AI and Analytics in Finance, Credit and Related Risks (Classroom and Asynchronous e-learning)
About This Course
Increasingly, employers today mandate employees to be equipped with skillsets in coding, analytical thinking and artificial intelligence to help to resolve organisational challenges, automate business and accounting processes, data crunching, report generation and providing financial advice. Similarly, credit-related risk is an essential area of business and finance, which leverages on the application of machine learning and data mining tools to large customer databases. In this course, learners will be equipped with the fundamental tools for credit risk modeling and evaluation by data analytics techniques towards supporting robust credit risk evaluation in their organisations.
As this micro-credential course is only offered in the FlexiMasters in Business and Financial Analytics programme, learners are required to enrol into the programme and complete all required courses within this programme.
What You'll Learn
1. Write codes to solve Accounting and Finance problems programmatically by creating Artificial Intelligence (AI) models using R, Python, Keras, Hadoop, Spark and API.
2. Analyse data to sufficiently derive, communicate analytics outcome and eventually create AI models in Accounting and Finance.
3. Implement a simple system in Amazon Web Services (AWS), including engineering work in implementing AI model in Accounting and Finance.
4. Employ data modelling skills for risky events.
5. Explain credit risk modelling concepts in detail.
6. Describe relevant data mining techniques for robust credit risk evaluation.
7. Utilise analytics tools for credit risk and credit scoring applications.
Entry Requirements
While no pre-requisites are needed, learners with relevant background and/or experience may have a better understanding of the course content.