IS4000

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Application of AI in Financial Services

Course (UG/PG)

Undergraduate

Offering Unit/Department

Course Description

The Application of AI in Financial Services is an SMU-X experiential course delivered in partnership with Union Bank of Switzerland (UBS), providing students with immersive learning opportunities that bridge academic theory with industry practice. Students collaborate directly with UBS professionals to tackle authentic business challenges in financial services, developing innovative AI-driven solutions across domains such as trading, risk management, and banking operations. Generative AI will be the enabling technology for the course.Working in multidisciplinary teams under faculty mentorship, students engage in a comprehensive project lifecycle—from initial problem scoping and stakeholder analysis through solution design, development, and final client presentation. This industry-embedded approach ensures students gain practical experience with cutting-edge AI technologies, i.e. large language models (LLMs), while understanding their real-world application constraints and business impact within the financial services sector.

Course Learning Outcomes

Course Objectives

Upon completion of the course, students will be able to:

● Analyze complex financial services business challenges to identify opportunities for AI-driven solutions.

● Evaluate the suitability of different AI technologies and methodologies for specific financial industry applications.

● Design and develop functional LLM-powered business applications that address real-world financial services problems.

● Implement AI platform features to execute data analysis, application development, system integration, and workflow automation.

● Apply project management methodologies and professional collaboration practices in industry partnership settings.

● Assess and adapt to uncertainties and constraints inherent in technology-driven business projects.

● Synthesize technical AI concepts with financial domain knowledge to create innovative, practical solutions.

● Present and defend AI solution recommendations to industry stakeholders and clients

Competencies

1. Implement LLM technologies to develop functional financial services applications

2. Integrate AI solutions with existing financial technology systems and workflows

3. Design AI architectures that meet financial industry security and performance standards

4. Apply financial services domain knowledge to identify AI implementation opportunities

5. Assess regulatory compliance requirements for AI solutions in financial contexts

6. Evaluate business risks and develop mitigation strategies for AI-driven financial applications

7. Construct business cases that demonstrate ROI and value creation for AI initiatives in finance

Discipline-Specific Competencies

Applications Development, Problem-solving & analysis, Business Innovation

SMU Graduate Learning Outcomes

Disciplinary knowledge, Critical thinking & problem solving, Collaboration and leadership, Ethics and social responsibility, Self-directed learning, Communication

Grading Basis

GRD - Graded