DF623 – Applications of Artificial Intelligence in Finance
MSc in Business Analytics
Core Course
DF623 – Applications of Artificial Intelligence in Finance
Course Unit Code: DF623
Type Of Unit: Elective
Level of Course Unit: Graduate
Year of Study: 1
Semester: Semester 3
Number of ECTS Credits: 10
Class Contact Hours: 12
Mode of Delivery
Distance Learning
Prerequisites
None
Course Objectives
The course “Applications of Artificial Intelligence in Finance” offers a comprehensive exploration into the rapidly evolving use of artificial intelligence (AI) within business context, with the special emphasis on the financial services sector. As the predominant consumer of AI services outside the technology industry, the finance sector presents a unique and fertile ground for deploying AI. The course will introduce an array of current AI applications that are transforming financial services. At the same time, the curriculum is structured to ensure that students not only grasp the theoretical aspects of AI deployment, but also gain practical insights into its applications.
Upon completion of this course, students will have acquired essential knowledge and skills pertinent to the application of AI in the business and financial sectors. They will understand the prerequisites for successful AI deployment in organizations and will have developed the ability to identify and prioritize AI use cases in their work environments and companies. This course aims to equip students with the necessary expertise to navigate and contribute to the AI-driven transformation in the financial industry, enhancing their ability to foster innovation and drive efficiency in their professional endeavors.
Learning Outcomes
- Understand the fundamental concepts of Artificial Intelligence (AI) and its contemporary applications in the business domain, especially in financial services.
- Evaluate the benefits and challenges of implementing AI in Small and Medium-sized Enterprises (SMEs), with a focus on implications across various dimensions of financial services sector, including, among others, customer experience, risk management, trading, and lending services.
- Identify and develop competencies for AI deployment and AI use case development, adapting to the evolving landscape of work roles in the finance sector.
- Critically analyze current trends and applications of AI in various sectors of the financial services industry, such as customer experience and service, risk management and compliance, trading and investment management, credit and lending services.
- Assess and prioritize business needs as prerequisites for successful AI deployment, recognizing the importance of aligning AI strategies with business objectives.
- Identify and address the data-related challenges in AI applications, understanding the importance of data quality, volume, and sources for effective AI implementation.
- Integrate AI deployment within a company’s technological capabilities, focusing on the digitalization of business processes.
- Lead and participate effectively in AI deployment projects, ensuring alignment among people, processes, and technologies, and fostering a culture of innovation and collaboration.
- Analyze and address ethical challenges associated with AI-based applications, especially in the financial sector, emphasizing responsible and ethical AI use.
- Utilize a collaborative approach to develop and refine AI use cases, applying knowledge of AI applications, data challenges, and ethical considerations in a practical context.
- Demonstrate an understanding of the future trends and potential developments in AI applications within the business and financial sectors.
- Articulate the key aspects of AI deployment and its implications for companies in financial sector, synthesizing course content to address frequently asked questions and emerging issues.
- Effectively communicate and present AI use case projects, showcasing the ability to translate theoretical knowledge into practical solutions for the financial industry.
Course Content
1st week (MEETING):
• Introduction to AI in business
2nd week:
• Benefits and implications of AI for business
3rd week (MEETING):
• Changing work roles and competences for AI deployment and AI use case development
4th week:
• Current trends of AI applications in finance and investment
5th week:
• Understanding business needs as the prerequisite for AI deployment
6th week:
• Applications and implications of AI on financial services
7th week:
• Data as the engine for AI applications
8th week:
• AI deployment as part of company’s technological capabilities
9th week (MEETING):
• Leading the work of AI deployment in your company, and participating in it
10th week:
• Ethical challenges for AI-based applications
11th week:
• Navigating AI implementation: Model for deployment and common company FAQs
12th week (MEETING):
• The future of AI applications in business and financial sector
Course Features
Weekly self-assessment activities (2%):
On a weekly basis, students will have the possibility to engage with self-assessment activities to judge their own level of understanding of the concepts covered so far. The weekly self-assessment activities provide immediate feedback.
Weekly interactive activities (48% – 4% each):
On a weekly basis, students will have the possibility to interact with the professor, other students, and/or real businesses for the completion of certain activities. These activities are an integral part of the course and help the students comprehend and assimilate the material of each week. Each weekly interactive activity carries 4% of the grade and the professor will provide feedback within 1 week.
All activities will apply the learning from the week on a real organization, which will be approved by the professor during the first week of the course.
Final exam (50%)
The final exam is made up of two parts:
Part I (2 hours) (30%)
The students will be asked to answer questions that refer to AI applications, data strategies, and ethical considerations in business and financial sector. Through these questions, students must demonstrate their comprehension of AI’s integration in companies and financial sector.
Part II (45 minutes) (20%):
The students must answer 20 questions (multiple answers). One attempt only is allowed.
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