Financial Analytics

Program: 6B04106 “Financial Analytics”
University: Eurasian Technological University
Level: Bachelor’s, NQF Level 6
Mode of Study: Online
Languages: Russian, Kazakh, English
Credits: 240
Duration: 2–4 years
Partner Institution: Swiss Institute of Technology and Entrepreneurship (dual-degree program)

Program Goal:
The program aims to prepare highly qualified specialists in financial analytics capable of building financial and economic models, analyzing and interpreting data using digital and analytical tools, assessing risks, and developing well-founded managerial decisions in the context of digital transformation and sustainable development.

Distinctive Features:

• Dual-degree program with an international partner

• Focus on integrating business analytics, finance, and digital technologies

• Aligned with the professional standard: “Business Analysis in Information and Communication Technologies” (approved 05.12.2022)

Learning Outcomes:
Graduates will be able to:

1. Analyze macro- and microeconomic indicators, forecast trends, and provide strategic development recommendations.

2. Evaluate and optimize business processes using management approaches and economic models.

3. Apply digital technologies and BI tools for data analysis and managerial decision support.

4. Use programming languages and machine learning methods to solve financial-analytic tasks.

5. Apply statistical and analytical methods to interpret financial data and identify patterns.

6. Analyze financial statements, detect deviations, and make recommendations according to international standards.

7. Build financial models using discounting methods, Excel, and statistical tools for project evaluation.

8. Assess financial stability, investment attractiveness, and risks based on analytical data.

9. Develop and present data-driven financial proposals using visualization and modern business communication techniques.

10. Plan, implement, and evaluate business and ICT projects using project management methods and analytical tools.

11. Consider legal, ethical, and environmental aspects of financial activities in the context of sustainable development and corporate responsibility.

12. Develop personal and meta-competencies—responsibility, critical thinking, initiative, and teamwork—for effective professional activity in a digital economy.

13. Make effective entrepreneurial decisions through business idea development, planning, market analysis, financial calculations, risk management, and regulatory compliance.

Core Courses:

1. Research Methods: Methods for scientific research, data collection and analysis, hypothesis testing, critical thinking, and reporting results.

2. Law and Anti-Corruption Culture: Key principles of law, citizens’ rights and obligations, anti-corruption practices, ethical decision-making, and legal analysis skills.

3. Entrepreneurship Fundamentals: Business idea development, business planning, market analysis, financial calculations, risk management, and innovation.

4. Ecology and Life Safety: Environmental principles, sustainable resource use, human safety, and preventive measures against hazards.

5. Introduction to Business Analytics: Data collection, processing, interpretation, and the role of analytics in managerial decisions.

6. Introduction to Finance: Financial concepts, markets, investments, corporate finance, risk management, and financial planning.

7. Career Design: Professional goal setting, career planning, self-presentation, CV preparation, interviews, personal branding, and networking.

8. Artificial Intelligence: Machine learning, neural networks, deep learning, computer vision, NLP, and autonomous systems applications.

9. Corporate Finance: Financial management, planning, investment decisions, capital management, and corporate structures.

10. Micro- and Macroeconomics: Economic principles, supply-demand analysis, market mechanisms, macroeconomic indicators, and sustainable development.

11. Taxation: Tax theory, tax system of Kazakhstan, policy, and regulatory frameworks.

12. Economics Fundamentals: Economic theory, market laws, rational choice, government roles, inflation, and unemployment.

13. Entrepreneurial Law of Kazakhstan: Legal framework for business, contracts, taxation, and rights/responsibilities of entrepreneurs.

14. Accounting Principles: Fundamentals of accounting, financial statements, auditing, and digital accounting technologies.

15. BI Systems and Business Analytics: Power BI, Tableau, Qlik Sense, Google Data Studio, data integration, dashboards, and analytical reporting.

16. Project Management: Project lifecycle, planning, execution, monitoring, risk management, and inclusive team management.

17. Big Data Analysis in Finance: Methods for analyzing large financial datasets, clustering, regression, and predictive analytics.

18. Computational Modeling in Economics: Regression analysis, time series modeling, Excel, and Gretl for economic forecasting.

19. Marketing: Market analysis, consumer behavior, product management, pricing, promotion, and marketing research.

20. Machine Learning for Financial Forecasting: Algorithms for price prediction, regression, clustering, and neural networks applied to finance.

21. International Corporate Analytics: IFRS reporting, corporate performance analysis, and global financial decision-making.

22. Management: Strategic planning, leadership, personnel management, decision-making, motivation, and organizational structures.

23. Blockchain and Cryptocurrency Basics: Decentralized systems, smart contracts, cryptocurrencies, and digital financial systems.

24. Digital Technology Fundamentals: Python, SQL, digital tools, and computational thinking.

25. Data Analysis Programming: Python libraries (Pandas, NumPy, Matplotlib) for data processing, analysis, and visualization.

26. Modern Business Communications: Professional writing, presentations, negotiation, conflict resolution, teamwork, and virtual communication.

27. Statistics: Descriptive and inferential statistics, probability, data distributions, visualization, and hypothesis testing.

28. Management Theory: Management concepts, models, leadership, motivation, communication, and decision-making frameworks.

29. Financial Change Analytics: Analysis of financial deviations, reasons, consequences, and strategic recommendations.

30. Financial Literacy and Sustainable Development: Personal and corporate finance, responsible financial behavior, sustainable economic, social, and environmental practices.

31. Financial Reporting and Analysis: Balance sheets, income statements, cash flow analysis, financial ratios, and trend analysis.

32. Financial Risk Management: Risk identification, evaluation, mitigation, and mathematical/statistical modeling.

33. Digital Transformation and FinTech: Digital finance trends, fintech solutions, AI, blockchain, and payment systems.

34. Language Technologies for Financial Analysis: NLP, text classification, semantic analysis, and speech recognition in finance.

35. Financial Analytics and Strategy: Financial data analysis, KPI evaluation, investment project assessment, and strategy development.

36. Financial Modeling: Building models for financial planning, project evaluation, risk management, and strategic decisions.

37. Economic Analysis and Financial Diagnostics: Assessing company financial health, solvency, profitability, and financial flows.

38. Automated Investment Strategies: Robo-advisors, algorithmic investment models, and portfolio automation.

39. Investment Project Analysis: Discounted cash flow, NPV, IRR, and project evaluation methods.

40. Fraud Analytics: Detecting and preventing fraud, monitoring suspicious transactions, and analytical tools for fraud management.

41. Crisis Financial Management: Financial planning, resource allocation, asset protection, and strategies in crisis situations.

42. Financial Audit: Verification of financial operations, internal controls, compliance, and fraud detection.

43. Graphical Financial Analysis: Visual representation of financial data using charts, diagrams, and dashboards.

44. AI in Business Analytics: Integration of AI tools for decision-making, predictive analytics, and automation.

45. Neural Network Financial Analysis: Neural networks for forecasting, anomaly detection, risk evaluation, and automation.

46. Compliance Management: Regulatory compliance, risk management, RegTech applications, and ethical business practices.

47. Financial Cybersecurity: Protecting financial systems, data confidentiality, cyber threat prevention, and incident response.

Conclusion:
The program equips graduates with advanced financial, analytical, and digital competencies, combining finance, business analytics, AI, and sustainable development principles. Graduates can work as financial analysts, business analysts, risk managers, investment strategists, or fintech specialists, capable of leveraging digital technologies and data-driven insights in a global business environmen