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Search Result of FINTECH : 27 found

CSIT 5920
Financial Technology for Engineering Professionals
[3-0-0:3]
Previous Course Code(s)
CSIT 6000H
Exclusion(s)
ISOM 5330, ISOM 5340
Description
Innovative computing technology has significantly changed the financial landscape in banking, insurance, gaming (gambling), investment and their respective regulatory frameworks. This course will give students new insights and solid understanding of how and why different IT infrastructure, technical designs and implementations are detrimental to success, and prepare the students for senior technology leadership positions in the banking, insurance, investment, IT audit, government/regulator, innovation and entrepreneurship areas. The course will cover the challenging FinTech issues in (i) IT strategy and governance, (ii) IT development and operations and (iii) the future data ecosystem. There will be class discussions and presentations on system design, flow analysis, modeling, POC (proof of concept), and MVP (minimal viable product) of various FinTech, lnsurTech and RegTech applications.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Describe FinTech and different business & finance model.
- 2.
  Identify FinTech and different payment systems.
- 3.
  Define digital identity, privacy and authenticity.
- 4.
  Apply BlockChain/DLT to solve real-world problems.
- 5.
  Recognize legal challenges and digital forensics in FinTech.
ECON 5040
Economics of Financial Technology
[2-0-0:2]
Background
Basic knowledge of macroeconomics
Description
This course focuses on using economic concepts to analyze the implications of financial technologies (FinTech) on the macroeconomy. It also addresses policy implications of FinTech on financial stability, central banking, and monetary policy. The aim is to highlight the importance of formulating appropriate policies to foster healthy development of the FinTech sector and at the same time ensure the financial stability of the economy.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Use economic concepts to analyze the reasons for the rises of FinTech.
- 2.
  Explain implications of FinTech on the financial sector and the rest of the economy.
- 3.
  Identify potential benefits and risks of FinTech for financial stability.
- 4.
  Address implications of FinTech on central banking and monetary policy.
EMBA 5760
Managing Emerging Technologies
[1-0-0:1]
Description
This course provides a managerial overview of new technological innovations such as Internet of Things, big data analytics, AI, FinTech, blockchain, and cryptocurrencies. We will go through the technological foundation of these new developments and how they connect with each other to transform businesses. The course will conclude with practical advice on how to strategically utilize and manage these new technological innovations.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Identify the properties and trends of emerging technologies.
- 2.
  Compare and contrast different data analytic techniques, AI, and their strategic or managerial values.
- 3.
  Characterize the FinTech landscape and opportunities and related technology development.
- 4.
  Explain the key features of blockchain and its design principles.
- 5.
  Compare and contrast the purposes of blockchain payment transactions and smart contracts.
- 6.
  Characterize initial coin offering (ICO) and its business and social values.
FINA 5240
FinTech Analytics
[2-0-0:2]
Description
The course will be based on the open-source Python language which provides a wide variety of statistical and graphical techniques, and is well-suited for data manipulation, calculation and graphical display. The first part of the course will be for general introduction to Python, and then use of specific tools like matrix manipulation, optimization, random numbers and simulation, etc. will be illustrated with financial applications. Some familiarity and prior experience with a proper programming language, beyond standard Excel, is recommended.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Demonstrate functional proficiency in Python programming.
- 2.
  Apply the control and data structures to solve computational problems.
- 3.
  Perform data input/output and simulations, and produce high quality graphics/plots.
- 4.
  Use packages of relevance to quantitative finance.
- 5.
  Apply the programming techniques in financial context.
FINA 5260
FinTech: The Future of the Financial Industry
[2-0-0:2]
Previous Course Code(s)
FINA 6910A
Description
This is an introductory course to Financial Technology (FinTech) which includes Insurance Technology (InsurTech) and Regulation Technology (RegTech). The student will have a solid understanding of the underlying information technology being applied in various innovative business models to disrupt the finance and banking landscape globally. The critical business, social/ethical, legal and technology issues and the related risks faced by corporate executives when planning FinTech projects using quant finance models, DLT, crypto-token, AI, big data and algorithms to drive innovations in banking and finance will be discussed in class. Live demos will be conducted to illustrate the proof-of-concept and their applications in real world scenarios. Key industry developments and the impact to stakeholders will be examined.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Identify the FinTech, InsurTech and RegTech landscape, its segment, regulations and ecosystem.
- 2.
  Confidently drive FinTech project developments as part of the executive team and deal with arising issues from various stakeholders, i.e. IT, legal, audit, compliance and regulations.
