Practice Module for Intelligent Financial and Risk Management

The objective of the practice module is many-fold:

• Firstly, it exposes participants to real world financial services problems so that they can learn to practice the skills they have gained during the component courses in a holistic manner.
• Secondly, it enables participants to demonstrate their proficiency across all the skills that they have learned in the course modules and hence obtain a grade at the Graduate Certificate Level.
• Lastly, it provides an opportunity for participants to demonstrate their critical thinking, problem-solving, and communication skills as they interpret data, defend their analytical decisions, and present insights to stakeholders. 

Participants should have completed, or possess equivalent knowledge of, the four component courses within the Graduate Certificate in Intelligent Financial and Risk Management.

Participants should also be comfortable using AI-assisted tools, including Generative AI and Agentic AI, as thinking partners for analysing information, generating alternatives, evaluating trade-offs, supporting decision making and solving complex business problems. 

There are two parts in the Practice Module.

1. Practice Project

Participants will need to undertake one or more projects to gain practical experience and demonstrate their understanding and mastery of the skills taught in the four component courses. The practice project will require each participant to expend an estimated 10-man days of effort. These days are not expected to be contiguous and may stretch over many weeks and months. These projects may be conducted by individual participants or in teams depending on the nature of the project requirements. Participants are expected to understand business requirements for DS/AI in financial services projects, identify multiple data sources, build sophisticated analytics model and apply key data analytic techniques to find out the insights and solutions.
In the practice project, the module may incorporate complementary forms of assessment, such as scenario-based analytics exercises, verbal explanation of model outputs, and troubleshooting of analytical workflows to evaluate participants’ critical thinking, displaying sound communication skills and having practical problem-solving skills. These activities are designed to be lightweight yet effective in reinforcing real-world analytical competencies.

2. Examination
Each participant is required to sit for an examination on a stipulated date and time.
The overall grade will be based on both the Practice Project and the Examination.