An end-to-end Business Analytics project that evaluates the financial performance of Indian listed companies using real-world financial statement data and transforms it into actionable business insights through financial ratio analysis, statistical techniques, and data visualization.
Financial statements contain large amounts of information, but comparing companies across industries and identifying meaningful business insights can be challenging.
This project analyzes five years of financial statement data for 47 Indian listed companies to evaluate profitability, liquidity, leverage, growth, operational efficiency, and overall financial health. Using Business Analytics techniques such as financial ratio analysis, exploratory data analysis, correlation analysis, and company benchmarking, the project transforms raw financial data into actionable insights that support strategic business and investment decision-making.
The project follows a complete analytics workflow—from collecting and preparing real-world financial data to interpreting results and generating business recommendations.
| Metric | Details |
|---|---|
| Companies Analysed | 47 Indian Listed Companies |
| Financial Years | FY2022 – FY2026 |
| Industries Covered | 15+ Sectors |
| Financial Ratios Calculated | 10+ |
| Charts & Visualisations | 20+ |
| Programming Language | Python |
| Data Sources | Screener.in & Yahoo Finance |
Investors, financial analysts, and business managers often rely on numerous financial statements to assess company performance. However, manually comparing companies across multiple industries is time-consuming and often fails to reveal broader financial trends.
This project addresses the following question:
How can financial statement analytics be used to evaluate company performance and generate actionable business insights for better strategic and investment decision-making?
This analysis aims to answer questions such as:
- Which companies demonstrate the strongest financial health?
- Which sectors consistently outperform others?
- How do profitability, leverage, and liquidity influence business performance?
- Which financial indicators are most closely associated with long-term success?
- Which companies exhibit sustainable revenue and profit growth?
- How can financial statement analysis support strategic business decisions?
The project demonstrates how real-world financial statement data can be transformed into meaningful business insights. By benchmarking companies using standardized financial metrics, the analysis helps identify financially healthy organisations, compare sector performance, evaluate financial risks, and support data-driven business and investment decisions.
Financial Statement Data
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Data Collection
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Data Cleaning & Validation
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Financial Ratio Calculation
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Exploratory Data Analysis
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Statistical Analysis
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Sector Benchmarking
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Company Performance Evaluation
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Business Insights
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Strategic Recommendations
The project follows an end-to-end Business Analytics workflow.
- Collected financial statement data from Screener.in
- Retrieved market information using Yahoo Finance
- Consolidated five years of financial information for Indian listed companies
- Missing value assessment
- Duplicate removal
- Data standardisation
- Consistency checks
- Financial data validation
Calculated and analysed key financial metrics including:
- Revenue Growth
- Profit Growth
- Return on Assets (ROA)
- Return on Equity (ROE)
- Operating Margin
- Net Profit Margin
- Debt-to-Equity Ratio
- Asset Turnover Ratio
- Free Cash Flow Margin
- Cash Flow to Profit Ratio
Performed:
- Company benchmarking
- Sector-wise comparison
- Distribution analysis
- Outlier detection
- Trend analysis
- Correlation analysis
Applied:
- Correlation Analysis
- Financial Performance Benchmarking
- Relationship Analysis between key financial indicators
Converted quantitative analysis into business insights and strategic recommendations.
This project demonstrates practical application of:
- Financial Statement Analysis
- Business Analytics
- Financial Ratio Analysis
- Exploratory Data Analysis (EDA)
- Statistical Analysis
- Business Insight Generation
- Strategic Decision Support
- Data Storytelling
- Data Visualization
Some of the major findings from the analysis include:
- Companies with stronger profitability generally demonstrated higher capital efficiency.
- Lower financial leverage was associated with improved profitability across multiple industries.
- High revenue growth alone did not necessarily indicate superior financial performance.
- Sector benchmarking revealed significant differences in profitability and operational efficiency.
- A composite financial health framework provided a more balanced assessment than relying on individual financial ratios.
The following visualisations highlight the key analytical findings of the project. Rather than presenting raw financial statements, the analysis transforms financial data into business insights through benchmarking, financial ratio analysis, trend analysis, and statistical relationships.
A composite scoring framework was developed by integrating profitability, leverage, liquidity, efficiency, and growth metrics to benchmark companies on overall financial performance. This provides a more holistic assessment than relying on any single financial ratio.
Business Insight
- Identifies financially strong and underperforming companies using multiple financial dimensions.
- Demonstrates how composite scoring can support investment screening and strategic business evaluation.
Correlation analysis was performed to understand relationships between key financial indicators including profitability, leverage, cash flow, operational efficiency, and company size.
Business Insight
- Highlights financial metrics that move together and identifies potential performance drivers.
- Supports data-driven interpretation of profitability, leverage, and operational efficiency.
Sector-wise benchmarking compares median Return on Equity (ROE) and Net Profit Margin across industries to evaluate capital efficiency and profitability.
Business Insight
- Identifies industries demonstrating stronger financial performance.
- Enables meaningful comparison of profitability and operational efficiency across sectors.
Five-year Revenue CAGR was analysed to identify companies demonstrating consistent long-term business growth rather than simply large revenue figures.
Business Insight
- Highlights companies delivering sustained growth over multiple financial years.
- Distinguishes long-term growth leaders from companies with high revenue but slower expansion.
Companies were benchmarked using Return on Equity (ROE) to compare their effectiveness in generating shareholder returns and utilizing invested capital.
Business Insight
- Identifies capital-efficient companies across industries.
- Demonstrates comparative financial performance using one of the most widely used profitability metrics.
Through this project, real-world financial statement data was transformed into actionable business insights by applying financial ratio analysis, exploratory data analysis, statistical techniques, and company benchmarking. The analysis demonstrates how Business Analytics can support financial performance evaluation, strategic decision-making, and investment analysis across multiple industries.
Based on the analysis, the following recommendations were identified:
- Benchmark against financially stronger sectors to identify operational best practices.
- Monitor leverage levels to improve long-term financial stability.
- Focus on sustainable profitability rather than revenue growth alone.
- Improve cash flow management to strengthen liquidity.
- Use financial ratio benchmarking to support strategic planning and investment decisions.
financial-performance-analytics/
│── notebook/
│ Financial_Performance_Analytics.ipynb
│── data/
│ ├── raw/
│ └── processed/
│── images/
│── reports/
│── README.md
│── requirements.txt
│── LICENSE
│── .gitignore
- Python
- Pandas
- NumPy
- Matplotlib
- Seaborn
- SciPy
- Scikit-learn
- BeautifulSoup
- yfinance
- Jupyter Notebook
- Git
- GitHub
Clone the repository
git clone https://github.com/sakshi2992/financial-performance-analytics.gitInstall dependencies
pip install -r requirements.txtLaunch Jupyter Notebook
jupyter notebook notebook/Financial_Performance_Analytics.ipynbFuture improvements include:
- Financial forecasting using time-series models
- Interactive Power BI dashboard
- Company clustering using advanced machine learning techniques
- Automated financial data collection pipeline
- Peer valuation and investment screening module
This project was developed as part of my Business Analytics portfolio to demonstrate the complete analytics lifecycle—from collecting real-world financial statement data to generating business insights and strategic recommendations. It reflects my interest in financial analytics, analytics consulting, and data-driven decision-making.
Sakshi Gupta
Integrated MBA (Business Analytics + Data Science & AI)
Indian Institute of Technology (IIT) Mandi
📧 Email: im24037@students.iitmandi.ac.in