We elaborate our research objectives across four key areas:

1. Analytical Goals: We aim to conduct surveys on SMEs and anchor enterprises in Singapore, to explore the status quo of supply chain diagnosis techniques in these companies. Evidence from our survey analytics will guide us in figuring out the bottlenecks in supply chains, and the possibility of related loans turning into defaults. We will also address real-world challenges using state-of-art machine learning techniques such as neural network, shuffled regression, federated learning, etc. These analytical results will solidify the foundation for us to establish ideal theoretical models.
   
   
2. Operational Goals: To align with the digital transformation of enterprises in ASEAN regions, we will propose new scorecards that can capture the shift of tired supply chains to platform-based models. Additionally, we plan to develop efficient, actionable, and interpretable decision rules for bank decision-makers, to complement traditional machine learning methods that often perform as black-box algorithms. Our approach will enable financial institutions to leverage on their daily diagnostics and rich experiences to improve the models constantly.
   
   
3. Economic Goals: We aim to evaluate the economic benefits of supply chain diagnosis in Singapore’s financial sector, with a special focus on the benefits for Asian SMEs and local financial institutions. Our goal is to enhance the profits of local banks and their loan services linked to supply chain activities. Our scorecards will boost trade efficiency along the whole supply chain, thereby enabling a resilient credit financing ecosystem. Our case studies will demonstrate that loan services combined with supply chain diagnosis can ascertain significant monetary benefits for local banks without increasing their financing risks.
   
   
4. Theoretical Goals: We employ prescriptive analytics techniques to refine financial credit strategies and improve the profitability of risk management frameworks. This involved pinpointing and monitoring factors that lead to supply chain inefficiencies or disruptions within Singapore and Southeast Asia. Consistent with modern portfolio optimization problems in finance, we will address a series of risk hedging problems that are faced by operators in banks, particularly when they encounter frequently in daily operations. Our theory will contribute to modern portfolio theory by addressing computational difficulties, and will be delivered through academic publications, which contributes to the scholarly discourse on risk management and optimization in Singapore.