[Industry Talk] Discover the Next-Generation of Internal Audit with Data Science

The MSA Class Committee was honored to have GIC Private Limited (“GIC”) share with SMU School of Accountancy Postgraduate Programme students on their internal audit data science journey through an Online Zoom Industry Talk on 18 September 2020.

By Ho Chu-Ying and Goh Shun Min
Master of Science in Accounting (Data & Analytics) (MSA), 2019 Intake

Discover the Next-Generation of Internal Audit with Data Science

We had Dr. Kelvin Sim and Dr. Nick Yeo, data scientists from GIC Internal Audit Department share how GIC started their data analytics journey four years ago and has successfully transformed internal audit into a data-driven business function. In this industry talk, the speakers shared with us the role of the Data Analytics team, skillsets and core competencies required to be a data scientist in internal audit, and three useful and insightful case studies on the application of data science in internal audit.

Four tasks of the data analytics team
The role of the Data Analytics team is broadly categorized into four tasks: Audit Support, Investigation Support, Continuous Audit, and Advanced DA Projects. Dr. Kelvin Sim led the sharing of how the Data Analytics team performs scripting for audit tests, and at times also double up as programming coaches to the internal auditors. During the investigation, their expertise is tapped on to perform Extract, Transform, Load (“ETL”) process, and Natural Language Processing (“NLP”) on the voluminous data to gather insights. Participants also learnt about GIC automation of the data ingestion process to ensure continuous audit and how machine learning techniques are applied in advanced projects. 

Application of machine learning in internal audit
Dr. Nick Yeo gave participants a glimpse of the application of machine learning techniques in the GIC internal audit. Participants learnt how NLP is used to identify optionality clauses in legal documents, how reinforcement learning is used to conduct SWIFT payment analytics, and the utilization of unsupervised learning to perform portfolio manager behavior analytics to detect anomalies. In the feedback received, participants found these practical demonstrations extremely useful and insightful in helping them understand the applicability of the advanced ML techniques and theories in a real situation.

Auditors with data analytics skills
Participants witnessed how data analytics enhances the execution of audits, providing quick and effective monitoring of continuous controls. Auditors can also more quickly make connections between different datasets, allowing them to focus on more profitable areas like strategic risks. With analytics playing a greater role in internal audit, offering sustainability and agility to businesses; internal auditors equipped with programming skills are going to be sought after in the industry.

The need for Data Analytics
Mr. Lee Ying Choong, Head of IT Audit and Data Analytics, GIC who also joined the discussion shared that, “Machine Learning (ML) algorithms represent a natural evolution beyond rule-based analysis. Business functions that incorporate ML beyond their existing toolkit can expect to develop new capabilities to predict potential outcomes, identify patterns within data, and generate insight difficult to achieve through rudimentary data analysis. Relevant to the ongoing pandemic, analytical capabilities such as Continuous Audits (CA) alleviate the reliance on other parties for critical data and provides baseline assurance that becomes particularly useful in a crisis when audit requests are de-prioritized.”

My data analytics journey with MSA programme
I’m really glad to have the opportunity to join this programme. This programme allows me to start my data analytics journey and achieve my ambition of becoming a business analyst. Almost all our classmates have an accounting background, so it’s really great to find fellow students exploring new fields together. We learn not only hard skills but also soft skills, which are more crucial in the workplace. Programming (Python and R), data visualization (Tableau), and data management (SQL) are the hard skills, while collaboration, communication, and presentation are the soft skills. I have sharpened all these skills in this one-year programme, and I am ready to enter the workforce.  

Feedback for the seminar:

•    “Relevant material and useful demonstrations.”
•    “It was very informative and helped us see the real-life applications of what we learn in school.”
•    “Good to have GIC to share their Data Science Journey with live demos. Have broadened our horizons and applicable to real-life scenarios.”
•    “I enjoyed the talk very much. I liked how the speakers were experienced professionals, the content was interesting, and thought-provoking. Hope that there will be more of such high-quality talks in the future.”
 

To find out more about the MSA programme, visit smu.edu.sg/msa