can affect the perception of the professionalism of the whole department. In many cases the effectiveness of the analysis can be affected by the non-acceptability of the Audit Report.

Topics covered in this session include:

  • Creating an effective Audit Report
  • Writing for Impact
  • Conveying the message
  • Using Clear Writing Techniques
  • Incorporating the Analytics
  • Communication Modes
  • Communication Provisions
  • Visualization Techniques
  • Selecting the Form
  • Big Data Visualization
  • Advanced Visualization