Mui Kim Chu

This project is funded by the MOE Academic Research Fund Tier 1 grant of $9,876.65. Our research contributes to the development of a toolkit tailored for the accounting industry in these ways: (i) enable the responsible use of algorithmic systems in auditing through better design of intelligent teams and optimizing the collaboration between human and algorithmic systems; (ii) better design of guidelines and rules for human-algorithm interaction; and (iii) better alignment with the fairness, ethics, accountability and transparency principles when designing and implementing algorithmic systems.  

Supported by SkillsFuture Singapore Mentorship Support Grant of $30,000, I used my research in quality management and lean practices to develope a Technology Plan that proposes solutions to automate the creation of new/continuing engagement jobs, tracking of manpower hours, monitoring engagement performance and archival of engagements for an international audit firm.

This is a collaboration with Charity Council and KPMG Singapore. The 2023 Risk Management Survey documents the risk management procedures adopted by charities in Singapore and offers comprehensive and insightful reflections on charities' risk management approaches and practices, including existing gaps. The findings of the RM Survey provide the insights that led to the development of the Enterprise Risk Management Toolkit for Charities and Institutions of a Public Character (IPCs) 2023.  The toolkit provides the 'next steps' guidance for Charities in Singapore such as responding to risk incidents and incorporating climate risk drivers into existing ERM frameworks.

This project aims to provide students with more real-world experience relevant to audit practice through the use of interactive, branching and 360-degree videos. Branching story lines within an interactive decision-making video can be used to develop students’ ability in making professional judgement. Each short video segment along the path of the branching story line presents the students with decision points that auditors commonly face and subsequent choices of how to proceed. As each student makes decisions and proceeds along the story line, he or she creates a unique viewing and learning experience for him/herself. 360-degree videos provide students with realistic and immersive images and videos to help students to visualize what they can observe when they visit clients’ premises. This project has resulted in a Project IP leading to licensing agreement.

This project was a collaboration between SIT, Nanyang Technological University (NTU), Deloitte and Handshakes, supported by Accounting and Corporate Regulatory Authority (ACRA) and Singapore Stock Exchange (SGX). The report was launched at the SID Conference in November 2021.

The 2020 Study on “The Profile of Audit Committees of Listed Companies in Singapore” is the fourth study of audit committees (ACs) of listed companies in Singapore. This report provides a comprehensive and holistic view of the ACs of listed companies in Singapore as at the end of 2019. It serves as a baseline benchmark on what regulators and listed companies can further consider in improving the effectiveness of ACs. The report link can be found in https://isca.org.sg/media/2825349/ac-study-2020-final-report.pdf

This project is funded by ISCA and Seed grant to develop a job budgeting system that automates the job budgeting process of a big audit firm. The novelty of the system is that it uses algorithm to automatically populates the manpower hours and the budget for the planned personnel in charge, calculates the job recovery rate to prevent over-staffing and sends notifications to relevant personnels for further actions. The job budgeting system is integrated with an automatic job scheduling to ensure a smooth transition of data and allocation of resources to jobs based on budgets that have been objectively and scientifically developed. 

This project was supported by Ignition grant of $98,000. We developed a bookkeeping bot that leveraged optical character recognition (OCR) technology to automatically convert the scanned invoices into digitalized data.  We equipped the OCR model with accounting knowledge such as the domain terminologies by re-training and expanding the model to incorporate the knowledge pool we created. We developed a bookkeeping bot that leveraged optical character recognition (OCR) technology to automatically convert the scanned invoices into digitalized data.  We equipped the OCR model with accounting knowledge such as the domain terminologies by re-training and expanding the model to incorporate the knowledge pool we created.