Магистратура
2026/2027
Искусственный интеллект в корпоративных финансах
Статус:
Курс по выбору (Магистр аналитики бизнеса)
Где читается:
Факультет экономических наук
Когда читается:
1-й курс, 2 модуль
Охват аудитории:
для своего кампуса
Язык:
английский
Кредиты:
3
Контактные часы:
20
Course Syllabus
Abstract
This Master's program is designed for finance professionals and students seeking to master the application of artificial intelligence (AI) and large language models (LLMs) in corporate financial analysis and environmental, social, and governance (ESG) assessment. The program combines practical corporate finance methodology with modern AI tools, enabling participants to conduct comprehensive financial and non-financial analysis of public companies. Students will learn to use AI assistants (ChatGPT, Qwen, Perplexity) for financial ratio calculations, trend analysis, scenario modeling, and ESG data interpretation. The program emphasizes hands-on project work, including building interactive HTML dashboards and presentations that integrate financial and sustainability data. By completing this program, graduates will be equipped to leverage AI technologies for advanced financial decision-making, risk assessment, and sustainable business evaluation in real-world corporate environments.
Learning Objectives
- Assess the financial health of a company through key metrics (profitability, liquidity, debt burden) using AI for calculations, interpretation, and scenario analysis in thinking-style modes.
- Analyze non-financial aspects including environmental initiatives, social programs, and governance through processing ESG materials with AI, using both standard chat and deep research-style web-backed analysis modes.
- Integrate financial and non-financial data to form conclusions about the long-term sustainability of a company and build interactive HTML dashboards and presentations that summarize analysis results.
- Experiment with agentic workflows using Comet browser agents for automated collection of sources, navigation across investor-relations and ESG pages, and extraction of relevant fragments.
Expected Learning Outcomes
- Conduct AI-enhanced financial ratio analysis and comparative evaluations using Thinking-style reasoning
- Identify and analyze key ESG metrics using AI-powered deep research and agentic approaches for stakeholder assessment
- Create interactive AI-powered dashboards linking financial and ESG data with visual representations
- Develop AI-enhanced presentation with HTML templates, integrating financial metrics and ESG analysis
- Summarize project work and document AI tool effectiveness for financial and ESG analysis
Course Contents
- Introduction to Artificial Intelligence
- Fundamentals of Prompt Engineering
- AI Applications in Corporate Finance
- Financial Statement Analysis with AI
- AI-Based Text Generation for corporate reports and presentations
- Development of Specialized Financial Assistants, Custom GPTs
- ESG Analysis and Digitalization of Non-Financial Reporting
- Integration of Financial and Non-Financial Data
- Final Analytical Project
Bibliography
Recommended Core Bibliography
- Amel-Zadeh, A., & Serafeim, G. (2017). Why and How Investors Use ESG Information: Evidence from a Global Survey.
- Canty D. Agile for Project Managers – Auerbach Publications, 2015 – 234 p. ISBN:9781482244984 (доступ через электронную библиотеку НИУ ВШЭ http://library.books24x7.com/bookshelf.asp, для перехода по ссылке нужна авторизация в системе удаленного доступа ресурса)
- Clive Wilson Designing the Purposeful Organization: How to Inspire Business Performance Beyond Boundaries, Kogan Page © 2015 (доступ через электронную библиотеку НИУ ВШЭ https://library.books24x7.com/toc.aspx?bookid=77664, для перехода по ссылке нужна авторизация в системе удаленного доступа ресурса)
- Sherman, E. H. (2015). A Manager’s Guide to Financial Analysis : Powerful Tools for Analyzing the Numbers and Making the Best Decisions for Your Business: Vol. Sixth edition. AMA Self-Study.
Recommended Additional Bibliography
- Arnott R.J., McMillen D.P. A Companion to Urban Economics. John Wiley & Sons, 2006. 604 p.
- Clotilde Coron. (2018). From dashboards to Big Data in HR: three uses of quantification in HR, in the light of sociology of quantification. Post-Print. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.p.hal.journl.halshs.01961223
- Harvard Business Review Press. (2019). Artificial Intelligence : The Insights You Need From Harvard Business Review. La Vergne: Harvard Business Review Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=2003692
- Winkler, B. A Flow-of-Funds Perspective on the Financial Crisis.Volume I: Money, Credit and Sectoral Balance Sheets / Bernhard Winkler, Ad van Riet, Peter Bull. - London: Palgrave Macmillan, 2014. – 317 p. Retrieved from: https://link.springer.com/book/10.1057/9781137352989
- Платова, Е. Д. Effective Presentations in English : учебное пособие / Е. Д. Платова. — Оренбург : ОГУ, 2019. — 140 с. — ISBN 978-5-7410-2406-5. — Текст : электронный // Лань : электронно-библиотечная система. — URL: https://e.lanbook.com/book/160030 (дата обращения: 00.00.0000). — Режим доступа: для авториз. пользователей.