University Catalogues

Finance and Technology (FT)

FT 323 Introduction to FinTech     (3 credits)

Pre-Req: FI 306
Formerly FI 323

This course on Financial Technology (FinTech) aims to provide students with an introduction to the financial industry and a broad overview of the FinTech universe. The course specifically covers the role of technological innovations in shaping the financial services, emerging business models and products, and key factors, such as AI/ML, blockchain and data/APIs, that are enabling a massive disruption across the industry. It also provides an overview of the market structure, regulation and functions of the financial industry, in addition to techniques for founding and funding FinTech startups.

Typically Offered: Fall and Spring

FT 324 Blockchain Applications and Decentralized Finance     (3 credits)

Pre-Req: FI 305

This course aims to provide students with an introduction and broad overview of the DeFi (Decentralized Finance) universe, including Digital Assets, payments, currencies and e-Money/CBDC. The course specifically covers the role of Blockchain / Web3 and Metaverse related innovations pertaining to the financial services industry, in addition to how these can disrupt the traditional world of FinTech and Financial Services. It also covers areas such as AltCoins, NFTs, trading and regulations.

Typically Offered: Fall and Spring

FT 370 Investment Applications of Natural Language Processing     (4 credits)

Pre req: CS 230 and FI 306

This hands-on, advanced, multi-disciplinary course will teach students to extract investment signals contained within financial text using computational tools. It combines capital market theory, human behavioral characteristics, with technology to create systematic advantages for investors. Students will learn Natural Language Processing (NLP) techniques to systematically extract meaning and behavioral cues from financial text and implement them using Python programming language and its specialized libraries. Students will create trading signals based on features found within texts and will establish the strength of those signals through back testing.