FINA 5270
Portfolio Management with Fintech Applications
[2-0-0:2]
Previous Course Code(s)
FINA 6900Y
Prerequisite(s)
FINA 5120
Description
This course will focus on the key dimensions of Portfolio Management with FinTech Applications, and will give a predominant place to Artificial Intelligence, as a way to process and leverage the “Big Data” and automate the Portfolio and Wealth Management processes. The course will begin by a brief review of the fundamentals of Portfolio Management, FinTech and Artificial Intelligence and the advances in technology and data that has led the industry to where it is today. It will then delve into the Asset Management and Wealth Management value chains through a series of applications that enable students the critical skills they need to operate as expert actors in FinTech. The course will also expose students to the existing FinTech landscape and ecosystem within the portfolio management industry and will also touch upon on how Artificial Intelligence augments humans to make them better portfolio and wealth managers.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Explain the fundamentals of portfolio management with FinTech applications.
- 2.
  Recognize the FinTech landscape within the Portfolio Management space.
- 3.
  Use Artificial Intelligence in Portfolio Management to solve applied Business Problems.
- 4.
  Present the future trends that are coming to Portfolio Management.
FINA 5280
Smart Applications of Distributed Ledger Technology
[2-0-0:2]
Previous Course Code(s)
FINA 6910B
Description
Blockchain and Distributed Ledger Technology (DLT) are growing in use. This course covers the fundamental concept, design and implementation of the distributed ledgers and blockchain technologies in FinTech, InsurTech and other business areas. The characteristics and properties, as well as misconceptions, of blockchains will be discussed.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Understand what is Distributed Ledger Technology (DLT) / Blockchain that supports the disruptive business strategies/models in banking and finance.
- 2.
  Explore and critically examine the deployment of any one or more of the DLTs, i.e. Blockchain, Ethereum, Hyperledger, R3 Corda and Stella in different environments.
- 3.
  Design the FinTech/InsurTech/RegTech business using BIDT and LoNG PESTEL model.
- 4.
  Analyze the socio-economic impact in the deployment of DLT instead of the traditional model.
- 5.
  Acquire the fundamental and practical knowledge to be entrepreneur or project management in the FinTech and Innovation industry.
FTEC 5031
Advanced Probability Theory
[3-0-0:3]
Description
The course will give students a deeper understanding of the foundations of probability theory, such as probability theory from a measure-theoretic perspective, convergences of distributions and probability measures, and conditional expectations. During the course, important theorems, such as Radon-Nikodym theorem, Fubini theorem, and general central limit theorems, will be investigated.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Derive advanced probability-theoretic results of importance for statistical inference.
- 2.
  Independently prove important theorems in probability theory.
- 3.
  Independently solve advanced problems in probability theory.
- 4.
  Perform mathematically stringent probability-theoretic reasoning.
- 5.
  Critically apply central results in probability theory on typical problems related to FinTech.
FTEC 6000
FinTech Attachment
[2-4 credits]
Description
This course provides an opportunity for students to develop and apply FinTech research in an industrial organization. Students will work in a designated organization conducting FinTech research-related work under the supervision of their supervisors. Graded P or F.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Identify important FinTech research and latest advances in the industry.
- 2.
  Compare and contrast the FinTech projects undertaken by the industry and the academia.
- 3.
  Apply the FinTech research knowledge and capability to address a real-life problem.
- 4.
  Develop professional analysis, presentation, and report writing skills.
FTEC 6101
FinTech Program Seminar
[0-1-0:0]
Description
Advanced seminar series presented by guest speakers and faculty members on selected topics in Financial Technology. This course is offered every regular term. Graded P or F.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Apply essential skills in communicating research results.
- 2.
  Prepare professional presentation with the necessary presentation aids.
- 3.
  Ask intellectual questions in professional settings.
- 4.
  Interact with audience in research seminars effectively.
FTEC 6910
Special Topics in Fintech
[1-3 credit(s)]
Description
This course examines areas of current interest and special topics in financial technology. It employs a mix of lectures, case studies, and projects. Topics may vary from year to year and will be announced at the beginning of each term. This course may be graded by letter or P/F for different offerings.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Express in-depth understanding of key Fintech concepts and their applications in financial markets.
- 2.
  Demonstrate necessary skills to analyze the issue and make contribution to the discussion.
- 3.
  Ask intellectual questions and communicate effectively in academic and professional settings.
- 4.
  Relate the concepts and methodologies in the course topic to practical implementation in the financial technology industries.
