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.
Data Driven Movie Prediction & Optimisation Model
The team developed a Box Office Prediction Dashboard and a Session Optimisation Dashboard to help Cathay Cineplexes predict the performance of a prospective movie, and subsequently optimize the programming for the movie.
Automating the Portfolio Construction Process and Allocation of New assets to Existing Portfolios
The team developed a model to automate the typically manual portfolio construction process and efficiently allocate new assets to existing portfolios.
Making the Mean-Variance Optimisation (MVO) Model More Dynamic
The team aimed to identify the models that generated the highest market returns depending on the market state and established the following recommendations:
Stable Market: Sharpe Base
Sharp Market Decline: Sortino Base
Market Recovery: HMM SortinoMVO
Optimising Operations and Avoiding Inventory Stock Outs by Establishing a More Precise Reorder Point and Utilising Data Visualisation to Analyse Inventory Levels
The team developed a predictive model to establish reorder points and alerts, as well as a Dashboard that highlights current and forecasted product demand, aiding DrinkAid in planning future reorder quantities for each component and strategic decisions.
Utilising Revenue and Advertising Data Insights to Minimise Revenue Losses and Optimise Business Expenditure
DrinkAid's manual monitoring of financial metrics has resulted in delayed detection of critical Issues. The team had the following objectives:
- Automated data processing for future updates
- Automated dashboarding
- Anomaly detection
- Forecasting of Sales, and Return on Advertising Spending (ROAS)
How can DrinkAid improve its financial oversight and decision-making?
The team developed a centralized decision-making dashboard that identifies top-selling products, tracks sales by country and platform, and enhances decision-making with accurate, transparent financial data consolidation.
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.