Khushboo and her method of delivery was easy to receive. Very valuable insights from both speakers.
Provide Deeper Insights, High Quality Audits
With rising stakeholder expectations, stricter regulations and an increasingly complex business landscape, internal auditors are under pressure to generate new valuable insights and robust audits using data analytics. The challenge for internal audit is to rewrite the rulebook on traditional auditing techniques and shift towards insights-driven auditing.
Limited knowledge of data analytics tools available?
Lacking the skills to apply data analytics at different stages of the audit lifecycle?
Unsure of how other organisations are developing their audit analytics capabilities?
Acquire a Step-by-Step Approach to use Data Analytics to Perform Audits
Join this practical 2-day workshop to acquire critical skillsets and tools to effectively leverage data analytics in the audit lifecycle. Learn how to use data analytics to enrich the risk assessment process, support planning and scoping decisions. Overcome common challenges in data extraction and discover how to incorporate data analytics in fieldwork including designing data analytical tests. Examine how common analytics tools, advanced analytics and emerging technologies are used for audit. Find out how to create impact in your audit reports with analytics and visualisation.
- Real-life case studies from finance, hospitality, government and more
- Live demonstration of data analytics tools
- Lab sessions to experience different tools and techniques
- Group activities for peer learning
Practical Hands-on Exercises
- Data cleaning
- Validating data quality
- Analysing large sets of data
- Automating procedures
- Detecting fraud and outliers
- Testing internal controls
- Performing visual analytics
- Building charts
Adopt Free and Paid Tools
- Power BI
- Power Pivot
- Power Query
Benefits of Attending
- Examine the data analytics maturity continuum within the audit lifecycle
- Grasp how to efficiently select areas in your audit lifecycle to apply analytics
- Bridge the gap between data in ERP reports and data extracted by the I.T team
- Find out the key phases in using data analytics as part of fieldwork
- Identify the different technology components that make up an infrastructure layer
- Weigh the pros and cons of tools including ACL, Qlikview, Qliksense, Power BI, Alteryx, SQL
- Discover how advanced analytics such as clustering is employed in internal audit
- Acquire analytical and statistical techniques to identify anomalies and fraud
- Uncover how to use visualisation to enhance the progress and tracking of your audit plan
- Adopt the optimum people model when embedding analytics in your IA function
- Asses how to derive insights from a dashboard that satisfies audience needs
- Practice using Excel, Power Pivot, Power Query and data visualisation tools
Ren Hao has more than 8 years of experience in implementing data and analytics initiatives across both external and internal audit, where the focus area is to utilise effective audit techniques to drive audit efficiency.
He has worked across London, Singapore and Kuala Lumpur, where he has observed differing data and analytics maturity levels across organisations. This has enabled him to experience multiple first-time initiatives in using data techniques for the audit, ranging from clients in telecommunications, transport and utilities.
Ren Hao is an experienced trainer, his highest achievement has been to be selected as one of the Top 15 Tutor in PwC UK nationally in 2017.
Khushboo Khaitan brings over 6 years of work experience in the data and analytics space, covering a wide range of projects related to data, including analytics for audit, data migration, data quality and integrity reviews, analytics on supply chain, business processes analytics etc.
Khushboo’s industry experience is wide-ranging, spanning financial services, technology, government organizations, transport/logistics etc. Through her exposure to all these industries, she has seen first-hand, the similarities and differences in different industries and organisations. This has enabled her to advice clients on not only their own environment, but the external factors affecting them as well.
Past Delegate Testimonials
Comprehensive and tailored to Internal Audit
Very informative and productive
Great delivery on course information
Who Should Attend
Senior level executives responsible for Internal Audit, Finance, Risk Management, Fraud Management
Registration: 8.30am • Workshop: 9.00am – 5.00pm
Morning, afternoon refreshments & lunch will be served at appropriate intervals.
There are 2 components to this workshop:
- Understanding objectives and theory, which will be enriched with case studies from financial services, hospitality and government industries, demonstration of real-life tools and group hands-on exercises
- Lab sessions where delegates will get hands-on experience in different tools and techniques
Session 1: How Data is Transforming Internal Audit (IA)
- The driver and role of data analytics in recent years and megatrends
- Examining the data analytics maturity continuum
- How data analytics can transform all parts of the audit lifecycle
Session 2: Planning and Risk Assessment
- How data analytics can be used to enrichen the risk assessment process, support planning and scoping decisions
- How to effectively and efficiently select areas of your audit lifecycle to apply analytics
Session 3: Data Extraction and Common Pitfalls
- How to bridge the gap between data seen in ERP reports and the data I.T teams extract from the database
- How to efficiently extract data especially sensitive data sets
- Common difficulties faced in data extraction and how to overcome them
Session 4: Data Analytics in Fieldwork
- Key phases in using data analytics as part of fieldwork
- Hands-on exercise: Designing data analytical tests
- Data analytics tests that can support fraud detection
Session 5: Tools
- Common tools (e.g. ACL, Qliksense, Power BI, Alteryx, SQL, etc.) that are used to execute data analytics for audit functions
- Different technology components that make up an infrastructure layer for analytics
Session 6: Advanced Analytics and Emerging Technology
- Use of advanced analytics such as clustering and its use in IA
- Different types of analytical techniques commonly applied
- Statistical techniques that can support identifying anomalies
- Other emerging technologies to look out for
Session 7: Reporting
- Enrich and create impact in your audit reports through data analytics
- How analytics and visualisation can enhance the progress, monitoring and tracking of your audit plan
Session 8: Organisational Structure
- How the value of IA increases through the use of data and analytics
- Key components of a strategy to embed data analytics within the IA function
- Analysing the optimum people model for IA functions
Practical Hands-On Exercises
Sessions 9 and 10 will consist of real life application and hands-on exercises. Using mock sample data, delegates will use data analytics tools to ensure data quality, detect fraud and outliers, test internal controls and perform visual analytics.
Session 9: Lab Session Using Data Analytics
- Data cleaning and validation using Excel formula and functions
- How to validate data quality
- Using Power Pivot and Power Query to analyse large sets of data or automate procedures
- How to detect outliers, potential fraudulent transactions and attest to internal controls using data analytics
Session 10: Lab Session Using Data Visualisation
- How to use a data visualisation tool to perform visual analytics
- How to build charts in a visualisation tool
- How to derive insights from a dashboard in a way that it satisfies the audience needs