GFIN 5300
FinTech
[1-0-0:1]
Description
The course will introduce the current state of FinTech and discuss how financial institutions and their stakeholders are being affected by new technologies. Students will understand how traditional business models are being impacted by the application of new technologies and how financial innovation impacts money and payment systems. The course offers a combination of case studies, lectures, and guest speaker sessions, and will identify current trends and opportunities within the FinTech ecosystem.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Describe the FinTech ecosystem and its impact on global financial market.
- 2.
  Identify opportunities and threats that FinTech disruptions may bring to the financial market.
- 3.
  Discuss how disruptive technologies can be applied to real-life finance issues and investment strategies.
- 4.
  Identify the privacy and regulatory challenges that FinTech presents for risk management in the financial industry.
IMBA 5120
Managing Emerging Technologies
[1-0-0:1]
Previous Course Code(s)
IMBA 512
Exclusion(s)
ISOM 5020
Description
This course provides a managerial overview of several cornerstone technologies, including blockchain, business analytics, and fintech, that fuel this digital transformation. We will provide students with a solid technical foundation and working knowledge of these new technologies and how they interact with each other to transform businesses. Analysis will be drawn from exemplary cases to develop guidance and insights on how to strategically utilize and manage these new technological innovations.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Describe the technological foundation of blockchain and smart contract.
- 2.
  Compare and contrast the differences between cryptocurrency and fiat currency and physical commodity.
- 3.
  Compare and contrast different types of blockchains in terms of the degree of trust and decentralization and their applications.
- 4.
  Compare and contrast big data and general business analytics applications.
- 5.
  Explain the concept, and strengths and weaknesses of different analytic techniques.
- 6.
  Identify factors that facilitate the emergence of fintech.
- 7.
  Compare and contrast different fintech strategies and applications.
ISOM 5220
FinTech Regulation and Compliance
[2-0-0:2]
Description
This course provides students with frameworks, concepts, and background to understand the role of regulation, compliance and assurance in FinTech markets from both technology and business perspectives. The course will also examine the perspectives of government officials, investors, managers, and consumers in how they benefit from, guide, and influence the evolution of regulation and associated compliance activities.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Identify major regulatory objectives and implications for FinTech.
- 2.
  Assess how technology influences and is influenced by regulation and markets.
- 3.
  Describe RegTech and InsurTech ecosystems to understand regulatory transformation and opportunities created by relevant technologies.
- 4.
  Examine the risks and challenges associated with technology innovations in the context of FinTech applications.
- 5.
  Discuss future directions of FinTech and its implications for their own future.
ISOM 5330
Financial Technology for Business Professionals
[2-0-0:2]
Previous Course Code(s)
ISOM 6000E
Exclusion(s)
ISOM 5340, CSIT 5920
Description
This course provides students with an overview of the underlying information technologies used in the finance, banking, and insurance industries. The course covers the critical business, legal and technology issues and the related risks faced by corporate executives when analyzing, designing, launching and managing Financial Technology projects to drive business innovations.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Explain what FinTech is and the underlying ICT (Information Communication Technology) that supports the disruptive business strategies/models.
- 2.
  Explore and assess the threats and the business opportunities in the innovative finance landscape with Artificial Intelligence, big data, blockchain and distributed ledger technology (DLT).
- 3.
  Critically examine the innovative FinTech business models, ICT and their respective critical success factors, risks, compliance and legislative frameworks related to Crowd Funding, Fast Payment, Financial Intelligence, Quantitative Finance, Algorithmic Trading and High Frequency Trading for institutional/professional traders vs. retail traders, and Robo-Traders.
- 4.
  Lead FinTech development teams when dealing with stakeholders from business, IT, legal, audit and the regulators.
- 5.
  Manage global FinTech and InsurTech projects and be part of the senior executive team.
ISOM 5340
FinTech and Big Data Financial Analytics
[2-0-0:2]
Previous Course Code(s)
ISOM 6000F
Exclusion(s)
ISOM 5330, CSIT 5920
Description
Recent technology innovations have reshaped the finance industry, leading to new way of how financial information is disseminated, processed and analyzed. Topics to be covered will include: artificial intelligence in financial analytics, big data alpha models, algorithm trading and high frequency trading, social trading, robo-advisor, P2P lending, cryptocurrency and blockchain.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Describe the emerging trend of technology-enabled financial applications.
- 2.
  Explain the quantitative trading with big data.
- 3.
  Explain the role of artificial intelligence in financial applications.
- 4.
  Define the mechanism behind the Cryptocurrency.
- 5.
  Conduct basic financial analytics with Python programming language.
