Financial Organizations Adopting Emerging Technologies: Strategies and Best Practices (Synchronous e-Learning)
About This Course
This course provides a comprehensive exploration of how financial institutions can strategically leverage artificial intelligence (AI) to enhance business objectives such as credit risk management, fraud detection & prevention, meeting financial regulatory requirements, financial risk monitoring etc. Designed for professionals in the finance sector, this course delves into aligning AI initiatives with the core strategic goals of financial organizations. Learners will examine the necessary infrastructure and governance models required to integrate AI responsibly, while navigating the unique challenges associated with varying levels of AI maturity within financial firms. Emphasis is placed on understanding the distinct differences between traditional business initiatives and those involving AI, highlighting the need for innovative planning and execution in the financial context. The course also addresses the critical cultural shifts and regulatory considerations essential for successfully incorporating AI technologies into financial organizations which can help in processes such as determining the financial creditworthiness of borrowers to predict the probability of default to improve the accuracy of credit decisions. By focusing on the financial industry's specific needs, learners will gain valuable insights into optimizing processes and decision-making through AI as a powerful supplementary tool to achieve objectives such as minimizing financial losses in financial institutions.
This course forms part of the SCTP NUS Digital Finance Project Management with AI which consists of 8 modules.
What You'll Learn
• Describe the challenges and financial risks associated with integrating Artificial Intelligence (AI) into financial institutions such as the complexities of aligning AI-driven credit risk assessments and the potential repercussions when these initiatives deviate from core financial strategies.
• Explain the differences between traditional financial processes (such as standard risk assessments, manual budgeting, and regulatory reporting) and AI-enhanced financial initiatives (like predictive analytics for credit scoring and financial planning), emphasizing how the iterative design, testing, and refinement of AI models introduce unique planning and financial management challenges.
• Identify the various AI solutions applicable in finance—such as machine learning models for fraud detection, risk analytics tools, and automated portfolio management systems—and describe their potential impacts on financial performance, regulatory compliance, and strategic decision-making within financial institutions.
Entry Requirements
General Diploma