Internal Audit M16: Data Analytics – PowerPoint PPTX Template

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BENEFITS OF THIS DOWNLOADABLE POWERPOINT DOCUMENT

1. Provides comprehensive analytics opportunity assessment frameworks with data availability checklists, feasibility scoring models, and business case templates enabling systematic identification and justification of high-value analytics initiatives.
2. Delivers ready-to-use analytical procedures including duplicate detection, completeness testing, gap analysis, aging analysis, and three-way matching with step-by-step implementation guidance and SQL query examples for immediate application.
3. Equips audit functions with capability-building frameworks including maturity assessment models, tool selection criteria, training program designs, and Analytics Center of Excellence implementation roadmaps for sustainable analytics development.

AUDIT MANAGEMENT PPT TEMPLATE DESCRIPTION

Data Analytics in Audit PPT: Learn practical audit analytics frameworks, data prep templates, anomaly detection & investigation tools. Download the IA Professional Series. Internal Audit M16: Data Analytics is a 51-slide PPT PowerPoint presentation template (PPTX) available for immediate download upon purchase.

The Internal Audit Professional Series is a comprehensive 18-module training program designed to transform internal audit professionals from foundational competence to strategic excellence. Developed and published by Business Excellence, a leading advisory and consultancy firm specializing in internal audit, risk management, corporate governance, and business strategy, this series delivers practical, actionable knowledge aligned with the Global Internal Audit Standards (GIAS 2024).
Module 16: Data Analytics in Audit provides a practical implementation guide for leveraging data analytics effectively in audit work. This module equips professionals with analytical procedures, data preparation techniques, and capability-building approaches regardless of technical background.
This module covers 7 comprehensive sections:

Analytics Opportunity Assessment – Identifying where analytics can help by evaluating data availability across existence, storage, format, access, and quality considerations. Covers how to assess analytics feasibility using weighted scoring, identify quick wins through value-effort prioritization, and build a sound analytics business case.
Data Acquisition and Preparation – Getting data ready by specifying the elements, time periods, formats, and extraction criteria a data request should define. Walks through data validation for record counts, control totals, completeness, and field checks; data cleansing for missing values, inconsistent formats, and duplicates; and data integrity verification.
Common Audit Analytics Procedures – Core tests explained step by step, including transaction completeness testing through sequence analysis, cross-system reconciliation, and period-over-period comparison; duplicate detection using exact, fuzzy, and near-duplicate matching; gap and sequence analysis for checks, invoices, and transactions; aging analysis; and three-way matching.
Analytical Technique Application – Advanced methods including trend analysis for identifying patterns and anomalies over time, ratio analysis across financial, operational, and compliance measures with benchmark comparisons, and stratification for risk-based population segmentation.
Anomaly Investigation Process – Investigating findings by prioritizing exceptions on magnitude, frequency, and risk exposure. Covers structured root-cause analysis, filtering false positives to keep effort focused on genuine exceptions, documenting investigations, and clear escalation criteria for confirmed anomalies.
Results Interpretation and Reporting – Turning analytics output into defensible audit evidence: validating results before reporting, linking findings back to control objectives and risks, visualizing patterns for non-technical stakeholders, and structuring analytics findings within the audit report so conclusions are actionable and stand up to challenge.
Building Analytics Capability – Embedding analytics into the audit function for the long term, including the skills and roles required, selecting fit-for-purpose tools, establishing repeatable analytics routines, agreeing data governance and access with the business, and a maturity roadmap toward continuous auditing.

Each section moves from concept to application, with worked examples and practitioner guidance you can apply directly in your audit environment.
Series Overview: This is Module 16 of the 18-part Internal Audit Professional Series by Business Excellence, fully aligned with GIAS 2024. The series progresses through four levels – Foundation (Modules 1–5), Core Processes (Modules 6–10), Specialized Practice (Modules 11–14), and Advanced Application (Modules 15–18) – and Module 16 sits within the Advanced Application level alongside Quality Assurance, ESG Auditing, and Leading Internal Audit.
About the Author: Amer Morgan, CIA, CRMA, CFE, is the founder of Business Excellence and a Senior Consultant with over three decades of audit leadership across the GCC, MENA, Europe, and the USA.

Source: Best Practices in Audit Management, Data Analytics PowerPoint Slides: Internal Audit M16: Data Analytics PowerPoint (PPTX) Presentation Slide Deck, Amer Morgan