ISOM 5740
Managing Financial Services Operations
[2-0-0:2]
Prerequisite(s)
ISOM 5700
Description
This course focuses on the products and processes in the financial industries. It analyzes and evaluates the designs and performances of the internal operations and the different distribution channels of the financial institutions, and identifies opportunities for continuous improvement in productivity and efficiency. It also covers the issues of quality control and operational risk management, the application of IT in the industry. It will also discuss the automation/outsourcing of the financial operations for non-financial institutions to improve the financial performance and risk management in the supply chain.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Explain and evaluate financial markets and fund flow and distribution channels, the business processes in an economy and in the financial institutions (FI), with focus on banking industry.
- 2.
  Design and critique business processes for improving the productivity and service quality of the FIs.
- 3.
  Integrate and evaluate the different business processes and service experience in the financial organizations to create competitive advantages for the FIs.
- 4.
  The new development and innovations in the financial industries (fintech).
- 5.
  Introducing compliance, risk management for FIs and corporations.
MAFS 5380
Entrepreneurship in Fintech
[3-0-0:3]
Previous Course Code(s)
MAFS 6010X
Description
The course covers how to identify and evaluate business opportunities in the fintech context, formulate the business model and strategy, and how to raise venture capital (VC). The financial issues confronting fintech startups are different from traditional financing approaches. The course will discuss in detail on preparing an effective pitch deck, the key terms of VC financing, and initial public offering (IPO).
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Conduct independent research to handle the complexities in emerging trading applications and finance technologies.
- 2.
  Analyze problems with real industry data (such as trading data and market data).
- 3.
  Apply financial mathematical theories to assess the values for fintech startups and new ventures.
- 4.
  Draw meaningful implications to capture market behaviors and make forecasting.
- 5.
  Develop an effective pitch deck and present to VC investors.
MFIT 5001
AI for FinTech
[2-0-0:2]
Background
Linear Algebra, Multivariable Calculus, Probability and Statistics
Description
This course covers the basic theory of artificial intelligence and machine learning, and their applications to FinTech. Topics include natural language understanding and sentiment analysis using various deep learning architectures. The course also covers basic natural language processing methods for applications such as event and anomaly detection, fraud and fake news detection. The course will also relate sentiment and affect analysis to stock market trading, market monitoring, and to compliance and regulatory-related adverse events.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Describe and explain basic concepts of Machine Learning and Natural Language Processing (NLP).
- 2.
  Implement Machine Learning and NLP algorithm in the FinTech domain.
- 3.
  Analyze different financial related problems and their possible solutions.
- 4.
  Explain how and when an NLP solution (e.g. Sentiment Analysis) can be used in the FinTech industry.
MFIT 5005
Foundations of FinTech
[2-0-0:2]
Description
This course aims to provide a foundational introduction to financial technologies. More specifically, this course will cover various important financial technologies and innovations, including investment and financing technologies such as P2P lending and crowdfunding, payment technologies such as mobile payments, wealth management technologies such as robo-advisors, blockchain technologies such as cryptocurrencies, and other technologies such as InsurTech and RegTech.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Describe the principles of P2P lending and crowdfunding.
- 2.
  Explain the principles of wealth management technologies.
- 3.
  Define the foundational theories of blockchain technologies.
- 4.
  Identify the functions of InsurTech and RegTech.
- 5.
  Analyze advantages and limitations of financial technologies qualitatively and/or quantitatively.
- 6.
  Apply finance or economics to the analysis financial technologies.
MFIT 5006
Mathematical Foundation of FinTech
[2-0-0:2]
Description
This course teaches mathematical and quantitative skills as a technical preparation for development of financial technology. The topics covered in this include multivariate calculus, linear algebra, optimization, numerical computation, elementary number theory for cryptography, probability, statistics and other topics, with applications to finance.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Recognize a wide variety of statistical models.
- 2.
  Identify a wide variety of optimization algorithms.
- 3.
  Develop skills on evaluation of models and optimization algorithms.
- 4.
  Differentiate strength and weakness for difference models and algorithms.
- 5.
  Implement at least one programming language, e.g., Python, R or MATLAB.
MFIT 5008
Decision Analytics for FinTech
[3-0-0:3]
Description
This course aims to introduce decision analytics instruments and their applications in FinTech. Main topics covered in this course include basic probability and statistics, predictive analytics, prescriptive analytics such as linear programming integer programming, dynamic programming and sequential decision making, stochastic models, quality control, Monte Carlo simulation, game theory, and their applications in various areas of FinTech.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Define basic theories of probability and statistics.
- 2.
  Apply prescriptive analytics to modeling and analysis.
- 3.
  Apply predictive analytics to modeling and analysis.
