Strategic Financial Management: Tools, Analysis, and Decision-Making

The Microdegree offers a comprehensive understanding of how financial analysis and data-driven tools support corporate strategy and drive value creation. The programme integrates classical financial management, modern technologies, and real-world decision-making to develop strategic thinking and analytical precision.

The courses are delivered by international faculty members and industry practitioners who bring together academic excellence, analytical rigour and a practical perspective on strategic finance.

The learning journey follows a cyclical structure – starting with data acquisition and analysis, moving into financial modelling and investment strategy, and culminating in effective financial communication and capital acquisition. Each course contributes to the development of a well-rounded competence profile, helping learners understand financial decisions from both corporate and investor perspectives.

The learning approach is highly practical: contact sessions and group work are combined with independent assignments. Real-life case studies are used alongside tools such as Excel, Power BI and Python. Discussions, simulations and project-based work create a learning experience that is at once analytical, creative and strategic.

This microdegree is not only about acquiring knowledge; it is designed to shape your professional identity at the intersection of business thinking and financial leadership.

The programme is intended for participants who already have the ability to read and interpret financial statements and who understand the core principles of corporate finance, including investment decisions, the functioning of capital markets, and the relationship between risk and return.

Data Tools for Financial Management –  16 h in classroom, 62 h independent studies  – 3 ECTS
Modern finance leaders must be fluent in data. This course develops the analytical mindset and technical toolkit needed to turn complex financial and economic data into actionable insights. Participants learn how to extract and structure data from diverse sources, apply statistical and econometric models, and present findings using Excel, Power BI, and Python. By the end of the course, learners can support high-stakes financial decisions with clarity, precision, and credibility.
Lecturer: Samuli Saarinen- PhD Student / AML Analyst

Financial Modelling –  16 h in classroom, 88 h independent studies  – 4 ECTS
This course provides in-depth knowledge and hands-on skills in building dynamic financial models to support decisions on capital budgeting, dividend policy, and M&A. Learners construct integrated pro forma statements and dashboards in Excel and Power BI, incorporating data-driven assumptions and scenario analyses. The course also emphasizes ethical decision-making, ESG considerations, and the ability to clearly communicate complex financial outcomes.
Lecturer: Alvin Kamienski – PhD professor and consultant with extensive experience bridging business and education; has taught finance, strategy, and economic freedom in the U.S. and internationally

Investment Decisions  –  16 h in classroom, 62 h independent studies  – 3 ECTS
This course builds a solid foundation in investment principles, risk management, and portfolio construction, enabling participants to evaluate asset classes and make sound investment decisions. Students learn how macroeconomic trends and capital market mechanisms affect portfolio strategies, and how to assess risk-reward trade-offs. By formulating a personal investment philosophy, participants align financial goals with real-world market behavior and investor logic.
Lecturer: Valeria Kiisk – PhD, Partner at Redgate and Head of the Capital Markets Working Group at FinanceEstonia.

Financial Storytelling for Capital Acquisition –  24 h in classroom, 106 h independent studies  – 5 ECTS
As the capstone course of the microdegree, this module challenges students to combine financial modeling, investment strategy, and data storytelling to pitch capital acquisition strategies. Teams develop investor-focused presentations and reports based on rigorous analysis, valuation, and market insight. The final project simulates a real-world investor pitch, enhancing strategic thinking, persuasive communication, and team collaboration in high-stakes finance scenarios.
Lecturer: John Paul Broussard – PhD, finance professor and researcher of artificial intelligence, machine learning, and big data applications in finance.

Upon successful completion of the microdegree, the learner will be able to:

• Acquire and process financial and economic data from various sources using statistical and programming tools. (Application, Transferable)
• Build and apply financial models that integrate assumptions and forecasts to support strategic financial decision-making. (Knowledge)
• Design and evaluate investment portfolios based on macroeconomic indicators, portfolio theory, and risk management strategies. (Application, Critical Thinking)
• Interpret financial analysis results in a strategic context and provide data-driven recommendations for capital allocation and business decisions.(Individual)
• Communicate financial insights and recommendations persuasively to diverse stakeholder audiences using visualizations and structured reports.(Communication, Social)

To complete the microdegree, learners must pass all courses with at least a grade of E (51–60%). Assessment is course-based, with differentiated grading (A–F) based on practical tasks and learning outcomes.

Graduates of the programme will receive a certificate of microdegree with ECTS credits 

Assessment is course-based, with differentiated grading based on practical tasks and learning outcomes of each course

The courses takes place at EBS’s modern campus in Tallinn, Lauteri 3. Students have access to ergonomic classrooms, the EBS library, and the cloud-based Canvas learning platform. The study process is supported by online tools such as Canvas and MS Teams. Free Wi-Fi is available throughout the building.