Finance Concentration

Financial Technology and Innovation

Open to Full-Time MS Finance Students

Finance is evolving fast, with fintech, AI, and entrepreneurial finance driving exciting changes across the industry. In this optional concentration, you’ll explore the latest innovations in AI and fintech and learn to spot new opportunities. These timely, in-demand skills open doors to a growing field in finance—and position you for a future at the forefront of financial technology.

In this concentration, students choose two of the following elective options.

FIN 446

Financial Technology

FIN 446

This course provides an introduction to the evolving use of technology in financial markets and applications. One area of focus is “blockchain” technology in financial transactions, markets, permanent historical records and cryptocurrencies. The other major area of focus is innovations such as peer-to-peer transactions and the use of artificial intelligence in evaluating and funding investments. Throughout we will consider the prospects for the success of the new technologies, asking questions such as: How revolutionary are the various parts of Fintech? What are the hidden pitfalls of the technology/business models to individuals, companies and/or society? How will major financial institutions and governments react? What changes are required in legal rules (including internationally) to accommodate Fintech? The course will require working with large data sets (the blockchain) and specific cryptocurrency implementations. While computer programming skills are not required as a pre-requisite, success in the course will require that students learn the basics of the computer science concepts of public-key cryptography, data verification, and simple programming structures (loops, branching).

 

MBA Prerequisite: FIN 402
MS Prerequisite: FIN 462

FIN 478

Intro to AI & Finance

FIN 478

FIN478 covers the application of generative AI technologies across diverse business contexts. The course will help you understand how to integrate Generative AI into today’s business workflows, providing frameworks to decide when and how to use it effectively. You’ll gain hands-on experience designing Generative AI tools to create business value and programming basic LLM-driven applications in Python. Finally, the course will ask you to become conversant with the big questions about Generative AI, to debate the moral, philosophical, and ethical challenges inherent in these systems and technologies.

MS Prerequisites: (GBA 462 or GBA 471),
(GBA 464 or GBA 465 or GBA 485A)

In this concentration, students choose two of the following elective options.

FIN 444

Entrepreneurial Finance

FIN 444

This course provides an introduction to financial theories and tools an entrepreneur needs to start, build, and harvest a successful venture. Lectures and case studies cover financial planning, business valuation (including the venture capital and the real option approach), financing,venture capital funds, compensation structures, and exit strategies.

 

MBA Prerequisite: FIN 402

FIN 443

Private Equity

FIN 443

The Private Equity and Venture Capital [PE/VC] industry is more in the popular press than ever before; funds are larger and more diverse than in any past generation, deals are bigger, scope is worldwide, and wealth-generation seems to be at levels heretofore unseen. Many argue that PE/VC drives major segments of national economies more than ever before, and that it is essential that the industry is better understood and weighed more heavily in the thinking and plans of policy-makers in government and commerce. This course provides exposure to what PE/VC is and how it works. We cover, among other things; the make-up of funds, the composition and operation of PE/VC firms, dealing sourcing, due diligence and investment process, and the roles of partnerships, GPs, LPs, ‘activists’ and Boards. At a higher level, we cover industry performance and competition, fund creation, some international aspects of the business, and differing approaches to financing in different alternative asset categories.

CIS 433

AI & Deep Learning

CIS 433

Artificial intelligence (AI) was born in the middle of the 20th century as a branch of computer science. The early approach of symbolic AI has now been largely supplanted by machine learning. The recent breakthrough in artificial neural network, rebranded as deep learning, represents the state-of-the-art of machine learning in many tasks, including computer vision and natural language processing. This has in turn triggered an unprecedented enthusiasm and huge investment in AI in the business world as well as in society at large. This course introduces the field of AI to business students with a particular emphasis on deep learning which is driving the current AI revolution. The course consists of three modules. The first module establishes the foundation of AI and deep learning. The second module introduces major neural network architectures widely used in practice. The third module touches on generative AI which is particularly promising in recent years. The course emphasizes experiential learning and contains many hands-on projects using TensorFlow broadly and Keras in particular. Specific learning objectives include

  1. Learn the fundamentals of deep learning, including its origin, theory, and training techniques.
  2. Learn the modern network architectures including dense network, convolutional network, recurrent network, and transformer.
  3. Learn major algorithms of generative AI such as variational autoencoder, generative adversarial network, and diffusion models.
  4. Learn TensorFlow Data API
  5. Learn the three approaches of building models in Keras
  6. Learn Conv2D layer to build convolutional network.
  7. Learn LSTM and GRU layers to build recurrent neural network.
  8. Learn the implementation of transformer.
  9. Learn the implementation of variational autoencoder.
  10. Learn the implementation of generative adversarial network.

  11. Learn the implementation of denoising diffusion implicit model.

     

MBA Prerequisites: GBA 412, GBA 485A MS Prerequisi