Overview
Audit analytics utilizes advanced data analysis techniques to improve audit effectiveness and efficiency. Through statistical analysis, data mining, and other methods, auditors examine large volumes of financial and operational data to extract insights and identify patterns, aiding in risk assessment and decision-making. Its significance has grown with the complexity of financial transactions and business environments. In essence, audit analytics is a powerful tool enhancing audit accuracy, efficiency, risk management, fraud detection, and decision-making in modern business. As technology progresses, its role becomes more vital in the audit profession.
Why You Should Attend:
Enhanced Risk Assessment: Audit analytics enables a more thorough risk assessment by analyzing large datasets to uncover irregularities and potential areas of risk, leading to a targeted audit approach.
Increased Efficiency and Effectiveness: Automation of audit processes through analytics reduces reliance on manual procedures, allowing auditors to analyze entire datasets accurately and efficiently, saving time and resources.
Timely Detection of Anomalies and Fraud: Audit analytics facilitates early detection of anomalies and signs of fraudulent activities through real-time monitoring and analysis, minimizing the impact on financial statements.
Insightful Decision-Making: By generating valuable insights into business operations and financial performance, audit analytics empowers auditors to provide meaningful recommendations for informed decision-making based on data-driven insights.
Adaptation to Technological Advances: Audit analytics helps auditors keep pace with technological advances by examining electronic records and digital transactions, aligning audit practices with evolving business technology.
Regulatory Compliance: In a dynamic regulatory environment, audit analytics supports compliance with industry regulations and accounting standards, demonstrating organizations' commitment to transparency and accountability.
Who Should Attend:
1. External Auditors and Internal Auditors
2. Financial Analysts and Accountants
3. Risk and Governance Professionals
4. Compliance Professionals
5. IT and Data Professionals
6. IT Audit Professionals
7. Finance Professionals
8. Internal Control Professionals
9. Assurance Professionals
Training Objectives:
Stay ahead in the ever-evolving field of auditing by joining our hands-on Audit Analytics Training Course. Gain practical experience with real-life examples and case studies, allowing you to seamlessly integrate advanced data analysis techniques into your daily audit procedures. Learn to identify potential risks and anomalies more effectively, enhancing your risk assessment capabilities for a more strategic approach to auditing.
Improve efficiency through automation, analyze entire datasets, and reduce reliance on manual processes. Engage in interactive sessions, collaborate with professionals, and enhance your understanding of audit analytics through discussions and hands-on exercises. Future-proof your auditing expertise by acquiring skills aligned with the latest technological advancements.
Learning objective:
Understand and apply right visualisation techniques
Import and transform Data
Deal with Multiple Data Sources
Analyse data with PowerBI
Apply PowerBI in real life scenarios
Training Outline Modules:
Day 1
Basics of data visualization
• Introduction – the what, who and why?
• How to make a good data visualization
Basics of data visualization
• Choosing the right visualization
Introduction to Power BI
• Overview
• Connecting Data
• Working with Power Query Editor
Case Study 1: Importing and understanding Sales Data
• Data import with Power BI
• Data transformation with Power BI
• Statistics with Power BI
Case Study 2: Visualizing Data with Power BI Report:
• Bar Chart
• Hierarchy with Drill Controls
• Matrix with Conditional Formatting
Case Study 3: Analyzing Data with Power BI:
• Line chart (including dual axis)
• Scatter chart
• Use of filters
• Use of Calculated Columns vs Calculated Measures
• Pie and Donut Chart
• Slicer, card and text box
Day 2
Case Study 4: Intermediate use of Power Query Editor using
Property data
• Dealing with multiple data sources
• Data cleansing
• Data transformation
• Data appending
Case Study 5: Data Modelling with Power BI
• Data Cardinality
• Creating relationships
• Filter Directions
Case Study 6: Visualizing Valuation Change with Map
• Map: Country vs City Hierarchy
• Slicers
• Drill through
Case Study 7: Visualizing single % change vs Portfolio Average
• Calculated Columns vs Calculated Measures
• Calculate Function
• All Function
Case Study 8: Sensitivity Analysis on Forex Changes
• Parameter – What-Ifs
• SUMX function
• Switch Function
Other Power BI Features
• Bookmarks
• Custom Visuals
• Natural Language Query
Trainer's Profile:
Chong Yu brings over 16 years of diverse experience in financial audit and data analytics across various industries, including stock exchange, investment funds, banking, retail, manufacturing, and more. He currently shares his wealth of knowledge as a lecturer for the accounting analytics elective at Nanyang Technological University (NTU), and previously served as an Adjunct Lecturer at Singapore Management University (SMU), teaching Audit Analytics. Chong Yu is a seasoned trainer on data analytics, collaborating with professional bodies like the Institute of Singapore Chartered Accountants and Deloitte Learning Solutions. He co-authored a chapter on "Data Analytics in Audit" in a publication by CPA Australia and SMU School of Accountancy. As a former Director at Deloitte, he led a regional Southeast Asia data analytics team, delivering innovative solutions to audit and non-audit clients. Chong Yu holds a First Class Honours degree in Accounting from the University of Hertfordshire, UK, and is a Chartered Accountant of Singapore, an ASEAN Chartered Professional Accountant, and a Fellow Member of the Association of Chartered Certified Accountants (FCCA).
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