Data Analytics in Risk, Control and Audit™ – in Collaboration with CT Event Asia

Online Course

In stock


19 May 2020
21 May 2020
8:30 - 13:00

This hands-on program aims to give the participants an understanding on the types of data analytics, its benefits, the various standards of data analytics along with their respective limitations.

Program Overview

This hands-on program aims to give the participants an understanding on the types of data analytics, its benefits, the various standards of data analytics along with their respective limitations.

Throughout the program, there will be group discussions, case studies and practical analysis as attendees will learn the different types of data analytics modes. Participants will also be given the opportunity to experience “hands on” in building a Machine Learning model of a business process and discover relationships within datasets.

The program contains a very strong focus on hands-on learning. During the two days, students will spend 30-40% of their time performing practical tasks or taking part in role-playing scenarios.

Software and datasets for Standard, Advanced and “State-of-the-Art” analytics will be provided during the course. Attendees can keep those and use them in their work afterwards.


Learning Outcomes

Upon completion of this program, participants will:

Intended Audience

Program Level and Pre-requisites for Attending

Foundation level, no pre-requisites


Program Duration

  • Online – 3 sessions * 4:30 hrs 

Number of Attendees

Maximum 20 attendees


Training Methodology

A distinguishing feature of our programs is their practical aspect and the gamification of content and delivery. At the end of each module there is a practical exercise designed to reinforce the concepts of the module and to give participants a chance to “get their hands dirty”. The exercises are either scenarios where participants work in groups or individual tasks executed within a specially prepared software environment.

At the same time, gamification is extensively used throughout all of the content. The gamification is done on two levels: full course and individual modules. The full course gamification is based on a gamified storyline across all modules. It increases the levels of engagement, by introducing a mild competitive element, while providing consistent environment for participants.

On the other hand, small gaming activities are present in all modules. Examples include crosswords – based on the content; games like “Hangman” – using terms from the training program, etc. Their purpose is to reinforce learning, while simultaneously applying the principles of Neuropsychology and letting the brain rest every 15-20 mins for a short period of time. The 15-20-minute rests are key to efficient learning, since 20 minutes is the maximum the hippocampus, a part of the brain that takes in learning, can hold.

A specific module of the programs is devoted to creating pilot projects, which ties all of the content together and which the participants will be able to use as a blueprint in their teams for real-life initiatives.

At the start of the course, each participant will receive access to a fully configured software environment that is used for the practical work throughout the course. Participants will retain access after the course and will be allowed to use the software in their work in the following 30 days.

Program Outline

  • Definition and Benefits of Data Analytics in Risk, Compliance and Audit™ (RCA)
  • Organisational Units and Processes Suitable for Data Analytics
  • The Data Analytics Process
  • Types of Data Analytics
  • Gamified Exercise
  • Scenario Work
  • Overview
  • Benefits and Limitations
  • Planning Standard Data Analytics Tests
  • Gamified Exercise
  • Specific Analytical Techniques
  • Examples of Standard Data Analytics
  • Practical Work:
  • Investigating Payroll
  • Investigating Purchasing
  • Overview
  • Benefits and Disadvantages
  • Planning for Advanced Data Analytics Engagements
  • Gamified Exercise
  • Case Studies and Real-life Examples
  • Practical Work
  • Investigating Money-Laudering
  • Investigating Purchasing
  • Overview and Characteristics
    • Continuous Auditing (CA)
    • Business Intelligence (BI)
  • Benefits and Disadvantages
  • Gamified Exercise
  • Planning and Implementation
  • Group Discussion 
  • Continuous Auditing Demo – Real-life System
  • Big Data
    • Group Discussion: How do you understand Big Data
    • Overview, History and Characteristics
    • Big Data Success Stories – Case Studies
    • Big Data Sources
    • Gamified Exercise
    • Practical Work – Accessing an External Dataset
  • Artificial Intelligence (AI) / Machine Learning (ML)
    • Overview
    • Categories and Types of AI/ML
    • Gamified Exercise
    • AI/ML in Risk, Compliance and Audit™ – Use Cases and Case Study
    • Practical Work – Investigating Network Penetration Attempts with KNIME

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