The Accounting Analytics Capstone course is a compulsory capstone course for undergraduate students pursuing a 2nd Major in Accounting Data & Analytics. We showcase their completed projects below.
Identifying High-Risk Transactions on Grab: A Data- Driven Approach to Anti-Money Laundering (AML)
Grab’s existing process to mitigate & detect ML transactions is labour intensive. The team was tasked to develop an automated solution that minimizes manual involvement and enhances effectiveness of anomaly detection. They adopted a data-driven approach to identify transactions with the highest risk of ML activity.
Enhancing and Streamlining Grab's Anti-Money Laundering (AML) Process
The team was tasked to enhance and streamline Grab's Anti-Money Laundering (AML) process, by developing an efficient and automated solution to mitigate risks. The team adopted the following approach: from data preparation to unsupervised learning to rule-based filtering and supervised learning and finally dashboard development.
Understanding and Leveraging Data from ERP System to Monitor Key Sales Metrics and Customer Buying Trends
The team was tasked to enhance sales performance and drive informed business decisions, by enabling Far East Flora’s management to understand and leverage data from its ERP system to monitor key sales metrics and customer buying trends.
Addressing Restricted Understanding of Far East Flora Market's Business due to Outdated Practices for Data Utilisation
The team proposed new analyses to address the outdated data utilisation practices which resulted in restricted business understanding at Far East Flora Market. The team offered RFM Analysis to identify customers who showed changes in purchasing behaviour to implement targeted marketing to retain customer base and other solutions.
Expanding Lee Wee & Brother’s Market Footprint
The team employed several sophisticated techniques such as the Association Rules model, RFM model, and Geographical Map analysis to achieve a nuanced understanding of customer purchasing patterns and potential markets for expansion. This drove targeted strategies to help LWB further grow & gain a competitive advantage in the market.
Leveraging Data for the Identification and Analysis of LWB’s Key Target Audience and its Characteristics to Refine Business Strategies
The team was tasked to support Lee Wee & Brothers (LWB) in leveraging on relevant data for the identification and analysis of LWB’s key target audience and its characteristics to refine business strategies and better cater to customer preferences and needs.
Expense Claim Anomalies Detection
The team employed rigorous analysis and advanced methodologies to detect anomalies within Grab's employees' expense claims data, identifying irregularities that may pose risks to the company's financial integrity.
Optimising Pricing Strategy and Improving Market Competitiveness
The team was tasked to find out how Fong Lee Metal could better price their quotations to increase the likelihood of closing a deal while improving lead time, thereby optimising their pricing strategy and improving their market competitiveness.
Enhancing Operational Efficiency of FairPrice Online
The team utilised process mining tools to create a graphical representation of FPOnline's order-to-cash process. The output map allows them to compare the actual process to FPOnline's SOP for risk compliance, identifying bottlenecks and inefficiencies.
