Financial Analysis and Modeling

2026/2027

Academic Year

ENG

Instruction in English

3

ECTS credits

Delivered at:

Department of Finance

Course type:

Compulsory course

When:

1 year, 2 module

Instructor

Churakova, Iya

Course Syllabus

Abstract

This discipline refers to a cycle of special disciplines and a block of disciplines that provide basic training. The study of the discipline "Financial analysis" is based on the following disciplines: Economics of the enterprise; Company valuation Microeconomics; Accounting. For the effective development of this academic discipline, students must have the following knowledge and competencies: know and understand the basics of the enterprise economy; have an idea about the management system at the enterprise; know the basics of business law; know the classification of costs and types of costing.

Learning Objectives

• Learn to make analysis of financial statements, make conclusions upon the financial performance and position of a company
• Analyze financial statements and financial reports of companies of different industries
• Learn how to analyze banking financial state
• Describe and explain essential principles of forecasting financial statements
• Learn how to build pro-forma statements
• Identify and apply various approaches to forecasting of financial statements

Expected Learning Outcomes

• Evaluate a company’s financial position by applying both conventional and contemporary analytical tools.
• Detect and interpret key financial strengths, vulnerabilities, and interrelationships that shape a company’s overall position.
• Develop predictive models to assess a company’s future financial stability and viability.
• Demonstrate comprehension of fundamental financial management techniques and core financial calculation methods.
• Recognise the significance of identifying fraud within financial statements and related documentation that impacts a company’s operations and reputation.
• Apply established fraud detection methodologies using financial statements, including Beneish’s M-score, Benford’s Law, and matched time-series analysis.
• Define the concept of a company’s financial health and identify its key constituent elements and indicators.
• Conduct a comprehensive assessment of a company’s financial health by selecting and implementing suitable analytical approaches.
• Explain the nature of financial risk and articulate its potential effects on a company’s business activities and strategic outcomes.
• Interpret and apply key audit evidence standards (ISA) when evaluating the reliability of financial data and supporting documentation during financial analysis.
• Master foundational algorithms for constructing and utilising financial distress prediction models, and demonstrate their practical application to real-world company performance data.
• Perform scenario analysis and stress testing to assess a company’s resilience under adverse economic conditions, aligning with ACCA’s emphasis on forward-looking risk assessment and prudent financial judgement.

Course Contents

• Topic 1. Analysis of the financial statements
• Topic 2. Predicting financial distress of companies:indicators and models
• Topic 3. Fraud detection methods
• Topic 4. Financial health of the Company
• Topic 5. Financial modelling

Assessment Elements

• Module 4 — Financial Health Assessment
  Assessment type: Integrated health scorecard + scenario commentary. Brief description: Students build a composite financial health assessment combining liquidity, solvency, profitability, and cash flow metrics. They produce a scoring system, interpret the overall health status, and add a short stress scenario commentary (e.g., “What if revenue drops 15%?”). Grading focuses on holistic thinking, balanced use of quantitative and qualitative factors, and practical relevance of conclusions.
• Module 1 — Analysis of Financial Statements
  Assessment type: Case-study analysis + short written conclusion. Brief description: Students analyse a real company’s financial statements using horizontal, vertical, and ratio analysis. They must identify key trends, explain inter-statement relationships, and draw evidence-based conclusions about the company’s performance and position. Focus is on accuracy of calculations, logical reasoning, and clarity of insights.
• Module 3 — Fraud Detection Methods
  Assessment type: Fraud-detection simulation + risk-flag report. Brief description: Using sample financial data, students run fraud-detection tools (Beneish M-score, Benford’s, time-series checks), identify potential anomalies, and compile a concise risk-flag summary. They must explain how each method contributes to overall assurance and link findings to ISA principles on professional scepticism and evidence reliability.
• Module 2 — Predicting Financial Distress
  Assessment type: Model application and comparative report. Brief description: Students apply at least three distress-prediction models (e.g., Altman’s Z-score, Taffler, Zaitseva) to a given company’s reports, compare results, discuss limitations, and justify which model is most appropriate for the specific context. Emphasis is on correct formula implementation, interpretation of scores, and critical evaluation of outcomes.
• Module 5 — Financial Modelling
  Assessment type: End-to-end financial model + user guide. Brief description: Students construct a dynamic financial model (in Excel or similar) that forecasts key outputs (cash flow, profit, distress indicators) based on realistic assumptions. The submission includes the working model and a 1–2 page user guide explaining inputs, key drivers, sensitivity tests, and how to interpret outputs. Marking criteria cover technical accuracy, usability, transparency, and alignment with strategic decision-making needs.

Interim Assessment

• 2026/2027 2nd module
  0.2 * Module 1 — Analysis of Financial Statements + 0.2 * Module 5 — Financial Modelling + 0.2 * Module 4 — Financial Health Assessment + 0.2 * Module 2 — Predicting Financial Distress + 0.2 * Module 3 — Fraud Detection Methods

Bibliography

Recommended Core Bibliography

• Financial Statement Fraud and Financial Stability. (2019). Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.A19809A6
• Казакова Н.А., Дун И.Р., Бобкова М.П. - Financial analysis: collection of case studies - ИНФРА-М - 2018 - https://znanium.ru/catalog/product/972205 - 972205 - ZNANIUM

Recommended Additional Bibliography

• DeAngelo, H., DeAngelo, L., & Wruck, K. H. (2002). Asset liquidity, debt covenants, and managerial discretion in financial distress:*1: the collapse of L.A. Gear. Journal of Financial Economics, (1), 3. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.a.eee.jfinec.v64y2002i1p3.34

Authors

• Churakova Iiia Iurevna
• Soloveva Ekaterina Evgenevna