This course provides the foundation for financial data analytics used in business and FinTech applications. The objective of this course is for students to gain experience in analyzing financial data using modern machine learning techniques, statistical methods, and prediction models. Students will develop computational skills to perform data analysis using a modern statistical programming environment, and apply these skills to address a range of problems encountered by business firms, including those in the FinTech industry. The topics discussed include an introduction to R language, visualization of financial data, cluster analysis, simple and multiple linear regression, classification models, high dimension data analysis using Lasso, tree regression, and model assessment and selection using cross validation. Students will have hands-on experience in the development of data analytics applications to analyze real world financial problems.
Below are basic parameters for advisors to use when talking to potential FinTech students regarding appropriate prior knowledge, and to ensure that students can be successful. Students should have a strong foundation in very basic concepts from multiple areas listed below. Students should have an understanding of how all of these are impacted by technology and by the regulatory environment.
Good candidates for the FinTech courses should have a background in business, finance, information technology, cybersecurity, computer science, mathematics, data science, or another related field.
Students should be familiar with or exposed to the following competencies:
1. Create and explain the income statement, balance sheet, and statement of cash flows
2. Perform time value of money calculations
3. Value and describe stocks and bonds
4. Evaluate capital budgeting projects