Towards Financial Industry Transformation: Understanding the AI Development Life Cycle (Synchronous e-Learning)
About This Course
This course is designed to equip financial professionals with the skills and knowledge needed to harness Artificial Intelligence (AI) technologies for strategic advantage. Focusing on the unique needs of the financial industry, the course delves into how AI can drive innovation leveraging on technologies such as blockchain and enhance operational efficiencies in processes such as financial reporting, payments etc. Learners will explore the AI development life cycle with an emphasis on financial applications e.g. credit risk scoring, financial transaction monitoring, credit analysis, Know Your Customers(KYC), trade surveillance etc , learning to manage AI systems responsibly from inception to deployment.
The course also addresses critical industry-specific issues, such as governance, accountability, and compliance with regulatory standards. This course is essential for those looking to lead AI-driven transformation in the financial sector, with examples including AI-powered credit scoring, real-time fraud detection, algorithmic trading, proactive risk management, automated compliance and regulatory reporting, innovative loan underwriting, and tailored customer segmentation. Through real-world case studies and collaborative approaches, learners will gain insights into mitigating AI-related risks and ensuring ethical implementation within their financial organizations.
This course forms part of the SCTP NUS Digital Finance Project Management with AI which consists of 8 modules.
What You'll Learn
• Discuss how Artificial Intelligence (AI) is transforming financial services by exploring its real-world applications in processes such as automated credit scoring, real-time fraud detection, and algorithmic trading, as demonstrated by current industry case studies.
• Examine the critical stages of the AI development life cycle—planning, testing, validation, deployment, and monitoring—and illustrate how each phase advances financial processes, enhancing operational efficiency through systems like risk management frameworks and automated compliance reporting.
• Explore the collaborative strategies employed by financial regulators, institutions, and technology providers to manage risks associated with AI implementation, highlighting initiatives such as inter-agency data sharing and joint efforts to mitigate bias in services like loan underwriting and portfolio management
• Review the latest discussions on AI governance, focusing on legal considerations, user concerns, and accountability measures pertinent to the financial sector, including emerging guidelines for responsible AI deployment in banking and investment advisory functions.
Entry Requirements
General Diploma