- 4.
  Analyze real problems via quality control and game theory.
- 5.
  Conduct Monte Carlo simulation to solve real problems.
- 6.
  Explain the applications of decision analytics to various FinTech-related problems.
MFIT 5009
Optimization in FinTech
[3-0-0:3]
Description
This course introduces the basic theory of convex optimization and illustrates its practical employment in a wide range of FinTech applications. Techniques and applications of nonconvex optimization are also considered. Examples of the problems considered include Markowitz portfolio optimization and its many variations (e.g., maximum Sharpe ratio portfolio, risk-parity portfolio, robust portfolio, sparse portfolio), data fusion, machine learning for classification/estimation, imputation of missing data, big data analysis, outlier detection, data clustering, and deep learning.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Design a portfolio based on optimization.
- 2.
  Clean data (outlier detection and imputation of missing data).
- 3.
  Perform data fusion from different sources via optimization.
- 4.
  Analyze high-dimensional data via clustering and low-rank fitting methods.
- 5.
  Employ deep learning methods in a financial context.
MFIT 5012
FinTech Enrichment Workshops
[0 credit]
Previous Course Code(s)
SBMT 6020A
Description
The course aims to broaden MSc(FinTech) students’ horizon and develop students’ essential knowledge and skills related to financial technology through participating in a series of enrichment activities. Different speakers, practitioners, or FinTech professionals may be invited to conduct the workshops or engagement activities. Students are required to attend at least six enrichment activities recognized by the program in order to pass this course. Graded PP, P or F.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Identify the updated development and the current market trend in different sectors of Financial Technology industry.
- 2.
  Apply the knowledge and practical skills attained from the enrichment activities in the real business world.
MGMT 5870
Entrepreneurship and Innovation in FinTech
[2-0-0:2]
Description
This course introduces fundamental concepts relevant for developing FinTech entrepreneurial opportunities. The course begins with frameworks for understanding technology innovation and evolution, and then dives into how new ideas can be generated and assessed, and brought to market by developing an effective organization and relationships in the financial ecosystem.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Define technology innovation and evolution.
- 2.
  Develop and assess creative FinTech ideas.
- 3.
  Develop the business model for a FinTech innovation.
- 4.
  Develop effective external collaborations in the financial ecosystem.
- 5.
  Building an effective entrepreneurial organization to harness the FinTech ideas.
MSBD 5017
Introduction to Blockchain Technology
[3-0-0:3]
Previous Course Code(s)
MSBD 6000D
Description
This course introduces basic concepts and technologies of blockchain, such as the hash function and digital signature, as well as the blockchain applications, especially in Fintech. The students will learn the consensus protocols and algorithms, the incentives and politics of the block chain community, the mechanics of Bitcoin and Bitcoin mining. The course also covers the limitations and possible improvements of the blockchain system.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Identify the fundamental technologies about blockchain and cryptocurrencies.
- 2.
  Analyze the algorithms, optimization, and tradeoff of the distributed system.
- 3.
  Develop de-centralized applications over blockchain.
- 4.
  Write smart contracts on Ethereum platform.
- 5.
  Identify the token economy and mining eco-system.
- 6.
  Design advanced consensus algorithms taking into consideration of scalability, security, and privacy.
- 7.
  Write blockchain technical white paper supporting solid business plan.
MSDM 5058
Information Science
[2-1-0:3]
Background
Good performance in undergraduate mathematics
Description
This course will cover: (1) decision theory and its applications to ﬁnance; options and payoff diagrams, binomial trees; (2) portfolio management of financial time series using mean variance analysis; (3) evolutionary computation for optimization, with applications in ﬁnding good prediction rules in finance; (4) measure of information, various information entropies, and methods of maximum entropy; (5) game theory and its applications in competitive situations; (6) multi-agent systems modeling and applications to social networks and financial systems.
Intended Learning Outcomes
On successful completion of the course, students will be able to:
- 1.
  Explain the concept information measure, mutual information, and various types of information entropy.
- 2.
  Describe and explain the method of Bayesian decision criterion and other common tools in decision theory.
- 3.
  Explain association rule in prediction using decision theory and data pre-procession.
- 4.
  Define options with examples in payoff diagrams and binomial tree.
- 5.
  Explain the method of mean variance analysis in portfolio management.
- 6.
  Assess the financial time series database to form new tools of FinTech.
- 7.
  Describe and explain the method of evolutionary computation (genetic algorithm) and its applications.
- 8.
  Explain and apply the game theory (zero and non-zero sum games, Nash equilibrium and Pareto optimum).

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